By Enrico Fantaguzzi – Co-founder Digital Fashion Academy

Reading time:

3–5 minutes

Key topics: AI image creation, fashion videos, oragnization and management

Today, AI solutions are transforming this heavy cost center into an agile, highly creative powerhouse, completely bypassing traditional logistical hurdles.

Elevating customer experience at accessible cost

Virtual Try-On: Elevating Customer Experience and Sustainability

One of the most impactful consumer-facing applications of AI in fashion is the “virtual try-on”. Startups like the Milan-based Dual Me have developed innovative tools that can be easily integrated into fashion e-commerce platforms, allowing users to upload a personal photo and see exactly how a garment will fit on them before making a purchase.

By enabling consumers to see how colors and fits suit them personally, brands are significantly improving their e-commerce conversion rates. Furthermore, this technology aims at lowering return rates, which not only mitigates heavy financial burdens for brands but also severely reduces the negative environmental impacts associated with reverse shipping.

Unprecedented speed and operational efficiency in image creation.

Photo Studio Quality in Seconds with AI

For fashion professionals, AI offers unprecedented speed and operational efficiency. Through smart, user-friendly dashboards, brand managers can create high-end campaign imagery with just a few clicks.

The workflow is remarkably simple:

1. Users upload standard “still-life” images of garments or accessories, frequently utilizing existing shots from their B2B virtual showrooms.
2. They then select a model from a preset roster of diverse virtual models, or upload photographs of their own contracted human models.
3. Finally, by typing a brief text prompt, they instruct the AI on the desired camera angle, background location, and creative direction.

The AI instantly merges these elements, delivering cohesive, professional images that rival traditional, high-end photoshoots. Beyond static images, these AI platforms can also generate short, highly consistent video clips starting from just five seconds in length, which are perfect for social media reels and e-commerce product pages. Because producing real video content is traditionally even more expensive than photography, AI video generation offers massive cost savings for the industry.

How much does AI photography cost?

Hybrid Models and Creative Flexibility

While many brands opt for a self-service software-as-a-service (SaaS) model, which can start at highly accessible prices like €19.99 per month, others prefer a hybrid or delegated approach.

Traditional product photography studios like Squareshot, which operates a fully equipped studio in Brooklyn, now offer AI-powered visual production alongside their physical model shoots and flat-lay photography services.

Squareshot allows brands to experiment with AI visuals based on their product shots or references, offering AI campaigns starting at $95 per image or $975 for a 5-image set.

Alternatively, AI providers can take a brand’s creative brief, still-life product photos, and brand guidelines to fully manage the generation of an entire customized package of images and videos, saving the brand immense time.

Crucially, these AI workflows offer immense versatility. Professionals can seamlessly adapt the same generated image to multiple formats and styles, ranging from a clean standard e-commerce look to a highly creative editorial style, tailoring the dimensions perfectly for a website homepage, a LinkedIn update, or an Instagram post, all within a single dashboard without external software.

Maintaining model consistency across these diverse assets is also becoming easier, with advanced methods like “Face Reference” ensuring the exact same model identity is kept across all visuals and poses.

Is AI photography law compliant?

What are the risks

Navigating AI Compliance As brands integrate these powerful tools, they must also navigate the evolving legal landscape, particularly in Europe. The EU Artificial Intelligence Act is the world’s first comprehensive regulation on AI by a major regulator, and it is already setting a global standard. The Act categorizes AI applications into three risk levels:

1. unacceptable risk (which is banned),
2. high-risk (subject to strict legal requirements), and
3. low risk for largely unregulated applications.

For fashion businesses adopting AI, understanding these legal obligations is critical. Small and medium-sized enterprises (SMEs) and startups can utilize tools like the online AI Act Compliance Checker to quickly discover how the regulation affects them. Furthermore, developers providing the General-Purpose AI (GPAI) models that power these fashion image generators must adhere to specific guidelines and a Code of Practice to ensure compliance and transparency under Chapter V of the Act.

Ultimately, the integration of AI in fashion photography is not a passing trend. It is a fundamental evolution that optimizes daily operational workflows, slashes production costs, and creates a more engaging, sustainable, and personalized retail experience for the modern consumer.

Photoshooting AI solutions

FAQs

Shopify has significantly expanded its AI capabilities over the past two years, introducing tools that support merchants across the entire value chain: from product creation to merchandising, marketing automation, and store optimisation.

For fashion brands operating in a competitive digital environment, understanding how to leverage these AI-powered tools can create a measurable advantage in efficiency and performance.

Below are 10 Shopify AI features worth knowing in 2026.

1. Shopify Magic – AI Product Description Generation

Creating compelling product descriptions at scale is one of the most time-consuming tasks for eCommerce teams.

Shopify Magic allows merchants to automatically generate product descriptions based on a few keywords. The AI can adapt tone of voice, highlight key product benefits, and produce SEO-friendly content that improves organic visibility.

For fashion brands managing large seasonal collections, this feature significantly reduces time-to-market.

Key benefit: faster product launches with consistent brand voice.

2. AI-Driven Product Attribute Suggestions

Structured product data is essential for navigation, filtering, and search optimisation.

Shopify AI can automatically suggest relevant product attributes such as materials, colours, occasions, fits, or style categories. This improves product discoverability and helps customers find products more easily.

For fashion eCommerce, enriched product data also improves internal search performance and supports better recommendation algorithms.

Key benefit: improved product discoverability and conversion rates.

3. AI Image Editing and Visual Enhancement

Product imagery plays a critical role in fashion eCommerce conversion rates.

Shopify AI tools can automatically remove backgrounds, adjust lighting conditions, and generate visual variations of product images. This helps brands maintain visual consistency while reducing the cost and time required for post-production.

AI image enhancement is particularly useful when working with large product catalogues or frequent collection drops.

Key benefit: improved visual quality with reduced production effort.

4. Personalised AI Block Creation for Store Content

AI can assist in creating personalised content blocks that adapt to different customer segments.

Merchants can generate dynamic promotional banners, featured collections, or storytelling modules tailored to customer preferences or behaviours.

For fashion brands, this means the ability to create more relevant shopping experiences without manually designing multiple versions of the same content.

Key benefit: more relevant content experiences that increase engagement.

5. Sidekick – Shopify’s AI Commerce & Marketing Assistant

Sidekick is Shopify’s AI assistant designed to support merchants in analysing store performance and identifying optimisation opportunities.

Users can ask questions in natural language, such as:

• Which products are trending?
• Why did conversion rates change last month?
• What actions could increase revenue?

Sidekick provides data-driven insights that help merchants make more informed strategic decisions.

Key benefit: easier access to actionable insights.

Creation of marketing segments with AI

When you need to create a segment for a direct marketing campaign, for example if you need to target “registered users speaking a specific language” you can ask Sidekick to create a segment that you can then use for your direct email marketing campaign

6. AI-Supported Store Configuration with Sidekick

Sidekick also supports operational tasks such as configuring store settings, shipping rules, and promotional conditions.

Instead of manually navigating multiple configuration panels, merchants can request guidance or automate setup tasks through AI suggestions.

This reduces complexity and accelerates store optimisation processes.

Key benefit: faster and more efficient store management.

7. AI Email Marketing Suggestions

Shopify Email integrates AI to suggest subject lines, messaging structure, and campaign ideas.

The AI analyses customer behaviour patterns to recommend content that is more likely to resonate with target audiences.

For fashion brands, this can improve engagement metrics such as open rates and click-through rates.

Key benefit: improved email marketing performance.

8. AI Email Flow Creation

Automated email flows are essential for lifecycle marketing strategies.

Shopify AI can assist in generating email sequences for:

• welcome series
• abandoned cart reminders
• post-purchase follow-ups
• re-engagement campaigns

AI reduces the complexity of creating marketing automation workflows while ensuring communication consistency.

Key benefit: faster implementation of lifecycle marketing strategies.

9. Smart FAQ and AI Customer Support Automation

AI-powered chat solutions can automatically respond to frequently asked customer questions, improving response times and customer satisfaction.

Typical use cases include:

• delivery information
• return policies
• product details
• order tracking

Automation allows customer support teams to focus on higher-value interactions.

Key benefit: scalable customer service operations.

10. AI-Powered Insights and Recommendations

Shopify AI can identify patterns in sales performance, customer behaviour, and merchandising effectiveness.

The system can suggest optimisation opportunities such as:

• pricing adjustments
• product bundling ideas
• merchandising improvements
• promotional timing recommendations

These insights support more data-driven decision-making.

Key benefit: smarter commercial strategies.

Final Thoughts

AI is not replacing eCommerce professionals — it is enhancing their capabilities.

The competitive advantage comes from understanding how to integrate AI tools into digital workflows and business strategy.

For fashion brands, AI adoption can improve operational efficiency, increase personalisation, and support scalable growth.

At Digital Fashion Academy, we help professionals and companies develop the skills needed to leverage AI effectively across eCommerce, digital marketing, and customer experience.

Understanding how to use these tools strategically is becoming an essential competence for digital fashion professionals.

Learn Shopify for Fashion

Discover our Shopify online course

Starting September 2026, the Shopify for Fashion Online Course will take you through the creation of a professional ecommerce for fashion with Shopify. Enrol now or contact us to request information

Interview with Andrea Pertici, CIO at Global Fashion & Luxury Brands

How is AI transforming strategic processes in fashion and luxury?

AI is transforming strategic processes in the fashion and luxury sectors by necessitating a shift from purely technological implementation to a holistic focus on organizational culture, risk management, and data governance. According to industry experts, the integration of AI requires the same level of strategic and organizational vision previously applied to innovations like Blockchain or ERP systems, as technology alone cannot solve business problems and may even create new ones without a clear strategy.

The transformation of strategic processes is evident in the following key areas:

• Risk Assessment and Governance: With the introduction of regulations such as the European AI Act, companies must now evaluate all AI investments and implementations based on the level of risk they introduce to the organisation. Strategies must account for four levels of risk, ranging from “unacceptable” (which must be avoided) to “minimal” risk. Furthermore, leadership must manage “Shadow AI”—the phenomenon where generative AI interfaces allow any employee to introduce digital tools independently, bypassing standard vetting processes and creating potential security risks.
• Economic and Financial Planning: AI implementation is fundamentally altering cost structures; it is typically an operating cost (OpEx) that directly impacts a company’s profit margins. Unlike previous IT evolutions, the introduction of AI does not necessarily reduce traditional IT costs, and recovering these expenses through efficiency gains, sales increases, or personnel reduction is currently difficult in the fashion sector. Consequently, rigorous business plans are essential, as current data suggests the success rate for AI applied to the value chain is only around 5%,.
• Data Consolidation as a Foundation: A successful AI strategy relies heavily on an organisation’s capacity to consolidate and valorise its own data. The foundation of any AI initiative must be integrated processes and data; without this, companies risk “vendor lock-in,” where they lose control over data and competencies to external services, retaining control only over payment processing.
• Process Optimisation vs. Sub-optimisation: Strategic planning must ensure that applying AI to specific use cases, such as value chain transformation, does not sub-optimise other areas,. Decision-makers must evaluate whether to develop, assemble, or buy services while ensuring that optimising one process does not simply shift costs to another part of the organisation.

Ultimately, the successful transformation of strategic processes depends less on the technology itself and more on the culture and identity of the company, ensuring that AI adoption is driven by a clear understanding of business needs rather than spontaneous adoption.

What are the primary risks of adopting AI in organisations?

The primary risks of adopting AI in organisations can be categorised into regulatory, security, financial, and strategic challenges:

Regulatory and Compliance Risks With the introduction of the AI Act in Europe, companies face strict compliance obligations based on four levels of risk, ranging from “minimal” to “unacceptable”. Organisations must carefully evaluate investments to ensure they avoid “unacceptable” risks, such as unauthorised facial recognition or social engineering, which are prohibited.

Security and Governance Risks (“Shadow AI”) A significant risk is the emergence of “Shadow AI”, a phenomenon where the ease of access to generative AI (conversational interfaces) allows any employee to introduce digital tools independently. This bypasses standard vetting processes, meaning individuals can subscribe to and use instruments that may introduce security vulnerabilities or data leaks without the organisation’s oversight.

Financial and Economic Risks The financial implications of AI adoption pose serious risks to profitability:

• Impact on Margins: AI is typically an operating cost (OpEx), which directly affects profit margins.

• Additive Costs: Unlike previous technological shifts, AI does not necessarily reduce traditional IT costs; instead, it tends to be an additive expense. While revenues for AI vendors are projected to grow significantly, this implies increased costs for client companies.

• Low Success Rates: Returns on investment are not guaranteed. When applied to complex processes like the value chain (rather than simple personal productivity), the success rate is estimated to be as low as 5%,.

• Difficulty in Cost Recovery: Recovering these costs through personnel reduction, efficiency gains, or sales increases is currently difficult within the fashion and luxury sectors.

Strategic and Operational Risks

• Vendor Lock-in: There is a major risk of entering a state of “lock-in”, where an organisation relies so heavily on external services that it loses control over its own data and internal competencies. In this scenario, the company effectively retains control only over paying the invoices, while the core intelligence resides externally.

• Process Sub-optimisation: Without a holistic view, there is a risk of optimizing one specific process while inadvertently sub-optimising others, simply shifting costs or inefficiencies to a different part of the organisation rather than eliminating them.

• Lack of Strategic Vision: Adopting AI spontaneously without a clear organisational and cultural strategy can create more problems than it solves in the short term

Why is the success rate for business AI implementation currently low?

he success rate for AI implementation in business processes—specifically regarding the transformation of the value chain—is estimated to be as low as 5%. This low success rate is attributed to several structural, financial, and organisational factors:

• Complexity of Value Chain Integration: While “embedded” AI tools for personal productivity (e.g., in browsers or office suites) are easily adopted, applying AI to complex corporate processes and the value chain is far more difficult. This type of implementation requires deep integration rather than simple adoption.

• Additive Costs and ROI Challenges: Unlike previous technological shifts, introducing AI does not necessarily reduce traditional IT costs; instead, it often acts as an additive Operating Cost (OpEx) that directly impacts profit margins. Recovering these costs—whether through personnel reduction, efficiency gains, or increased sales—is currently proving difficult in the fashion and luxury sectors.

• Data and Process Maturity: Success depends heavily on an organisation’s existing culture and its ability to consolidate and valorise its own data. Without a solid foundation of integrated data and processes, companies cannot effectively deploy AI and risk “vendor lock-in,” where they rely entirely on external services and lose control over their internal competencies and assets.

• Risk of Sub-optimisation: There is a strategic risk that optimising one specific process via AI may inadvertently sub-optimise other areas, simply shifting costs or inefficiencies to different parts of the organisation rather than eliminating them.

• Hidden Implementation Costs: The cost of AI is never limited to the service fee alone; it involves a significant learning curve, as well as costs related to training, infrastructure, and networking

What does ‘Shadow AI’ mean for fashion industry security?

“Shadow AI” in the context of the fashion industry refers to the phenomenon where employees independently subscribe to and introduce AI tools into the company without official oversight or IT vetting.

According to Andrea Pertici, a CIO for global fashion brands, this presents specific security implications:

• Bypassing Safety Governance: The primary risk is that these tools bypass the rigorous risk assessments now required by regulations like the European AI Act. Companies are legally obliged to evaluate AI implementations against four levels of risk (from “minimal” to “unacceptable,” such as unauthorised facial recognition or social engineering), but Shadow AI prevents this evaluation from happening.

• Zero-Barrier Access: Unlike previous complex technologies, the “conversational interface” of generative AI has removed all technical barriers. Any employee who can type or speak can now introduce digital instruments that may contain security vulnerabilities, effectively creating a hidden layer of technology that the organisation cannot control or secure.

• Evolution of Shadow IT: It is described as the modern evolution of “Shadow IT,” where the ease of access to powerful tools increases the likelihood of data leaks or compliance violations because the central organisation is unaware the technology is even being used

How can brands avoid ‘vendor lock-in’ while using AI?

To avoid “vendor lock-in,” brands must ensure they do not reach a state where data, services, and competencies reside entirely externally, leaving the company with control over nothing but the payment of invoices.

According to the sources, the primary strategy to prevent this involves establishing a strong internal foundation rather than simply purchasing solutions. This includes:

• Consolidating and Valorising Internal Data: The crucial starting point is the organisation’s capacity to consolidate its own data. A company must have integrated processes and data as a “foundation”. Without this internal backbone, the company becomes overly reliant on the vendor’s infrastructure to manage its core assets.

• Strategic Sourcing Decisions: Once that data foundation is established, the company is better positioned to make informed strategic decisions about whether to “develop, assemble, or buy” specific services on a case-by-case basis,. This allows the brand to integrate external AI where efficient without handing over total control of the value chain.

• Retaining Internal Competencies: The risk of lock-in is explicitly linked to the externalisation of competencies. Therefore, brands must ensure that while they may use external tools, the strategic understanding and management of these processes remain within the company to avoid dependency.

How can fashion brands prevent employees from using Shadow AI?

Preventing “Shadow AI” is not presented as a simple technical block, but rather as a challenge requiring a shift in organisational strategy, culture, and governance.

Fashion brands can address and mitigate the use of Shadow AI through the following strategic measures:

• Implementing Formal Risk Assessment (AI Act): Companies must replace spontaneous adoption with a formal evaluation process. Under regulations like the AI Act, organisations are obligated to evaluate all AI implementations based on four levels of risk, ranging from “minimal” to “unacceptable” (such as unauthorised facial recognition or social engineering). By enforcing this vetting process, brands ensure that no digital tool enters the company ecosystem without passing through this governance filter.

• Shifting from Spontaneous to Strategic Adoption: The primary driver of Shadow AI is “spontaneous adoption” by employees. To prevent this, leadership must impose a “strategic, organisational, and cultural vision” similar to past implementations of PLM or ERP systems. The organisation must actively define how AI solves business problems so that employees do not feel the need to independently seek outside tools.

• Centralising Data and Competencies: A key preventive measure is ensuring the organisation creates a strong internal foundation. By focusing on the “culture and capacity… to consolidate and valorise its own data”, the company provides a legitimate, integrated infrastructure. If the company provides integrated processes and data, it reduces the incentive for employees to use external “Shadow” tools that might lead to “vendor lock-in” or data loss.

Why prevention is difficult: The sources note that preventing Shadow AI is particularly challenging because Generative AI (specifically the conversational interface) has “completely broken down any barrier to usage”. Unlike complex legacy systems, anyone who can type or speak can now independently subscribe to and introduce these tools, bypassing traditional IT hurdles. Therefore, the solution is less about technical barriers and more about corporate culture and adherence to the new regulatory frameworks

Enrico Roselli – Co-founder Digital Fashion Academy. Former CEO of La Martina

Gianluigi Zarantonello – Former Innovation Manager at Valentino

Enrico Fantaguzzi – Co-founder Digital Fashion Academy. Former Manager at Gucci, Tod’s, Yoox

How is AI changing fashion retail?

To create a seamless shopping experience, AI must facilitate a frictionless journey where the customer can move between e-commerce, physical stores, and mobile platforms without being conscious of the channel they are using.

The goal is to make the technology “invisible,” operating in the background to enable users to do whatever comes to mind without technical barriers,.

How can AI help to create a seamless customer experience in Retail

Unified Customer Identity and Recognition

A major hurdle to seamless shopping is the disconnection between online and offline Customer Identities. A customer might be recognised in their local shop but treated as a complete stranger online, or vice versa. AI can bridge this gap by analysing cross-channel data. For instance, AI can leverage a customer’s online browsing history, where they may spend time without buying, to enhance their experience and opportunities when they eventually enter a physical retail store,. This requires building technical capabilities to recognise the customer at various touchpoints, creating a holistic view of their journey.

Hyper-Personalisation via Generative AI

AI is moving personalisation beyond traditional customer segmentation. Previously, retailers might identify a segment but still show the same content to everyone within it due to production limitations. Through generative AI, retailers can now unlock data to produce unique content tailored to specific individuals based on their interactions and intent. This allows for a highly personalised experience that still adheres to the brand’s overall creative vision,.

Frictionless Payments and Loyalty

AI enhances the final stage of shopping, the transaction, by integrating advanced payment systems. Machine learning algorithms contribute to a seamless experience by:

• Scoring transaction reliability to instantly approve valid purchases, thereby improving e-commerce conversion rates.
• Utilising tokenisation and blockchain to create safe connections that integrate directly with loyalty programmes, managing client information securely to further customise the experience.

Agentic AI for Natural Interaction

The emergence of “Agentic AI” changes how users interact with complex software. Rather than forcing customers or employees to navigate rigid interfaces and rules, Agentic AI allows them to use natural language to ask for exactly what they need,. This shifts the paradigm from the user adapting to the software to the software adapting to the user, making the interaction intuitive and removing the complexity of the underlying technology,.

Empowering Physical Retail

Since a significant majority of transactions (around 80%) still occur in brick-and-mortar stores, AI is crucial for enhancing the physical environment. This includes using data to improve store efficiency and potentially integrating robotics for deeper interactions, ensuring the physical space is as responsive and data-informed as the digital one.

How can generative AI produce unique content without losing brand vision?

Generative AI allows companies to produce unique content at scale by unlocking data and production capabilities that were previously limited. Historically, even when retailers identified specific customer segments or “personas,” they were forced to show the same content to everyone within that group due to the difficulty of producing numerous variations. Generative AI solves this by using customer data to create individualised content dynamically.

To ensure this unique content does not compromise the brand vision, the process relies on the following principles:

• Adherence to Core Creativity: The brand vision remains firmly in the hands of the creative director and the company. The content produced by AI serves as variants of this central vision rather than independent creations, ensuring that the foundational aesthetic and message provided to the customer remain consistent.
• Strict Guidelines: Businesses can “teach” the AI to provide outputs that adhere strictly to the exact guidelines of the brand, ensuring that automated content stays within the established identity.
• Human-Centric Finalisation: While AI is excellent for brainstorming and providing “divergent,” out-of-the-box ideas to spark inspiration, human creatives are still considered “much better than AI” at creating the final, polished output. The AI acts as a tool to expand possibilities, not a replacement for the creative mind that defines the brand.

This approach allows brands to move beyond generic segmentation to true personalisation without the fear that the technology will distort the brand image.

How can AI identify customers across online and physical stores?

AI identifies customers across online and physical stores by integrating specific “technicalities” into the customer journey that link data points, rather than relying on “magic” or passive observation.

According to the sources, AI achieves this cross-channel identification through the following methods:

Payment and Loyalty Integration
One of the most effective ways to identify customers is through advanced payment solutions. By applying AI to payments, retailers can use tokenisation and blockchain to create safe, secure connections that link transactions directly to loyalty programmes. This allows the system to instantly recognise the client via their payment method, unlocking their history and preferences to customise the experience without requiring complex manual logins.

Leveraging Digital Intent in Physical Spaces
AI bridges the gap between the two worlds by analysing a customer’s online browsing history to enhance their in-store experience. For example, in the luxury sector, e-commerce conversion rates can be as low as 1%, meaning 99% of visitors are merely browsing. AI can capture this “intent to buy” or interest shown online and make it accessible to store staff when the customer eventually visits a physical location, transforming a “stranger” into a known prospect with specific preferences.

Designing Identification Touchpoints
The sources emphasise that technology alone cannot identify people without a strategy. Retailers must engineer specific “moments in the journey” where the customer is prompted to reveal their identity. Whether through a mobile app interaction, a loyalty scan, or a tokenised payment, these intentional touchpoints provide the data AI needs to connect the online user with the physical shopper.

What are the hidden costs of implementing AI in fashion?

While the surface narrative of AI often suggests a “plug and play” solution, there are several hidden costs and challenges associated with its implementation in the fashion industry.

Unpredictable Financial Costs A significant hidden cost lies in the pricing models of corporate AI tools. While individuals may be accustomed to free versions of tools like ChatGPT, corporate environments face costs based on consumption. This variable pricing makes financial planning highly volatile; while CFOs and boards may request three-year forecasts, it can be difficult for technical leaders to predict consumption costs even one week ahead. Without proper knowledge and management, companies risk wasting money rather than investing it effectively.

Organizational and Cultural Reinvention Implementing AI is not merely a technical update but requires a complete “reinvention of the organization”. The costs involve:

• Cultural Shift: There is a need for a deep change in mindset and culture to adopt these new instruments, as they cannot simply be used from scratch without preparation.
• Education and Literacy: Companies must invest in educating their workforce. There is a risk that without “literacy” (understanding) and “fluency” (ability to use), employees will struggle to adopt the technology.
• Underutilization: A historical hidden cost of technology is that companies often pay for tools with huge potential but only utilize 20% to 25% of their capabilities because they are too complex for staff to use effectively.

Data and Process Preparation Before AI can be effective, significant resources must be spent on the “boring” background work.

• Data Quality: AI operates on the rule of “garbage in, garbage out.” High-quality output requires high-quality structured and unstructured data, necessitating substantial work to clean and organize existing databases.
• Process Mapping: Companies must invest time in mapping their actual processes to understand what they want to achieve, rather than applying AI to obsolete workflows which would result in little more than a faster version of a broken process.

What strategies help manage the consumption-based costs of corporate AI?

To manage the unpredictable consumption-based costs of corporate AI, businesses must shift from a fixed-budget mindset to a value-driven strategy rooted in education and process efficiency. Unlike consumer tools like the free version of ChatGPT, corporate AI vendors typically charge based on consumption, making financial forecasting difficult for CFOs and boards.

Based on the sources, the following strategies help manage these costs:

Invest in “Literacy” and Preparation
The most critical cost-management strategy is education. Leaders must possess “literacy” (understanding) and “fluency” (ability to use) regarding AI technologies. Without deep knowledge, it is impossible to determine whether the organisation is “wasting money or investing money”. Thorough preparation allows companies to unlock actual value, whereas jumping in unprepared leads to financial loss and reduced competitiveness.

Optimise Processes Before Automation
Implementing AI requires a “reinvention of the organization” rather than a simple software installation. A major hidden cost arises from applying AI to obsolete processes; this merely results in a faster version of a broken workflow without generating real value. To control costs, companies must perform rigorous process mapping to ensure the AI is solving a valid problem efficiently.

Focus on Efficiency and Sustainability
Strategies should aim for maximum efficiency across the value chain, from sourcing to logistics and marketing. This approach aligns cost management with sustainability: by using technology to identify and eliminate waste (whether materials or energy), companies can simultaneously reduce costs and meet environmental goals.

Avoid “FOMO” Driven Adoption
Entrepreneurs are advised to be “bold but not a fool.” Rushing to adopt AI due to the “fear of missing out” (FOMO) often leads to wasteful spending on tools that are not fully understood or utilized. Taking the time to understand the specific value proposition for the business ensures that the consumption costs incurred actually drive return on investment.

How can AI identify waste and improve sustainability in fashion?

Based on the sources, AI identifies waste and improves sustainability in the fashion industry by reframing the concept of sustainability from a regulatory “burden” to an exercise in maximum efficiency.

Here is how AI achieves this across the value chain:

Redefining Waste as Inefficiency
AI helps retailers understand that waste—whether it is energy, materials, or products—is simply something that has not been utilised effectively. Instead of viewing sustainability solely as compliance with regulations, AI allows companies to view it as the elimination of inefficiency. If a resource is “put apart because it’s not useful to anyone else,” it represents a financial loss as well as an environmental one.

Granular Visibility and Root Cause Analysis
To improve sustainability, AI acts as a diagnostic tool that illuminates the “road ahead”. It provides access to data across the entire value chain—from sourcing and logistics to sales and distribution. By analysing this data, AI can:

• Pinpoint Origins: Identify exactly where waste is coming from in the production or supply process.
• Analyse Consumption: Monitor and reduce the usage of materials and energy.
• Forecast Accuracy: Help forecast the future to prevent overproduction, ensuring that what is produced is actually needed.

Maximizing Asset Utility
Once waste or potential waste is identified, AI helps determine how to maximise the value of every item produced. If a product fails in its primary channel, AI can calculate the best alternative path, such as:

• Selling the item in a different market.
• Repurposing it for a different use.
• putting it back into circulation rather than discarding it.

Aligning Profit with Planet
The sources highlight that cost reduction and sustainability are now intrinsically linked. With the costs of doing business in fashion (sourcing, advertising, logistics) skyrocketing, AI drives the efficiency needed to lower expenses. This creates a scenario where the “perfect company in terms of efficiency” is also a sustainable one, fulfilling both business objectives and legal requirements (such as those in the European Union) simultaneously.

Key takeaways from NRF 2026

Based on the discussion regarding the NRF (National Retail Federation) and the state of digital transformation leading up to 2026, the key takeaways focus on moving beyond the “hype” of AI to practical, structural, and “invisible” implementations. The sources suggest that by 2026, the industry focus will shift from simply adopting new tools to a fundamental reinvention of the organisation and the customer journey.

Here are the central themes discussed in the context of NRF 2026 and Fashion AI:

1. From Omnichannel to “Seamless” and “Invisible” Experiences The speakers argue that the industry is moving past the concept of “omnichannel,” which can feel disjointed, toward “seamless” experiences. In this model, the customer moves between e-commerce, physical stores, and mobile apps without consciously thinking about the channel.

• Invisible Technology: A major takeaway is that technology should be “invisible,” operating in the background to enable the user’s desires rather than being the focus itself.
• Unified Identity: A critical component of this seamlessness is using AI to bridge the online-offline gap. For instance, using payment tokenisation and blockchain to recognise a customer in a physical store and instantly access their online browsing history and preferences.

2. The Rise of Agentic AI “Agentic AI” is identified as a dominant trend at NRF, though the sources caution that much of it is currently marketing noise.

• Paradigm Shift: True Agentic AI shifts the paradigm from users adapting to software rules to software adapting to users. Instead of navigating complex interfaces, users (both employees and customers) can use natural language to command the software to perform complex tasks, such as creating a landing page by fetching data from disparate databases.
• Current State: While promising, the sources note that the industry is still “far away from actually adopting the real Agentic AI potential,” as it requires robust data structures that many companies currently lack.

3. The End of “Plug and Play” A recurring theme is the demystification of AI as a simple add-on. The sources emphasise that AI is “not plug and play”.

• Organisational Reinvention: Successful implementation requires a complete reinvention of the organisation, including culture shifts and extensive employee education.
• AI Literacy vs. Fluency: There is a distinction made between “literacy” (understanding the concepts) and “fluency” (the ability to use the tools). Leaders must possess both to avoid wasting money on technologies they do not understand.
• Process Mapping: Before applying AI, companies must map and optimise their processes. Applying AI to an obsolete process merely results in a faster version of a broken workflow.

4. Hyper-Personalisation via Generative AI The sources highlight that Generative AI is finally unlocking the true potential of personalisation, which was previously limited by production capacity.

• Scaling Content: Retailers can now use GenAI to produce unique content variants for specific individuals based on their data, solving the problem of having customer segments but only one piece of content to show them.
• Brand Integrity: This can be achieved without compromising the brand vision. The creative director sets the core vision, and AI generates variants that strictly adhere to these guidelines, ensuring consistency while increasing relevance.

5. Sustainability as Efficiency In the context of 2026, sustainability is reframed not as a regulatory burden but as an exercise in maximum efficiency.

• Waste Reduction: AI provides visibility across the value chain (sourcing, logistics, sales), allowing companies to identify “waste” as simply “inefficiency”—resources that are not being used effectively.
• Profit Alignment: By using AI to forecast accurately and maximise asset utility, companies can simultaneously reduce costs and meet environmental standards, such as those in the European Union.

6. The Financial Reality of AI Finally, a practical takeaway for the roadmap to 2026 is the shift in cost structures. Unlike consumer tools, corporate AI often operates on consumption-based pricing.

• Budget Volatility: This makes financial forecasting difficult for CFOs, as costs fluctuate with usage. The sources warn that without proper knowledge (“literacy”), companies risk “wasting money” rather than investing it, making education essential for financial control.

Watch the video

1. AI Literacy and Tech Fluency Understanding AI tools for design (e.g., generative AI for concepts), trend forecasting, customer service, content creation, and supply chain optimization is the top opportunity cited by executives. Brands are scaling AI deeply, requiring professionals who can adapt workflows without losing creative essence.
2. Digital Marketing and E-commerce Expertise Proficiency in platforms like Shopify, Google Analytics, Meta Ads, CRM systems (e.g., Salesforce, Klaviyo), and social media strategies remains critical as brands operate as digital-first entities. Omnichannel thinking, blending online and offline experiences, is essential.
3. Sustainability Knowledge Skills in ethical sourcing, circular economy practices, eco-friendly materials, supply chain transparency, and regulatory compliance (e.g., upcoming laws on unsold stock) are increasingly mandatory, driven by consumer demand and legislation.
4. Data Analysis and Analytics Advanced use of Excel, data tools for merchandising, inventory planning, consumer insights, and performance metrics. Quantitative skills help in trend forecasting and personalized marketing.
5. 3D Design and Digital Tools Mastery of software like CLO 3D, Browzwear, Adobe Suite, or PLM systems for virtual prototyping, reducing waste and accelerating production.
6. Soft Skills: Adaptability, Communication, and Teamwork Critical thinking, curiosity, cross-cultural collaboration, and agility in volatile environments (e.g., tariffs, economic shifts) are valued over purely technical proficiencies.
7. Customer Understanding and Experience Design Insights into consumer behavior, personalization, and omnichannel retail to drive engagement amid value-conscious spending.

To stand out in 2026, focus on building a portfolio showcasing these hybrid skills, e.g., projects using AI for design or data for merchandising. Upskilling via online courses (e.g., in AI tools or sustainability certifications) and a strong LinkedIn presence will be key in a competitive market.

The industry rewards multi-skilled, adaptable professionals who connect creativity with efficiency and ethics

Discover our new Executive Master in AI for Fashion

Sources and further readings

Article written with the help of grok.com

• Fashion industry challenges in 2026: How brands can overcome sustainability, supply chain, and innovation hurdles – Heuritech
• The State of Fashion 2026: When the rules change

Launching an eCommerce website for an affordable jewellery brand is an exciting step, but it’s also one that requires a business plan, a vision and expertise. Too often, brands think of eCommerce as simply “building a website”. In reality, a successful online store is the result of a well-defined process that combines strategy, content, user experience, technology and marketing.

At Digital Fashion Academy, we help brands and retailers design and launch Shopify eCommerce stores that are not only visually appealing, but also ready to sell, scale and compete in a crowded market.

In this article, we’ll walk you through the complete process of setting up a Shopify eCommerce website for an affordable jewellery brand, and explain how our consultancy and implementation service supports you at every step.

Why Shopify Is the Ideal Platform for Affordable Luxury Brands

Shopify is one of the most powerful and flexible eCommerce platforms available today, particularly for fashion and luxury brands. It allows you to:

• Launch quickly without complex technical development
• Manage products, prices and collections easily
• Offer a seamless mobile shopping experience
• Integrate payments, shipping and taxes in a scalable way
• Connect marketing channels such as Google, Instagram and Facebook

For affordable luxury brands, where high volume, mobile traffic and efficient operations are key — Shopify provides the ideal balance between simplicity and performance.

Step 1: Strategy & eCommerce Foundations

Before building anything, we start with strategy, to ensure that the Shopify store is aligned with your brand positioning and commercial goals.

Key activities include:

• Defining the target customer and their buying behaviour
• Clarifying price positioning and value proposition
• Analysing competitors and reference brands
• Identifying key collections and hero products
• Defining the markets as country-language combinations and rules to serve them
• Defining success metrics (conversion rate, average order value, traffic sources)

For affordable luxury brands, strategic clarity is essential to avoid competing only on price and instead build perceived value and trust.

Step 2: Product Content Creation – The Heart of Your Store

Product content is the most critical element of any affordable luxury eCommerce website. No theme or advertising campaign can compensate for weak product presentation.

We support brands in structuring and creating:

• High-quality product photography (studio and/or lifestyle)
• Clear and consistent product naming
• Detailed product descriptions including:
  • Materials and finishes
  • Sizes and dimensions
  • Usage and styling suggestions
  • Care instructions
  • Tags and attributes
• Variants such as colours, sizes or sets

Strong product content increases conversion rates, reduces returns and improves SEO performance.

Step 3: Shopify Store Setup & Visual Experience

Once the foundations are defined, we move into the Shopify setup phase.

This includes:

• Theme selection and customization
• Homepage structure focused on best sellers, collections and trust elements
• Product page layouts optimized for conversion
• Mobile-first design (essential for fashion, jewellery, beauty shopping)
• Consistent branding across all pages

The goal is to create a clean, elegant and trustworthy experience that reflects the brand while remaining fast and easy to navigate.

Step 4: Collections, Navigation & Filters

As your catalogue grows, structure becomes essential for usability and conversion.

We teach you how to configure, and support you in the configuration of:

• Smart collections (by product type, price range, material, style or occasion)
• Clear navigation menus
• Advanced filters to help customers find products quickly
• Internal linking for better SEO and discoverability

For affordable luxury brands, good navigation helps customers browse more products, increasing both time on site and average order value.

Step 5: Legal Compliance & Trust Elements

Trust is fundamental in online luxury sales, especially for new or emerging brands.

We configure all essential legal and trust components, including:

• Privacy Policy
• Terms & Conditions
• Returns and Refund Policy
• Cookie consent and GDPR compliance
• Payment icons, guarantees and customer reassurance elements

This step protects your business and reassures customers at the moment of purchase.

Step 6: Payments, Shipping & Tax Configuration

A smooth checkout experience directly impacts conversion rates.

We set up:

• Payment gateways (Shopify Payments, PayPal, Klarna and others)
• Shipping methods and pricing rules
• Tax configuration based on your markets
• Automated order and customer notifications

Everything is tested to ensure reliability before launch.

Step 7: Marketing & External Integrations

A Shopify store should be built with growth in mind from day one.

We connect and configure:

• Google Analytics and GA4
• Google Ads
• Google Merchant Center for Shopping Ads
• Google My Business
• Meta (Instagram and Facebook)
• Social commerce integrations

This ensures accurate data tracking and allows you to activate digital marketing campaigns immediately after launch.

Step 8: Testing, Launch & Team Training

Before going live, we conduct a full quality check:

• Checkout and payment testing
• Mobile and desktop usability tests
• SEO and performance checks

We provide training and coaching so your team can confidently:

• Manage products and collections
• Process orders
• Handle basic marketing and content updates

How Digital Fashion Academy Supports Your Shopify Project

At Digital Fashion Academy, we don’t just “build websites”. We guide fashion and jewellery brands through the entire eCommerce setup process, combining:

• Fashion & Luxury eCommerce expertise
• Shopify technical implementation
• UX and conversion optimization
• Digital marketing readiness

Our approach is ideal for affordable luxury brands that want a professional Shopify store that is ready to sell, compliant, scalable and aligned with long-term growth.

Ready to Launch or Improve Your Jewellery eCommerce?

If you are planning to launch a Shopify store for your jewellery brand — or want to improve an existing one — our team can support you from strategy to launch and beyond.

Contact us to discuss your Shopify eCommerce project and discover how we can help you build a store that truly performs.

By Aisha Khalid

Aisha K. is Global Vice President of Digital at Ulla Johnson, where she leads global digital strategy and eCommerce growth. With extensive experience in digital transformation, performance marketing, and omni-channel expansion, she specializes in building scalable strategies that enhance customer experience and drive measurable results.
Passionate about blending storytelling with data-driven insights, Aisha has a proven track record of optimizing online platforms, streamlining digital operations, and delivering innovative solutions for the fashion industry.

Working with fashion brands of all sizes, I often see small and emerging labels struggling with similar issues. Running a fashion business today isn’t just about having a great product, it’s about building the right foundations to grow and compete in a very crowded market. Here are some of the most common challenges I see:

1. Lack of Strategic Foundations
Many small brands operate in a reactive way, chasing trends or short-term wins, rather than following a clear strategy. It’s easy to get caught up in daily survival mode, but without a long-term vision and scalable processes, growth becomes very hard.

2. Overdependence on Quick Conversions
The pressure to make sales today often overshadows the need to invest in brand-building and customer loyalty. This “short-term only” mindset can prevent the innovation and risk-taking needed for sustainable growth.

3. Knowledge Gaps
Unlike big players, small brands don’t always have access to market data, best practices, or years of experience to guide them. Founders wear multiple hats, which leaves little time for in-depth analysis or strategy building.

4. Talent & Team Building
“You’re only as good as your team” is especially true in fashion. But for small brands, attracting and retaining skilled talent can be tough. Budget constraints often lead to reliance on freelancers, which makes building a consistent culture or long-term structure harder.

5. Scaling & Operational Complexity
Growing from a founder-led business to an efficient organization requires expertise in areas like logistics, growth marketing, and margin optimization, not just creativity. Many brands spend too much time on aesthetics and not enough on the systems that actually fuel growth.

6. Brand Visibility in a Saturated Market
Standing out is harder than ever. Many young brands lean too heavily (or not enough) on Instagram and TikTok. Without a clear identity, it’s easy to get lost in the noise.

What Should Fashion Start-ups Prioritize?

If you’re building a fashion brand today, where should your focus be? A few key priorities stand out:

• Define a Clear Objective
  Set a concrete, measurable goal (e.g. “Grow to $3M revenue in 5 years”). This becomes your north star for every decision.
  
• Build Strategic Pillars
  Decide on 3 – 5 growth drivers that will get you there: brand positioning, product-market fit, customer acquisition, operations, and customer retention are usually the essentials.
  
• Find and Own Your Niche
  Don’t try to appeal to everyone. Focus on a cultural whitespace, unique aesthetic, or unmet need , and build a loyal community around it.
  
• Strengthen Your Brand Identity
  Trends can be copied, but your brand DNA can’t. Everything from pricing to photography to customer service should reflect your positioning.
  
• Set Up an Efficient Structure
  Invest in the right systems from the start, tech platforms that save time, processes that scale, and documentation that avoids dependency on individuals.
  
• Stay Curious & Connected
  Talk to other founders, go to trade shows, find mentors. Continuous learning and networking are underrated but extremely powerful growth tools.
  

The Must-Have Tools for Small to Medium Fashion Brands

In today’s market, small brands don’t need hundreds of tools , they need the right ones. The secret is simplicity, clarity, and execution. Pick tools that align with your goals, then make sure you’re using them to their full potential.

Here are my essentials:

• E-commerce Platform → Shopify (easy to scale, great UX, app-rich ecosystem).
  
• Analytics & Customer Journey → Google Analytics 4 + Hotjar for heatmaps and session recordings.
  
• Marketing & Retention → Klaviyo for email/SMS automation, segmentation, and predictive insights (CLV, churn, next purchase).
  
• CRM & Customer Data → Shopify + Klaviyo already cover a lot.
  
• Returns & Operations → Loop Returns for a seamless, revenue-retaining return process.
  
• Customer Support → Gorgias, built for e-commerce, integrates with Shopify and social platforms.
  
• Content & Social → Dash Hudson for social scheduling and performance tracking.
  
• Advertising → Meta, Google, and TikTok Ads Manager are more than enough , if managed by skilled marketers or the right agency.
  

At the end of the day, small and medium fashion brands succeed not by having everything, but by being clear about what matters most, staying focused, and building smart, flexible systems that support growth.

Deep dive: the full interview questions

Enrico Fantaguzzi: As someone who works closely with fashion brands of all sizes, what do you think are the biggest challenges facing small fashion businesses today?

Aisha Khalid: One of the biggest issues I see is that many small brands operate in a reactive way. They tend to make decisions based on taste or trends, rather than following a clear, strategic plan. It’s hard to stay focused on long-term goals when you’re constantly in survival mode.

Small brands often operate in a reactive way (problem > solution) instead of focusing on their medium and long term goals.

A lot of founders also don’t have the experience or resources to build scalable business models. They often overlook the importance of systems, processes, and platforms that could really help them grow efficiently.

Another major challenge is the pressure to generate quick sales. That pressure can make it difficult to invest in brand-building or long-term growth strategies. And let’s be honest, fear of failure can sometimes stop founders from taking the kind of risks that lead to real innovation.

There are also big knowledge gaps. Unlike established brands, smaller companies don’t always have access to insights, benchmarks, or best practices. Founders are juggling so many roles that there’s often little time left for deep market research or performance analytics.

Enrico: So it’s not just about making the product and selling it?

Aisha: Exactly. Many small brands underinvest in understanding customer lifetime value, retention strategies, or how to create an effective omnichannel experience. And let’s not forget the talent issue. Building a strong team is tough when you can’t offer big salaries or long-term career paths. You often end up working with creatives or freelancers who value freedom – which is great – but it can make it harder to build a stable company culture or leadership structure.

Enrico: And once they do start to grow, I imagine things get even more complex?

Aisha: Totally. Scaling a brand requires a different skillset. Suddenly you’re dealing with localization, personalization, marketing efficiency, margin optimization… all while trying to maintain your creative identity. Many founders spend too much time on things that look good but don’t actually move the business forward.

And of course, visibility is a massive challenge. The market is saturated, and it’s tough to stand out, especially without a big ad budget or in-house performance marketing expertise. Some brands rely too heavily on platforms like Instagram or TikTok without a strong brand foundation, and that can backfire.

Enrico: Given all these challenges, what do you think should be the top priorities for fashion start-ups? Should they focus on building a strong image, finding a niche, or creating an efficient structure?

Aisha: All of the above, but in the right order and with a clear goal in mind. First, define a non-negotiable objective. Something like, “We want to grow to $3 million in annual revenue within five years.” That goal becomes your north star. Every decision, whether it’s about product, marketing, hiring, or partnerships, should ladder up to it.

Then you build a focused roadmap with quarterly and annual milestones. From there, identify 3 – 5 key pillars that will drive your growth. For example:

• Brand Positioning & Identity: Know exactly who you are and why you exist.
  
• Product-Market Fit: Solve a real need for a specific audience—consistently.
  
• Customer Acquisition: Choose one or two channels and get really good at them before expanding.
  
• Operational Excellence: Build smart systems for inventory and fulfillment early on.
  
• Retention & Community: Use storytelling, CRM, and great customer experience to keep people coming back.

Enrico: And in terms of market positioning?

Aisha: Find and own your global niche. Don’t try to please everyone. Look for a cultural whitespace or a unique aesthetic or functional need that’s underserved—and build a community around it. Niche doesn’t mean small, it means focused and defensible.

You also need to create and maintain a strong brand identity. Product trends can be copied, but your brand DNA can’t. Your brand isn’t just your logo or tone of voice—it’s how you price, how you ship, how you photograph your items, how you hire… all of it.

And finally, set up an efficient, flexible structure. Use tech tools that scale with you, document processes early, and don’t rely too much on any one person.

Enrico: Great advice. One last question. You’ve worked in eCommerce for some of the biggest names in fashion and luxury. What software solutions do you think small and medium brands absolutely need to be competitive?

Aisha: Keep it simple. I always say—clarity of objective and strong execution beat fancy tech stacks. Too many tools can lead to confusion, fragmentation, and wasted budget. Choose tools based on your actual business goals, not what’s trendy.

Here’s what I’d recommend:

• E-commerce Platform: Shopify. It’s the best for fashion—scalable, app-rich, easy to use, and mobile-friendly.
  
• Analytics & Customer Insights: Google Analytics 4 for macro insights, and Hotjar for user behavior (heatmaps, session recordings).
  
• Email & SMS Marketing: Klaviyo is fantastic—deep segmentation, automation, and predictive analytics for churn and CLV.
  
• CRM: Honestly, Shopify + Klaviyo already gives you a solid customer data setup.
  
• Returns Management: Loop Returns works well with Shopify and helps retain revenue.
  
• Customer Support: Gorgias is purpose-built for eCommerce and integrates with all key channels—Shopify, Instagram, Facebook, email, and SMS.
  
• Content & Social: Dash Hudson is great for planning and tracking social content.
  
• Advertising: Stick with platform-native tools—Meta, Google, TikTok Ads Manager. Just make sure you’re working with an agency that understands fashion eCommerce and can deliver strong ROAS without blowing up your CAC.

Measuring success goes far beyond financial metrics: while topline growth, cost efficiency, and ROI remain central, true value also lies in strategic and intangible benefits, customer experience, organisational agility, and long-term competitiveness. In short, omnichannel is both a growth engine and a cultural shift, enabling brands not just to survive but to lead.

Gilles has spent the past 16 years working around the world (US, Asia and Europe) for Fashion companies such as Philipp Plein and Michael Kors in different roles around Finance & Operations.

He is currently MD of SpectR Consulting, working on consulting projects covering topics around Strategy, Finance and Operations

Omnichannel retailing is not a luxury but a requirement for competitiveness. It delivers both financial returns and intangible benefits, such as enhanced customer experience and loyalty, creating long-term value.

What are the main strategic and operational benefits of omnichannel for modern companies?

Omnichannel retailing offers a range of crucial strategic and operational advantages for modern businesses, turning it from an option into a competitive necessity.

Strategic Advantages

• Improved Customer Engagement and Loyalty: Companies with an omnichannel strategy report a retention rate of 89% compared to 33% for those relying on a single channel. This is a key indicator of the impact omnichannel strategies have on enhancing customer experience.
• Revenue Growth:
  • Companies that implement omnichannel strategies see topline growth of 9.5% per year, versus 3.4% for others.
  • More opportunities for cross-selling and up-selling increase the value associated with each customer.
  • Omnichannel customers, while only representing 7% of the total, generate 27% of overall sales.
  • Expanding the scope of business across multiple sales channels (such as Buy Online, Pick-up In Store – BOPIS, or mobile ordering) helps drive conversion rates. During the pandemic (2019–2021), the conversion rate for BOPIS rose from 2.3% to 3.3%.
  • Brands using three or more channels report a 494% increase in order rates and a 250% increase in engagement compared to single-channel players.
• Meeting Consumer Expectations: Consumers already live in an omnichannel world, and businesses must keep up to avoid falling behind. 60% of shoppers expect to use services like BOPIS, whose sales have grown by 208%.
• Organizational Agility and Cultural Transformation: Omnichannel is a catalyst for cultural change, requiring marketing, IT, and operations to work together and share objectives. This creates intangible but essential benefits, such as improved organizational agility.

Operational Advantages

• Cost Efficiency:
  • Omnichannel integration reduces stockouts, optimizes the supply chain, and lowers customer acquisition costs, as each interaction becomes more effective.
  • Better inventory management is critical; the most profitable brands have superior stock control. Brands with an EBITDA margin above 40% typically maintain lower inventory levels.
  • 27% of online customers would leave a site if a product was out of stock, moving to a competitor. Stock management is therefore a key priority.
• Operational Efficiency:
  • Streamlined processes and faster customer service.
  • Integration of online and offline channels eliminates duplication and waste.
  • Brands gain the opportunity to rethink processes and internal organization to reduce redundancies and improve workflows.
• Better Product Availability Management: This includes inventory optimization and the ability to offer personalized services to each customer.
• Change Management and Incentives: For a successful omnichannel strategy, managing organizational change is crucial, as is defining a new sales incentive plan—an often-overlooked factor.

How does omnichannel transform internal and customer relationships?

Omnichannel retailing introduces profound transformations both in internal company relations and in the way a business interacts with its customers.

Transformation of Internal Relations

Omnichannel acts as a catalyst for cultural change within the organization. It requires unprecedented integration and collaboration across departments:

• Cross-Functional Collaboration: It forces marketing, IT, and operations to work together and share common goals. Operating in silos is no longer sufficient.
• Review of Organizational Processes: Each brand has the opportunity to reassess its processes and internal organization to reduce redundancies and improve workflows. This leads to greater organizational agility.
• Change Management: Implementing an effective omnichannel strategy requires strong change management involving all departments. This aspect is often underestimated.
• New Incentive Systems: Defining a new sales incentive plan is crucial. It is an essential component of a properly functioning omnichannel strategy, yet often overlooked.
• Sharing of Insights: Departments must share their knowledge about customer behavior and preferences (customer insights and trends). Merchandising should also be involved, as this information can influence collection development and pricing decisions.
• Strategic Alignment: The goal is to align marketing strategies across all channels and markets to maximize customer engagement and campaign effectiveness.

These internal benefits, such as organizational agility, are considered intangible advantages which, while difficult to measure, make the difference between a company that merely exists in the market and one that leads it.

Transformation of Customer Relations

Omnichannel is essential to meeting consumer expectations, as customers already “live in an omnichannel world.” The transformation of customer relations is expressed through:

• Improved Engagement and Retention: Companies with an omnichannel strategy report a retention rate of 89% compared to 33% for those relying on a single channel. Brands using three or more channels see a 250% increase in engagement.
• Enhanced Customer Experience: Omnichannel is not just about multiplying touchpoints but about ensuring continuity and consistency in the customer journey. This includes seamless integration, better product availability management (through inventory control), and the ability to deliver personalized services throughout the customer’s relationship with the brand.
• Increased Customer Value: With stronger retention and more cross-selling and up-selling opportunities, the value of each customer grows. Leveraging cross-selling and up-selling also enhances engagement, enabling the development and promotion of additional initiatives.
• Adaptation to New Shopping Modes: Consumers expect to use options such as Buy Online, Pick-up In Store (BOPIS), whose sales have grown by 208%. In fact, 60% of shoppers expect this option to be available. Mobile e-commerce is also expanding rapidly, reflecting customer expectations of flexible shopping experiences.
• Higher Conversion Rates: Expanding across multiple channels drives higher conversion rates. For example, the conversion rate for BOPIS increased from 2.3% to 3.3% during the pandemic.
• Importance of Stock Management: Product availability is critical, as 27% of online customers would abandon a site and switch to another if an item were out of stock. Effective inventory management and better product allocation contribute to a positive customer experience.

How can you effectively measure the return on investment of an omnichannel strategy?

Measuring the return on investment (ROI) of an omnichannel strategy effectively goes beyond simple financial analysis. It must include strategic and operational metrics, while also recognizing the importance of intangible benefits.

Here is how the ROI of an omnichannel strategy can be measured, based on key points:

1. Direct Financial Metrics

These are fundamental and often the CFO’s main focus:

• Revenue Growth:
  • Topline Growth: Companies with an omnichannel strategy record annual topline growth of 9.5%, compared to 3.4% for others.
  • Omnichannel Sales: Measure the percentage of sales generated through omnichannel activities (e.g., 13% of physical sales and 20% of online sales, according to Mins).
  • Contribution of Omnichannel Customers: Omnichannel customers, while only 7% of the total, generate 27% of overall sales.
  • Conversion Rate: Expanding business scope across multiple channels (such as Buy Online Pick-up In Store – BOPIS – or mobile ordering) is aimed at improving conversion rates. For example, during the pandemic the BOPIS conversion rate rose from 2.3% to 3.3%.
  • Cross-Selling and Up-Selling: Quantify the increase in cross-selling and up-selling opportunities that boost customer lifetime value.
  • Order Rate Growth: Brands using three or more channels record a +494% increase in order rates.
• Cost Efficiency:
  • Reduction of Stockouts and Supply Chain Optimization: Measure the impact of reducing lost sales due to stockouts and improving supply chain efficiency. Better inventory management is correlated with higher profitability (brands with EBITDA margins above 40% typically have lower inventory levels). Since 27% of online shoppers abandon a site when an item is out of stock, inventory management is critical.
  • Lower Customer Acquisition Costs (CAC): More effective interactions enabled by omnichannel strategies can reduce the cost of acquiring new customers.
• Net Profit Margins: A fundamental metric for CFOs, who focus not only on topline growth but also on gross margin to identify potential issues (e.g., excessive discounting that erodes profitability).
• Return on Investment (ROI): Ensure that the benefits outweigh the investments made.

2. Strategic and Operational Metrics

These focus on the impact on customers and organizational performance:

• Customer Retention: Companies with an omnichannel strategy achieve an 89% retention rate compared to 33% for single-channel businesses. Measuring this rate is a key indicator.
• Customer Engagement: Brands using three or more channels see a 250% increase in engagement compared to single-channel players. Cross-selling and up-selling opportunities also strengthen engagement.
• Adoption of New Shopping Methods: Track the use of services such as BOPIS, whose sales grew 208%, with 60% of shoppers expecting to use it. Growth in mobile e-commerce (from 4.4% to a projected 10.4% of total sales) is another key indicator.
• Operational Efficiency: Assess process streamlining, faster customer service, and the elimination of duplication and waste thanks to online/offline integration. This may include warehouse optimization and better product allocation.
• Customer Experience Quality: While difficult to measure directly, improvements are reflected in consistent integration, better product availability management, and the ability to deliver personalized services throughout the customer journey.

3. Intangible and Organizational Benefits

ROI is not just about numbers—intangible benefits are crucial:

• Customer Loyalty and Experience: Hard to quantify, but they make the difference between a company that is present in the market and one that leads it. They contribute to long-term value creation.
• Organizational Agility: Omnichannel acts as a catalyst for cultural change, pushing marketing, IT, and operations to collaborate and share goals. This creates greater agility—an essential intangible benefit.
• Reduced Redundancies and Improved Workflows: Each brand has the opportunity to review processes and internal organization to enhance efficiency.

Key Considerations for Measurement

• Change Management: Often underestimated, but fundamental to the success of any omnichannel project, requiring the involvement of all departments.
• New Sales Incentive Plans: Defining an adequate incentive scheme is essential to an effective omnichannel strategy, though often neglected.
• Sharing of Insights: Departments must share customer behavior and preference insights (consumer insights and trends), with merchandising also involved in decisions around collections and pricing.
• Tailored Adaptation: There is no universal “magic recipe.” Each omnichannel project is unique and depends on the company’s strategy, history, and level of technological and organizational maturity.

Conclusion

Omnichannel retailing is not a luxury but a requirement for competitiveness. It delivers both financial returns and intangible benefits, such as enhanced customer experience and loyalty, creating long-term value.

Ultimately, omnichannel retailing enables businesses to build stronger, longer-lasting relationships with customers, ensuring greater satisfaction and loyalty. At the same time, it streamlines internal dynamics, transforming the company into a more agile and cohesive organization.

Measuring the ROI of an omnichannel strategy requires a holistic approach that combines concrete financial metrics with analysis of strategic, operational, and intangible indicators. It must be recognized as a transformational journey that generates long-term value.

Key takeaways from the Lesson by Oliwia Urban, Senior SEO Specialist at GA Agency.

7+ years of experience in international SEO strategy, on-page optimization, and content development. Known for delivering actionable, measurable results for fashion and lifestyle brands across markets such as the UK, US, Poland, and the Middle East. Leads a team of SEO professionals with a people-first, strategy-driven approach.

Evolving SEO with Google Algorithm Updates

Google’s algorithms have come a long way—from early PageRank and the 2003 Florida update aimed at reducing spam, through Panda, Penguin, Hummingbird, and RankBrain, to the recent AI-powered Helpful Content Update and SpamBrain. The focus has consistently shifted toward rewarding quality, relevance, and trust. In 2025, Google’s core updates and ongoing refinements emphasize high-quality, user-centric content paired with deeper AI understanding of user intent.

Adapting to the Age of “MSEO” and Zero-Click Trends
Today’s SEO isn’t just about Google—it’s about reaching audiences across multiple platforms (“MSEO”): Google, Bing, LinkedIn, AI-powered engines (e.g., ChatGPT, Perplexity), and more. Search Engine Results Pages (SERPs) have evolved to include AI overviews, rich snippets, shopping panels, “People Also Ask,” video and image carousels—often resulting in zero-click scenarios. To thrive, we optimize for these features: using schema markup, concise Q&A content, FAQs, bullet-point formatting, and localized SEO. This allows us to “answer in place” and capture valuable visibility directly in the SERP.

Here you are some of the key points about SERP evolution and AI impact:

Google’s Search Engine Results Pages (SERPs) are undergoing a significant transformation. Gone are the days of a simple layout with sponsored ads at the top and classic “blue links” below; today’s SERPs are rich with AI-driven features like AI Overviews, featured snippets, People Also Ask panels, image and video carousels, and shopping grids. These elements occupy more screen space and answer user queries directly—often without the user clicking through to a website. The goal of these changes is to enhance user experience: faster, easier answers tailored to intent, seasonality, and personal search history 

This shift has profound implications for SEO. With zero-click searches—where users don’t leave the SERP—increasing dramatically (up to 80% when AI Overviews are present), traditional click-through metrics are declining. To adapt, brands must optimize content for SERP features: structuring Q&A and FAQ sections, implementing schema markup, writing concise answers, and targeting keywords that trigger AI-driven elements. Visibility in AI Overviews and featured snippets—not just rankings—matters more than ever, as they build brand authority and influence even without clicks.

Google Shopping is evolving beyond bids to value-based ranking. 

With AI-infused shopping results, Google now evaluates product relevance and feed quality—alongside traditional bidding—to determine visibility. Well-structured, information-rich product feeds (complete with attributes like size, material, GTIN, pricing, and availability) are increasingly decisive. As a result, even without high bids, merchants with optimized feeds can outperform competitors simply by offering deeper, more accurate product data.

In-house vs. agency-managed shopping feed optimization? Partnering with an agency like ours offers immediate access to specialists who understand the latest tools, AI-driven feed generators, schema/structured-data implementation, and performance monitoring best practices. While in-house efforts require hiring and training multiple experts, agencies streamline processes and provide consistent optimization. For clients with extensive catalogues, this approach reduces workload—no need to juggle Google Merchant Center setup, AI-assisted structured data tools, or frequent feed audits—and avoids relying solely on ad spend to capture traffic and conversions.

Google Shopping is now driven by AI-powered ranking that values relevance and feed quality—not just bids—so merchants with well-structured, comprehensive product feeds (complete with accurate titles, images, pricing, stock, and review data) can outperform competitors regardless of budget. Partnering with an agency ensures your feeds are continuously optimized: specialists handle feed audits, structured-data implementation, attribution of reviews, and AI-driven feed improvements, while freeing you from managing Merchant Center complexities. This approach minimizes manual workload and maximizes performance—making ad spend more effective and improving visibility across Google Shopping and AI-driven shopping surfaces.

Link building for SEO

Link building remains a crucial aspect of SEO, but the emphasis has shifted firmly from quantity to quality. Search engines now prioritize backlinks from authoritative, relevant, and trustworthy sources, which means fashion brands should focus on building genuine relationships and earning links through valuable, niche-specific content. Effective strategies include personalized outreach tailored to a recipient’s audience, using AI to identify relevant linking opportunities at scale, and securing mentions through expert contributions or PR efforts. A strong, trusted backlink profile ultimately enhances domain authority and supports long-term SEO visibility and growth.

To summarize, SEO in 2025 requires a multidisciplinary approach: strong technical foundations, rich semantic content, and optimization for the AI-driven world. It’s no longer just about ranking—it’s about being the trusted source that AI systems cite and serving user intent in real time. 

The key takeaways:

🚀 1. AI-Driven Optimization based on AI-SEO, AEO & GEO:

– AEO (Answer Engine Optimization) focuses on structuring content—Q&A, structured data, concise conversational tone—to appear in AI responses like Google’s SGE, ChatGPT, or Perplexity
– GEO (Generative Engine Optimization) ensures your content gets cited or integrated in generative AI outputs, using metadata, llms.txt, and topical authority
A combined hybrid strategy—SEO + AEO + GEO—is essential to maintain visibility across both traditional search and AI‐powered platforms

🧠 2. AI-Enhanced Content Tools & Human Oversight

Tools like Surfer SEO, Clearscope, MarketMuse, and Alli AI enhance relevance and semantics—but human creativity must polish them to avoid generic, machine-like output
Efficiency is key: AI helps with metadata, ideation, summarization, and coding, but content needs authentic voices to stand out.

🎯 3. E-E-A-T & Originality
Google’s Experience-Expertise-Authority-Trustworthiness guidelines remain crucial. Featuring real authors, bios, and original research or data improves credibility
An “OriginalContentScore” rewards unique, experience-based insights over recycled content

⚡ 4. Core Web Vitals & UX
Technical metrics—LCP, FID, CLS—are now fundamentals for both SEO and AI indexing. Fast, stable pages enhance user engagement and bots’ crawling efficiency

🎙️ 5. Voice & Conversational Search
As voice assistants grow, use natural speech patterns and long-tail conversational keywords. Structuring content in FAQ or Q&A formats can capture voice search results

📹 6. Visual & Video SEO
Images and videos are critical: include rich metadata, alt-text, transcripts, and schema markup to surface in image/video carousels and AI answers

💬 7. Semantic Search & User Intent
SEO is shifting from keyword focus to intent: build topic clusters that cover related queries and contextually align with user needs

🌍 8. Zero-Click Answers & SERP Real Estate
With AI providing direct answers, optimize for featured snippets, People Also Ask, and knowledge panels. Even without clicks, you gain visibility

📍 9. Local & Mobile-First Optimization
Local businesses should leverage Google Business Profiles, hyper-local content, and voice search. Mobile-first design is essential as Google prioritizes mobile indexing

🛠️ 10. Emerging Tools & Metrics
New platforms (AI EngineBoost, Alli AI, RankIQ) support hybrid SEO, AEO, and GEO strategies
SEO metrics are evolving: monitor AI‐driven visibility (appearances in AI responses) not just rankings and CTR.

✅ 2025 SEO Checklist: discover the 5 key priorities:
1. Hybrid Optimization Combine SEO, AEO, GEO strategies
2. UX & Performance Core Web Vitals, mobile-first design
3. Authority Boost E-E-A-T with real authorship & data
4. AI Formatting FAQs, structured data, conversational tone
5. Visibility Metrics Track AI mentions and zero-click placements

About GA – Your Truly Omnichannel Digital Agency
GA is an omnichannel digital agency specializing in international markets. With local experts across 25+ countries speaking 18 languages, we ensure a truly local approach to SEO and paid media. This means strategies are tailored to each client’s specific market—aligned with local audience behaviours and cultural nuances—giving us a unique edge in delivering relevant, impactful campaigns.
At GA London headquarters, a team of 60+ specialists offer two core pillars of service: SEO and Paid Media. But their capabilities extend further, covering strategy planning, tools management, analytics, content writing, digital PR, CMS management, and comprehensive audits. We collaborate closely with clients to define and agree on tailored solutions upfront—solutions that drive measurable results and align with their business goals.

Video commerce is emerging as a powerful tool reshaping the way fashion brands connect with customers and sell products online.

So what is video commerce?
Video commerce refers to selling products directly through video content—either live or pre-recorded—where viewers can click and shop in real-time, without leaving the video. Think of it as QVC meets TikTok, but fully shoppable and digital-first. This trend is already booming in Asia and is steadily gaining traction in Europe and the U.S.

Why is it important now?
Attention is the new currency, and consumers, Gen Z and Millennials in particular, are spending more time watching short videos than browsing traditional eCommerce catalogs. Platforms like TikTok, Instagram Reels, and YouTube Shorts are not just for entertainment anymore, they are becoming shopping environments, and fashion brands and retailers should be aware of this. Video creates emotional engagement, shows products in action, and builds trust with creators and brand ambassadors.

As Eitan Koter points out, creators are becoming the new commerce engines. They bring authenticity, community, and influence—qualities that static product pages simply can’t match.

“Video commerce is not just the next step in retail and e-commerce evolution, it’s a fundamental shift in how we connect, communicate, and convert attention into action. It empowers brands and creators to merge storytelling with commerce, creating seamless journeys where content becomes the storefront”.

Eitan Koter, Co-CEO at Vimmi

How should fashion brands and retailers approach video commerce?

1. Start small but consistent: Don’t wait to launch a perfect livestream shopping strategy. Begin with shoppable Instagram Reels, TikToks, or styling videos integrated into your PDPs (Product Detail Pages).
2. Collaborate with creators: Influencers and micro-creators can present your products in relatable, real-life contexts.
3. Leverage platforms: Use tools like Bambuser, Livescale, or directly integrate TikTok Shop to make video instantly shoppable.
4. Educate and entertain: It’s not just about “buy now”—use video to tell the brand story, explain materials, and show versatility.

What’s the difference between eCommerce, social commerce, and video commerce?

• eCommerce is the digital storefront—your Shopify or Magento site.
• Social commerce is selling through social platforms like Instagram Shop or TikTok Shop, where discovery and purchase happen within the app.
• Video commerce is a subset of both—using video content to directly drive sales, whether it’s embedded on your site or hosted on social platforms.

The fashion world is flooded with content and products, video commerce cuts through the noise. It’s a format designed for attention, built for engagement, and optimized for conversion.

At Digital Fashion Academy, we believe in continuous professional development that goes hand in hand with digital transformation, and as part of this transformation we recommend to start looking at ways to integrate video commerce your marketing and ecommerce strategies, as this could become as a core pillar of your omnichannel strategy.

The Video Commerce at QVC

QVC, the original home shopping giant, is undergoing a bold transformation.

With a massive decline in traditional TV viewership, 44% down since 2018, the company is now livestreaming on TikTok 24/7, becoming the first constant stream of shoppable content.

This pivot is part of a broader strategy to reinvent itself as a “live social shopping company,” targeting $1.5 billion in sales through social platforms within three years.

For legacy brands like QVC, embracing platforms like TikTok is a survival tactic, and a strategic shift that validates the massive potential of live social commerce.

Glossary of Video Commerce

📘 Glossary: Key Terms in Video Commerce

1. Video Commerce
The use of video content—live or pre-recorded—to showcase and sell products online. It allows viewers to watch, interact, and purchase directly from the video interface.

2. Shoppable Video
A video that includes clickable links or interactive elements allowing viewers to purchase featured products without leaving the video.

3. Livestream Shopping / Live Shopping
A live broadcast (often on social media or eCommerce platforms) where hosts or influencers present products, answer questions, and sell in real-time. Popular in China and gaining ground globally.

4. Short-form Video
Bite-sized video content, usually under 60 seconds, designed for platforms like TikTok, Instagram Reels, or YouTube Shorts. Often used to showcase products in a dynamic and entertaining format.

5. Product Tagging
The practice of linking specific products to moments in a video, allowing viewers to click and view product details or make a purchase instantly.

6. Creator Commerce
A model where content creators (influencers, stylists, brand ambassadors) promote and sell products directly through their video content and social media platforms.

7. Social Commerce
Selling products directly through social media platforms like Instagram Shop, Facebook Marketplace, TikTok Shop, or Pinterest. Often includes video, but not exclusively.

8. eCommerce
Traditional online commerce via brand-owned websites or marketplaces (e.g. Shopify, Magento, Amazon), where users browse digital catalogs and complete purchases.

9. PDP (Product Detail Page)
A product-specific page on an eCommerce website that includes images, pricing, size options, and now increasingly includes video content to boost engagement and conversion.

10. Conversion Rate
A key performance metric in eCommerce that measures the percentage of viewers or visitors who take a desired action—usually completing a purchase.

11. Engagement Rate
A measure of how users interact with a video (likes, comments, shares, click-throughs), often used to gauge the effectiveness of video content in video commerce.

12. Video CMS (Content Management System)
A platform or tool used to manage, host, and distribute video content across websites and social media. Some platforms also include analytics and shoppable integrations.

13. Omnichannel Strategy
A unified customer experience across multiple platforms: web, mobile, social, in-store. Video commerce supports omnichannel by merging storytelling, content, and transactions.

14. Interactive Video
Video content that includes user-triggered actions (clicks, hovers, swipes), such as choosing product colors, adding to cart, or jumping to different video sections.

15. Platform Integration
The technical connection between your video content and eCommerce system, enabling real-time product data, pricing updates, inventory sync, and purchase flow.

Andrea Dell’Olio
Head of Marketplaces Boggi Milano

Enrico Fantaguzzi
Co-founder Digital Fashion Academy

Fashion eCommerce is continuously evolving, and events like Shoptalk Europe give us a front-row seat to what’s coming next. We caught up with Andrea Dell’Olio to unpack the biggest takeaways – from AI and brand control to what’s actually driving digital performance right now.

Fresh from attending Shoptalk in Barcelona, Andrea Dell’Olio, Head of marketplaces at Boggi Milano and experienced fashion professional, shares his reflections on the evolving landscape of fashion eCommerce after attending the ShopTalk event in Barcelona. 

In our conversation, we covered the most current topics in fashion digital business from artificial intelligence to the critical role of brand control and logistics performance. Here are the key insights from our discussion.

Shop Talk Barcelona: A Curated, Insightful Experience

Andrea described the Shop Talk Barcelona as “molto ben organizzato, ben curato” (well-organised and thoughtfully curated). Unlike broader industry events, this one was focused, manageable, and filled with high-calibre companies and quality sponsors. A standout feature was the one-to-one meeting format, likened to a “business speed dating”, which helped forge highly relevant connections.

The ancillary events, including a closing party hosted by the Ministry of Sound at Citadelle De Monjuïc, elevated the experience and contributed to valuable networking. However, connecting with major retailers like MyTheresa, Harrods, or Mr Porter proved more challenging, signaling a potential area for improvement.

AI-Powered Product Data: Efficiency and Scalability

One of the most pressing themes from the event – and our conversation – is the strategic use of Artificial Intelligence to enrich product data. Andrea notes growing interest in tools that generate attributes and content directly from product images, helping brands meet marketplace demands without intensive manual effort.

This is particularly crucial for working with platforms like Zalando, whose Z Direct system shows a direct link between enriched product data and performance metrics such as Add to Basket and Return Rate. As this guide on engagement rate and product discovery explains, optimizing how products are surfaced and interacted with is central to driving conversion on marketplaces. AI’s role in automating structured data, enriching content, and improving SEO visibility cannot be overstated.

From Product Images to Performance: How AI Drives Marketplace Success

Tools and partners like Dressipi, IEN, and emerging integrations with DAM/PIM systems (like Salesforce Commerce Cloud) are redefining product information pipelines. 

💬 “A brand must adapt to the environment… without losing its true nature.” – Andrea Dell’Olio

Brand Control is Non-Negotiable

With an increasingly conscious consumer base, especially Gen Z, brand control has become a competitive differentiator. As Andrea puts it, brands must maintain control over pricing, stock, and image to avoid diluting their identity.

“In a constantly changing world, a brand must adapt to the environment, which includes macroeconomic contingencies of a certain type – duties, adverse markets conditions and so on. However, it’s important to maintain relevance and a consistent brand identity, adapting to market conditions without losing your true nature.”

Boggi Milano was cited as a strong example, evolving from a heritage formalwear brand into a full-fledged lifestyle label, now thriving on platforms like Farfetch. But success comes with strategic discipline: avoiding discounting wars, carefully selecting channels, and protecting long-term brand equity, even if that means saying no to Amazon-level reach. As outlined in this overview of luxury fashion eCommerce KPIs, tracking the right performance metrics – while maintaining exclusivity and brand perception, is key to succeeding in the premium space.

Logistics and Last-Mile Excellence

Operational excellence extends beyond product content and brand equity. Andrea emphasised the importance of logistical agility, citing conversations with Zeos (Zalando’s logistics division) about leveraging hybrid business and fulfillment models. Brands are increasingly mixing internal and external logistics to optimise cost-performance ratios and scale efficiently.

In urban markets like Milan, Paris, and London, Same-Day Delivery is fast becoming a benchmark. Consumers now expect Amazon-like speed and service across all premium segments, pushing brands to innovate or risk being left behind.

A Final Note on Barcelona

Having not visited Barcelona in over 15 years, Andrea was struck by the city’s transformation: cleaner, more organised, and deeply international. A fitting backdrop to an event that reflects the spirit of evolution and reinvention permeating the fashion eCommerce world today.

Key Takeaways

• AI is revolutionizing product data creation and SEO performance.
• Brand control across pricing, image, and channel strategy is vital for long-term growth.
• Same-Day Delivery and hybrid logistics are shaping consumer expectations in urban markets.
• Events like Shoptalk are valuable for insight, but execution remains the differentiator.

Conclusion

From AI-driven product data to safeguarding brand integrity and mastering last-mile logistics, fashion brands are navigating a complex digital terrain. Events like Shop Talk offer critical insights and connections, but as Andrea Dell’Olio reminds us, the real challenge lies in how we execute these learnings. The brands that balance innovation with strategic control will shape the future of fashion commerce.

By Enrico Fantaguzzi, Editor-in-Chief, Digital Fashion Academy

May 25th 2025, updated

At Google’s annual I/O conference for developers, Google announced several new advances, including a more personalised multimodal AI search experience for shopping queries, agentic checkout capabilities and an enhancement to its virtual try-on tool that will allow users to see products on their own body.  

What does “agentic” checkout mean?

Agentic checkout, it’s an ecommerce check out that behaves autonomously. I.e. the check out acts like an agent that completes a series of actions without you being involved. For example the agentic checkout could ask you, “Do you want to buy this product?” and, if you say yes, it might be able to complete the purchase on it’s own.

How is the agentic checkout able to complete a purchase on your behalf?

The agentic check out can complete the purchase on our behalf if it has all the necessary information to complete the checkout. First of all it needs the payment method saved – Google Pay wallet – and then it may need confirmation of your shipping address.

Google’s AI virtual try-on (VTO)

Virtual try ons are not new to the digital fashion industry, I personally used virtual try ones and virtual fitting solutions in some of the companies I worked for (Twinset, 7 For All Mankind) with excellent results in terms of conversion rate but recently the improvements in AI have made possible to achieve more efficiency (savings) to implement VTO for fashion products.

At I/O 2025, Google unveiled a significant upgrade to its AI Mode shopping experience: a powerful virtual try-on feature that allows users to upload their own photos and visualise garments on their bodies. Powered by advanced generative AI, the system simulates fabric fit and texture across various body types, promising a new level of personalization in online shopping.

This development has the potential to be a game-changer for fashion e-commerce. But beyond the consumer-facing benefits, what does this mean for fashion brands, especially those navigating the complexities of digital transformation?

Organizational Impact

Fashion brands will need to rethink how they organize their product content. To fully take advantage of AI-powered platforms like Google’s, brands must invest in rich, structured product data, including detailed images, accurate sizing information, and standardized metadata. Product photography will likely need to evolve to include multi-angle, high-resolution, and fabric-dynamic visuals that AI models can effectively process.

Furthermore, cross-functional teams, marketing, merchandising, IT, and customer experience, will need to collaborate more closely to align content creation, technology integration, and user experience. This may drive brands to create or expand dedicated digital innovation teams.

Business Strategy Implications

From a business perspective, these AI tools could significantly impact conversion rates, return rates, and customer satisfaction. By reducing the uncertainty associated with fit and appearance, virtual try-on tools may decrease returns, one of the biggest operational costs in online fashion retail.

Additionally, AI-powered personalization could improve customer loyalty by offering a more tailored experience. Brands that successfully integrate these tools may also gain a competitive edge in SEO and product discoverability, especially if they are early adopters and featured in Google Shopping results.

However, brands must also consider data privacy, AI ethics, and moderation challenges. Reports have already highlighted potential misuses of generative AI in retail contexts, including the generation of hypersexualized imagery. This underlines the need for responsible implementation, clear user safeguards, and rigorous testing before adopting such features at scale.

The Road Ahead

As AI redefines how consumers interact with products online, fashion companies must evolve, not just in terms of tech adoption, but in mindset and internal workflows. This is not just a marketing opportunity, but a strategic inflection point: the brands that adapt their structures, teams, and processes for a digitally immersive future will be the ones that thrive.

Supporting and integrating with third party applications such as Google AI or ChatGPT is just a first step in a digital transformation process that need to create value for the customer

Enrico Fantaguzzi

However, supporting and integrating third party applications such as Google AI or ChatGPT is just a first step in a digital transformation process that need to create value for the customer. Google’s “Shopping Graph now has more than 50 billion product listings, from global retailers to local mom and pop shops, each with details like reviews, prices, color options and availability”, so that customers have more options to select from, however people don’t just buy a new product everytime they go on a trip or to a party, therefore customers should be allowed to integrate the AI features within their own wardrobe. This would allow people to integrate their current selection of garments with new products that their missing. This step is critical for user experience but also to create a sustainable digital fashion industry,

At Digital Fashion Academy, we believe that understanding and leveraging these technologies is no longer optional, it’s essential. We’ll continue to monitor these developments and support fashion professionals with the knowledge and skills needed to lead in the age of AI.

Sources

• Google Blog: AI Mode and Virtual Try-On Update
  
• The Atlantic: Google’s Shopping Tool and AI Image Ethics
  
• Google I/O 2025 Recap (for context on product announcements)

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Deep dive into fashion AI: join our live webinar

Here, too, the goal is to identify a north-star metric that can serve as a guiding benchmark for all initiatives aimed at optimizing this phase. As in previous discussions, it is essential to take a holistic perspective, recognizing that the e-commerce platform is just one component of a broader brand ecosystem.

The objective is not to maximize the online channel in isolation but to configure it in a way that enhances the performance of the entire ecosystem. At times, this may mean that certain elements appear to underperform — when in reality, they contribute more significantly to long-term brand success by unlocking greater systemic value. With this perspective, identifying the right KPIs becomes crucial, ensuring that all experiments and optimizations align with the broader brand strategy.

At the lower funnel stage, customers finalize their purchase, completing the transaction for products they previously explored. When it comes to placing an order, they have multiple channel options:

• Physical Stores — Traditional brick-and-mortar locations where customers can buy in person.
• Third-Party Partner Platforms — External websites or apps, such as marketplaces and concessions, that facilitate transactions.
• Customer Support — Purchases made via phone, often using a secure pay-by-link method.
• Brand Website — The brand’s primary e-commerce channel, where customers browse and buy directly.
• Brand Mobile App — A dedicated transactional app, if available, that provides a seamless shopping experience.

The first key difference between the discovery and purchase stages lies in how customers interact with channels. During product discovery, they often engage with multiple channels, taking advantage of each one’s unique benefits. However, when it comes to making a purchase, they typically commit to a single channel and complete the transaction within that environment.

This analysis specifically focuses on website performance, as it remains the primary driver of e-commerce activity. For simplicity, the term “online” will refer exclusively to the brand’s website throughout this discussion.

THE PARADOX OF A PERFECT EXPERIENCE

For most e-commerce businesses, the purchase stage is the ultimate goal — both a key revenue driver and a crucial touchpoint for customer satisfaction. A seamless, intuitive checkout experience not only boosts conversions but also fosters long-term brand loyalty.

However, for luxury brands, the role of e-commerce is fundamentally different. Their customer journey is designed to be store-centric, prioritizing high-touch service and immersive in-person experiences. As a result, defining the right north-star KPI requires careful alignment with the brand’s overarching strategy.

Traditionally, e-commerce success is measured by Conversion Rate (the percentage of website visitors who complete a purchase) and Digital Revenue (total online sales within a given timeframe). While these metrics work well for mainstream online retailers, they can be misleading for luxury brands.

Consider this scenario:

A luxury collection is so captivating that it inspires immediate desire. The website seamlessly provides all necessary details, compelling every shopper within a specific timeframe to visit a physical store to complete their purchase. Once in-store, expert advisors enhance the experience — curating additional selections, deepening brand engagement, and ultimately increasing customer spend.

Paradoxically, in this scenario, the website’s Conversion Rate would register as 0%, and Digital Revenue would appear as zero — not due to failure, but because every shopper opted for the in-store path within that period, driving significant business impact. Does this mean the e-commerce platform fell short? Absolutely not. It achieved its ultimate goal: engaging customers, facilitating discovery, and driving store visits, where the brand’s value is truly maximized.

This reveals a fundamental flaw in how luxury e-commerce performance is measured.

While a frictionless online checkout remains important — some customers lack store access, and certain products are well-suited for digital sales — it should be viewed as a secondary function, not the primary goal. For luxury brands, the true success of an e-commerce platform lies in its ability to drive in-store engagement.

North-star metrics should reflect the brand’s strategic priorities — not be based on a fallback option. To accurately assess luxury e-commerce performance, brands must look beyond traditional metrics like Conversion Rate and Digital Revenue and adopt KPIs that better align with their unique customer journey.

Traditional e-commerce metrics assume that brand websites function like Amazon — where every visitor is expected to complete a transaction online. This perspective fails to account for the distinct objectives of luxury fashion’s upper and lower funnels.

Here’s the flaw in that logic: if a customer visits a luxury brand’s website, finds exactly what they need, and is successfully guided to a physical store to complete their purchase, traditional metrics would still count this as a failed conversion. This artificially lowers the Conversion Rate and shows no contribution to Digital Revenue, creating a misleading assessment. In reality, for many luxury brands, driving in-store visits can be far more valuable than an online sale.

Beyond the multi-channel nature of the upper funnel and the single-channel flow of the lower funnel, another key distinction lies in online behavior. Product discovery is inherently nonlinear — customers move fluidly between product listing pages (PLPs), product detail pages (PDPs), and search results (SERPs), continuously refining their choices. This back-and-forth journey is shaped by inspiration, research, and evolving preferences. In contrast, checkout is a structured, goal-oriented process designed for efficiency and transaction completion. It typically follows these key steps:

• Customer Identification — Also known as the Checkout Login screen, this step can be bypassed via guest checkout but remains crucial for loyalty programs and marketing.
• Shipping Selection — Customers choose delivery methods and preferred locations.
• Packaging Options — A consideration for sustainability-conscious buyers and gift-givers.
• Payment — A range of payment methods accommodate different customer preferences.

Some of these steps can be streamlined with express checkout or pre-saved preferences, further reducing friction. However, while product discovery is an exploratory process, checkout follows a linear path toward transaction completion — a fundamental difference that should be reflected in north-star metrics.

Since product discovery is complex and non-linear, measuring its effectiveness requires a combined metric, such as engagement rate. On the other hand, the structured nature of the checkout funnel makes it better suited for traditional ratio-based metrics.

However, the standard Conversion Rate falls short in this context. While the numerator (completed transactions) is clear, determining the right denominator requires deeper analysis. What constitutes a meaningful conversion opportunity for a luxury brand? Instead of blindly applying traditional e-commerce KPIs, brands must examine user behavior patterns to develop more accurate measures of funnel efficiency — ones that reflect the true impact of their digital experience.

When analyzing users transitioning from product discovery to a purchase decision, we can identify three key categories:

1. Users who haven’t visited the website but have interacted with products through other digital channels or physical stores.
2. Users who browsed the website without adding items to the cart; still they might have shown measurable intent (e.g., clicking ‘Find in Store,’ contacting customer support) or not (taking screenshots, or saving product links).
3. Users who browsed the website and added one or more products to the cart, along with other engagement actions.

Users in all three categories may ultimately choose not to purchase, buy in-store, or complete their transaction through another channel instead of the website. However, only the third group is relevant to this analysis, as adding a product to the cart is a prerequisite for entering the website’s checkout process. This is why traditional e-commerce often considers the Add-to-Cart Rate the most reliable leading indicator of an impending transaction.

Given this, one might reasonably define the Add-to-Cart action as the entry point to the lower funnel and measure the effectiveness of this stage by the ratio of purchasers to users who added items to the cart. This approach provides a better proxy than the overall Conversion Rate, as it excludes visitors who merely browse the catalog without displaying intent to purchase via the website.

However, for many brands, the Add-to-Cart function often serves more as a wishlist than a direct purchase intent signal. The final transaction — whether online or in-store — is driven more by customer preference than by the efficiency of the purchase funnel. It’s common for customers to add products to their cart simply as a way to bookmark them, later exploring and purchasing in a physical store.

This makes an Add-to-Cart-based north-star metric vulnerable to the same fundamental flaw as the Conversion Rate: it misclassifies users who engaged in product discovery, added items to their cart, and ultimately completed their purchase in-store as failed conversions.

In reality, the Add-to-Cart action is a stronger indicator of successful online product discovery than of an imminent online purchase. From a holistic perspective, these customers have followed a highly successful and preferred journey, emphasizing the need for a broader evaluation beyond traditional e-commerce metrics.

To eliminate this bias, it is essential to identify a funnel stage that is reached primarily by customers who intend to complete their purchase online rather than in-store. This point should come after the Add-to-Cart action but may vary depending on the website’s flow.

In many cases, based on the checkout process flow outlined above, the best approximation for measuring true conversion intent is the Customer Identification step, also known as the Checkout Login screen. Reaching this stage indicates a clear intent to complete the transaction online, making it a more reliable benchmark for assessing conversion potential.

As a result, one of the most effective north-star metrics for evaluating purchase funnel efficiency is Checkout Conversion Rate — the proportion of customers who successfully place an order after reaching the Checkout Login screen. This metric provides a clearer picture of checkout performance and offers valuable insights for optimization.

At this stage, customers are prompted to log into an existing account, create a new one, or continue as a guest. Encouraging account registration is particularly important for loyalty-driven CRM initiatives, which is why brands often highlight benefits such as easy access to order status to incentivize registered purchases.

While most customers encounter the Customer Identification step, some checkout flows bypass it. For example, registered users who are already logged in will skip this step when entering the purchase funnel, and those using express payment methods may follow a different flow entirely.

To ensure accurate metric calculations, brands must account for these exceptions. The equivalent step in alternative checkout paths should be included in the denominator to accurately reflect the number of users reaching this stage, while all successful transactions — regardless of the path taken — should be counted in the numerator. This approach ensures a comprehensive and precise measurement of checkout conversion rate and overall funnel efficiency.

While the checkout login screen is chosen as the point reached only by customers intending to complete their purchase online, a potential concern with this approach is that some users may enter this stage solely to gather information that influences their decision. Many e-commerce websites observe users progressing into the purchase funnel not necessarily to buy immediately, but to check delivery options, shipping times, packaging details, final costs including taxes, or accepted payment methods.

Although these behaviors may lower the Checkout Conversion Rate, they present an opportunity to improve the product discovery funnel. The upper funnel’s role is not just to help customers find products that match their preferences in terms of shape, material, or color, but also to address broader purchasing considerations. For example, if a customer needs an item by a specific date, delivery timelines and availability should be clearly communicated upfront, without requiring them to enter the checkout process unnecessarily.

In other words, optimizing lower funnel performance may require a more systemic approach that enhances clarity and accessibility across the entire website, ensuring that critical purchase-related information is available at the right stage of the journey. The traffic reaching the checkout should be highly qualified, meaning that customers enter the purchase process with clear expectations and encounter no unexpected issues. This is even more crucial in e-commerce than in physical stores, where in-person interactions can help resolve last-minute uncertainties.

Other times, analysis may reveal that improving the north-star KPI requires removing frictions within the checkout process itself.

However, even when customer journeys successfully result in an order, the purchase funnel provides valuable insights from a broader perspective. Given that online purchases are a secondary goal compared to in-store transactions, every completed order on the website can also be viewed as a missed opportunity for store conversion. By analyzing these transactions, brands can gain insights into which products — and, to some extent, which customer segments, such as those in specific shipping locations — chose to purchase online instead of visiting a store.

In the ideal world envisioned by luxury brands, online checkout would be unnecessary. Customers would explore products online but ultimately visit physical stores, where they could enjoy a superior shopping experience while allowing brands to build deeper, more valuable relationships with them.

However, this vision is not entirely realistic. While the primary goal remains to drive as many customers as possible to stores, it is equally important to provide a seamless and effective online purchase experience. When in-store visits are not an option, ensuring that customers complete their purchases through e-commerce becomes the secondary goal.

Traditional e-commerce metrics, such as Digital Revenues and Conversion Rate, primarily measure the effectiveness of online sales but fail to capture the full complexity of customer journeys that blend both digital and in-store interactions — an essential consideration for luxury brands.

The Checkout Conversion Rate, by attempting to filter out users who engage with the website purely for product discovery, offers a more refined and relevant metric for assessing lower funnel performance. As a guiding north star, it helps shape improvement plans that enhance the online purchasing experience. However, these plans may also require optimizations in the upper funnel to ensure that high-quality traffic flows through the entire purchase journey.

In the next article, we will consolidate insights from both the upper and lower funnel to present a holistic, end-to-end view of e-commerce’s role in the luxury brand customer journey.

M.P.

Setting up and ecommerce is easy, making e-commerce profitable requires mastering the Fashion Ecommerce Value Chain

We’ve already discussed in detail al the aspect of the Profit and Loss of Fashion Ecommerce, in this article we present and examin the activities that generates value for a fashion ecommerce and the potential pitfalls that fashion companies need to be aware of before the start setting up their ecommerce.

The fashion and luxury industry requires a highly specialized approach to e-commerce, balancing brand storytelling, customer experience, and operational efficiency. From product sourcing to customer service, every stage of the e-commerce value chain plays a crucial role in delivering a premium experience that meets the high expectations of luxury shoppers.

Each activity in the value chain is interconnected and each activity contributes to the customer satisfaction and to the profitability of the digital channels.

The e-commerce value chain activities

• Sourcing the product and managing the Cost of Goods Sold (COGS) forms the bedrock. Strategic sourcing ensures quality and competitive pricing, directly impacting margins. Understanding COGS allows for accurate pricing and financial forecasting.
• The e-commerce business model decision, whether to build in-house or outsource, dictates operational control and scalability. In-house development allows for customization but demands significant resources, while outsourcing offers flexibility and specialized expertise.
• Product digitalization and content production are paramount for online engagement. High-quality imagery, videos, and detailed descriptions create a virtual showroom, driving conversions.
• Traffic acquisition, brand awareness, and digital marketing are the lifeblood of online visibility. SEO, social media, and targeted advertising are essential to reach the desired audience.
• E-commerce platform requirements and development ensure a seamless user experience. A robust, scalable platform with intuitive navigation is non-negotiable.
• Store management activities, encompassing the commercial plan and returns management, optimize sales and customer loyalty. A well-defined commercial plan drives promotions and inventory management, while efficient returns processes build trust.
• Logistics & shipping directly impact customer satisfaction. Fast, reliable delivery is a key differentiator.
• Customer service, including multilingual support, whether in-house or outsourced, fosters customer relationships. Prompt, helpful assistance builds brand loyalty.
• Payment systems must be secure and diverse, catering to global preferences. Offering multiple payment options reduces cart abandonment.
• Finally, e-commerce team organization ensures smooth operations. Clearly defined roles and responsibilities are vital for efficient workflow and strategic execution. Each of these components must be meticulously planned and executed to build a thriving international fashion e-commerce business

What is the fashion ecommerce value chain

The fashion ecommerce value chain is the set of processes that need to be implemented in order to run an ecommerce, in other words the value chain is made of all the activities that need to be managed in a fashion ecommerce business

1. Sourcing the product and the Cost of Goods Sold
2. Ecommerce Business Model decision: in house or outsourcing
3. Product digitalization and content production
4. Traffic acquisition, brand awareness and digital marketing
5. Ecommerce platform requirements and development
6. Store management activities: commercial plan, returns management
7. Logisitics & Shipping
8. Customer Service, multilanguage, in house and outsourcing
9. Payment systems
10. Ecommerce team organization

Sourcing the product and the Cost of Goods Sold

Strategic sourcing is the foundation of a successful fashion e-commerce business. It involves identifying reliable suppliers who can provide high-quality products at competitive prices within the time limits that you need. Effective sourcing directly impacts the Cost of Goods Sold (COGS), which determine your gross margin. Managing COGS is crucial for profitability. A lower COGS allows for more competitive pricing or higher profit margins. Understanding and controlling these costs through efficient sourcing is essential for financial sustainability of the e-commerce.

If you are the manufacturer of your product you will probably sustain a lower cost than if you need to buy your product and then resell online. This is the case of fashion brands that run their own ecommerce.

If you are a retailer and you buy the products at wholesale price, and then you resell them on your website, you will generally sustain higher cost for sourcing the product and therefore your gross margin will decrease.

The advantages for retailer are that they can source their products from a variety of brands and suppliers, thus creating a richer assortment; and the second advantage is that you may have less stock in your warehouse as you can source the product based on the demand.

E-commerce Business Model Decision: In-house or Outsourcing

The decision to handle e-commerce operations in-house or through outsourcing can significantly impact the profitability of the e-commerce. In-house operations offer greater control over branding, customer experience, and data. However, they require substantial investment in infrastructure, technology, and personnel.

Outsourcing, on the other hand, can provide access to specialized expertise, scalability, and reduced upfront costs. The choice depends on the business’s resources, strategic goals, and desired level of control.

Product Digitalization and Content Production

Forfashion brands product digitalization and high-quality content are your virtual showroom. This includes professional photography, videos, 360-degree views, and detailed product descriptions. These elements create a compelling online shopping experience, build trust, and drive conversions. Investing in excellent content is crucial for showcasing the quality and appeal of fashion items.

Photoshooting style-guides

Photoshooting style-guides

Photo studio for E-commerce

Photo shooting for fashion ecommerce

Traffic Acquisition, Brand Awareness, and Digital Marketing

Driving traffic to your e-commerce store requires a robust digital marketing strategy. This encompasses Search Engine Optimization (SEO), Pay-Per-Click (PPC) advertising, social media marketing, email marketing, and content marketing. Building brand awareness is equally important. Consistent branding across all channels, engaging content, and a strong online presence are key to attracting and retaining customers.

E-commerce Platform Requirements and Development

The e-commerce platform is the technological backbone of your online business. It must be user-friendly, secure, scalable, and it should be correctly sized for your business.

Some ecommerce platforms provide you will all the features that you need to run a small business but the same platform might not be suitable for a large one.

The ecommerce platform is usually divided into a Front-end – the ecommerce website – and a Back-office – the administrative panel.

Key features of the front-end include: pages (home page, about us, contact us), navigation menu, PLP Product Listing pages or category pages, Product Page (PDP) and checkout witha secure payment gateway.

In the back office you have control of visual merchandising, inventory management, order management.

Finally every ecommerce platform needs to integrate in your technological ecosystem that is generally made of an ERP, Product Information Management (PIM), Product Lifecycle Management PLM, and customer relationship management (CRM) integration.

Choosing the right platform helps you develop a smooth a seamless customer experience and organise your team and ecommerce processes.

Store Management Activities: Commercial Plan, Returns Management

Effective store management encompasses a well-defined commercial plan, including promotions, pricing strategies, and inventory management. It also involves establishing a clear and efficient returns process. A smooth returns experience builds customer trust and encourages repeat purchases. Both aspects are crucial for maximizing sales and customer loyalty.

Visual Merchandising & Product Discovery

• Curated Collections & Storytelling – Instead of generic categories, luxury brands should emphasize editorial curation (e.g., “Parisian Summer Edit” rather than “Women’s Dresses”).
• Automated & AI-Driven Sorting – Utilize AI-powered merchandising tools to dynamically adjust product ranking based on customer preferences, bestsellers, and inventory levels.
• Localized Merchandising – Luxury markets vary globally. A tailored approach ensures that winter collections appear in New York while resort wear is featured in Dubai.

Logistics & Shipping

Fast, reliable, and cost-effective logistics and shipping are essential for customer satisfaction. This includes order fulfillment, packaging, shipping options, tracking, and returns logistics. International e-commerce requires navigating complex customs regulations and shipping costs. Efficient logistics can be a significant competitive advantage. www.digitalfashionacademy.com

Customer Service, Multilanguage, In-house and Outsourcing

Providing excellent customer service is paramount in the competitive e-commerce landscape. This includes offering multiple channels for support (email, phone, chat), providing timely and helpful responses, and handling complaints effectively. For international businesses, multilingual support is crucial. The decision to manage customer service in-house or outsource depends on factors such as cost, scalability, and desired level of control. www.digitalfashionacademy.com

Payment Systems and Fraud Prevention

Offering a variety of secure payment options is essential for catering to a global customer base. This includes credit cards, debit cards, digital wallets, and local payment methods. A secure and seamless payment process reduces cart abandonment and builds customer trust.

Flexible Luxury Payments – High-value purchases require installment payments (Klarna, Affirm), crypto payments, and private banking options.

AI-Powered Fraud Detection – Advanced fraud prevention tools can identify suspicious activity while ensuring VIP customers aren’t blocked due to high-value transactions.

E-commerce Team Organization

A well-structured and efficient e-commerce team is crucial for smooth operations. This includes clearly defined roles and responsibilities across departments such as marketing, sales, technology, logistics, and customer service. Effective communication and collaboration are essential for achieving strategic goals.

Want to learn more about ecommerce value chain?

Explore our online courses created by leading fashion professionals or contact us.

One significant risk of an approach that relies solely on these metrics is that all costs associated with the online presence are allocated to the e-commerce Profit & Loss (P&L). Meanwhile, a considerable portion of in-store revenue is driven by customers who initially engage with the website, yet these sales are not reflected in the online P&L. This disconnect can distort the true value of the online channel, undermining its role in driving both digital and physical sales.

To address this complexity, a more holistic approach is needed — one that analyzes the customer journey across all channels, with a special emphasis on online interactions. This journey can be visualized as a funnel. The following analysis focuses on the upper part of the funnel, often identified as the product discovery phase.

PRODUCT DISCOVERY CHANNELS

During this stage, customers explore the brand’s product catalog. Success occurs when customers identify products that align closely with their needs, prompting them to move closer to purchasing.

Product discovery takes place through multiple channels:

• Physical Stores: Visiting a store in person or browsing its window displays.
• Offline Marketing: Channels like billboards, magazines, public transportation ads, and similar media.
• Brand Website: A central touchpoint where many e-commerce journeys begin.
• Brand Mobile App: Delivering a personalized, on-the-go shopping experience.
• 3rd Parties Partner Platforms: Third-party websites or apps, such as concessions and marketplaces.
• Other Online Channels: Social networks, digital ads, and other web-based platforms.

In luxury fashion, where careful consideration is a key part of the purchasing process, multiple channels are often involved for a single customer. According to the RACE framework for marketing, some channels align with the Reach (or Awareness) stage, while others support the Act (or Consideration) stage. However, all channels contribute to helping customers identify and select the right products.

It’s important to clarify that, while several channels operate online, this analysis focuses specifically on website performance, as it is the primary driver of e-commerce activity. For simplicity, the term “online” will be used throughout to refer exclusively to the website.

CHALLENGES WITH TRACKING

At first glance, tracking might seem like the solution to understanding how the brand’s website contributes to overall business performance. It offers the potential to seamlessly follow customers across the website, stores, and other touchpoints, such as mobile apps, to build a comprehensive view of their journey and revenue impact. However, this approach comes with significant challenges, particularly for luxury brands.

In the early stages of the customer journey, it is crucial to maintain the high-end experience by minimizing intrusive tracking methods. Preserving the brand’s exclusivity and sophistication is essential to building trust and loyalty. As the relationship develops and a personal connection is established — often through a client advisor — tracking becomes both more practical and less invasive.

Additionally, the luxury sector’s distinct characteristics present further complexities. Aspirational purchases, gifting, and the high-value nature of products mean that luxury brands often deal with a higher proportion of first-time customers. This reduces the effectiveness of conventional tracking strategies and CRM tools typically used in more transactional businesses.

In the absence of precise tracking, it becomes crucial to identify the most effective leading indicators of successful online product discovery. In other words, which KPIs specific to this stage of the customer journey can be monitored to predict future conversions, regardless of whether the transaction ultimately occurs online or in-store?

PRE-PURCHASE BEHAVIORS

When analyzing website visitor behavior, two distinct patterns emerge. Some users show little interest in exploring available products, exhibiting high bounce rates or minimal interaction. Others are more engaged, spending time navigating search results (SERPs), product listing pages (PLPs), and ultimately product detail pages (PDPs). Among those considering a purchase, users typically fall into one of three categories:

1. A2C (Add-to-Cart) CTA (Call-to-Action): These users clearly demonstrate intent to purchase by adding a product to their cart.
2. Other CTAs: These users interact with alternative buttons, such as checking product availability in physical stores, contacting customer support, or adding items to their wishlist. While not directly adding to the cart, these actions indicate interest and movement toward a potential purchase.
3. No CTA: These users do not engage with any buttons on the PDP but may still be considering a purchase. Their actions might include taking screenshots of the PDP, saving the product link, or doing nothing explicit. While there’s no visible interaction, these users may return to the product later, perhaps during an in-store visit or after consulting a client advisor.

Customers who intend to make an online purchase typically fall into the first category, as the Add-to-Cart action is required to enter the website’s checkout process. For this reason, traditional e-commerce often views the A2C Rate as the most reliable leading indicator of an upcoming transaction.

However, research shows that the A2C action is often used to save products for later rather than to proceed immediately with a purchase. According to Baymard, 42% of customers who want to save a product for later consideration go through the A2C button. This makes A2C an unreliable signal of a confirmed transaction. The challenge is even greater in luxury markets, where many in-store transactions occur without a prior A2C action online. In addition, for luxury brands aiming to drive as many transactions as possible in-store, the A2C step is optional in the ideal customer journey they envision.
Consequently, relying on A2C as a primary performance indicator in this industry can be even more misleading.

Referring back to our earlier discussion, it becomes clear that optimizing the product discovery journey solely to maximize the A2C rate risks undermining overall business performance. While online metrics may improve, in-store transactions could suffer — potentially outweighing the online gains. In systems thinking terms, a high A2C rate might represent a local maximum, whereas the true goal is to achieve a global maximum that benefits the entire business.

From a tracking perspective, the first two user categories (A2C and other CTA interactions) provide actionable data. However, the third category, which plays an important role as a bridge between online and offline experiences, occurs without detectable interaction, and therefore it’s neither trackable nor measurable.

All these considerations highlight why the step marking the closure of the upper funnel, just before customers enter the purchase journey, cannot reliably indicate the success of a product discovery activity. Even when expanding beyond the single A2C metric to include alternative behaviors, this stage remains insufficient as a comprehensive measure.

To develop a meaningful metric for upper funnel success and a strong predictor of future revenues, it is essential to step back and examine how customers discover the products they eventually choose to buy. A deeper understanding of this discovery process is key to accurately evaluating and optimizing the product discovery journey.

INTRODUCING THE ENGAGEMENT RATE

Healthy activity in the website’s product discovery area — PDPs, PLPs, and SERPs — is the best signal for upcoming purchases.
As in a mall or a supermarket, the volume of the crowd, the time spent in the lanes or in front of the windows, and the interaction with the products on the shelves indicate healthy conditions for those businesses. Similar observations can be considered for a brand website.
In a single term, Engagement is the behavior to measure, and the associated metric should be used as the north star metric for the product discovery stage of the funnel.

This approach aligns with Google’s recent updates to its Analytics product, which introduced more advanced methods for measuring website activity. Among these updates is a new metric called Engagement Rate, which goes beyond basic metrics like button click ratios. It aims to capture the qualitative aspects of user interactions, such as time on site, actions taken, and deeper navigation patterns, offering a richer understanding of genuine user engagement.

In GA4, a session is classified as “engaged” if it meets at least one of the following criteria:

• The session lasts longer than 10 seconds.
• The session includes at least one conversion event.
• The session involves two or more pageviews or screenviews.

A high Engagement Rate indicates that users find the content valuable and are actively engaging with the site or app. Companies can leverage this metric to optimize user journeys and improve conversion rates.

Furthermore, the individual metrics that contribute to the Engagement Rate definition — such as time spent on the site or the number of pages viewed — can be further analyzed for deeper insights.

Brands should establish a tailored definition of Engagement Rate, either adopting Google’s standard or customizing it to reflect better the unique characteristics of the online product discovery journey for luxury goods. For instance, users interested in luxury products tend to engage for longer periods than the typical duration suggested by Google.

Once defined, this customized metric should act as a guiding north star for upper-funnel activities, informing all experiments related to Conversion Rate Optimization (CRO). As customer behaviors evolve, the definition of this metric should be revisited and refined. The underlying assumption is that a high Engagement Rate signals the brand’s success in capturing and maintaining customer interest, encouraging deeper exploration of the catalog, and ultimately increasing the likelihood of future purchases, whether online or in-store.

IS LONG TIME SPENT ON SITE ALWAYS A POSITIVE INDICATOR?

A common critique of using metrics like time spent on site as an engagement indicator is that longer durations could imply either customers are actively exploring the catalog and evaluating products they plan to purchase or, conversely, that the site lacks relevance, leading to frustration and difficulty in finding desired products. This distinction is why, when introducing the Engagement Rate, the focus was placed on defining the activity as “healthy” to ensure the metric accurately reflects meaningful user engagement.

There are several ways to address these concerns. One effective approach, particularly in this context, is to use a mutually destructive pair of metrics: alongside the Engagement Rate, another metric can be tracked to ensure that customers are deriving real value from the discovery process. This secondary metric, often referred to as a health metric, is not intended for primary optimization but serves as a safeguard. For instance, brands might monitor the A2C Rate or interaction rates with CTAs within the PDP, establishing a threshold to detect a potential drop in engagement.

Another approach is to identify key elements that ensure the intrinsic health of engagement. For luxury brands, a positive customer journey typically involves significant interaction with product galleries, particularly images. This interaction rate can be integrated into the custom definition of Engagement Rate, providing a more accurate measure of genuine engagement.

It’s important to note that the Engagement Rate, as defined above, does not provide an absolute measure of the quality of the product discovery segment in the funnel. Given that different brands may have varying definitions of this metric, it’s not easily applicable as a benchmark against industry standards or competitors. Instead, its value lies in tracking changes over time — specifically, comparing the metric before and after a particular experiment or website update. Drawing from the Toyota Kata approach covered in the previous discussion, the Engagement Rate should act as a measurement system that captures trends and ensures that changes in the website are consistently moving toward the vision.

WRAPPING IT UP

While traditional e-commerce can effectively rely on the Add-to-Cart Rate to measure the performance of the product discovery stage, brands that favour an omnichannel experience cannot rely on it as a sole metric. This is because it doesn’t provide a comprehensive view of customer journeys that span both online and in-store experiences, which are crucial for luxury brands.

The Engagement Rate offers a more sophisticated and relevant metric for assessing the health of the upper funnel, acting as a guiding north star for improvement plans. However, defining and applying this metric requires careful consideration and customization to align with the brand’s specific strategies.

Optimizing the product discovery phase of the website based on the Engagement Rate can deliver holistic benefits, regardless of where the customer ultimately decides to make the purchase — whether autonomously online or by visiting a physical store.

In the next article, we will explore the lower stage of the e-commerce funnel, examining the key differences and commonalities in dynamics between luxury brands and transactional or traditional businesses at both ends of the funnel.

M.P.

Join us for an insightful webinar focused on pricing intelligence, benchmarking, and competitor analysis within the dynamic fashion and luxury sector. This session will explore how leading brands leverage data and technology to achieve optimal market positioning.

Key Discussion Points:

• The evolving landscape: Understand how increased production costs, the pursuit of ultra-luxury customers, and shifting consumer preferences are impacting the fashion and luxury industry. The rise of e-commerce and online sales has intensified competition, making it crucial to find the right product-price-brand positioning.
• Strategic price positioning: Discover how to align your pricing strategy with the characteristics of various geographic target markets.
• Data-driven decision making: Learn how to use software that gathers millions of data points from hundreds of brands worldwide. Specifically, the webinar will cover:
  • Product assortment by brand and country.
  • Product price positioning by brand and category.
  • Achieving almost real-time pricing monitoring.
• The role of AI: Gain insights into the role of Artificial Intelligence in pricing analysis.
• Expert perspectives: Hear from industry leaders who have successfully implemented best practices for price positioning using Competitoor software.

Featured Speakers:

• Maurizio Catellani, CEO at Competitoor, will share his expertise on how cutting-edge technologies can add customer value, and how AI can positively impact the business world.
• Enrico Fantaguzzi, Co-founder of Digital Fashion Academy, will offer insights from his extensive experience in scaling fashion brands online, and discuss digital transformation in e-business management.
• Gianluigi Zarantonello, Global Director of Digital Solutions at Valentino, will discuss how the lines between online and offline are blurring and the need for new digital skills. He will also address the importance of a single customer view and data-driven strategy.
• Fulvio Mercuri, Head of Pricing at Tod’s spa, will share his strategic approach to pricing, market positioning and how this drives revenue growth and profitability.

How to determine the best price for your products?

This webinar is essential for fashion professionals looking to optimise their pricing strategies, gain a competitive edge and understand how to reach the right customers with the right product and the right price. Learn from the experts and take your brand to the next level.

The webinar is sponsored by Competitoor, a leading platform providing price monitoring and product catalog benchmarking software. Competitoor’s platform assists brands in making the best pricing decisions for their products.

This description should effectively promote the webinar and highlight the value it offers to professionals in the fashion and luxury industry.

How to determine the best price for a specific market?

The best price for a product is the price that maximises the profit margin and the opportunity of selling.

In the competitive market of digital marketplaces and search engines, the algorithms often determine how much visibility your products will have based on a combination of stock, price, brand reputation and other factors that are relevant to the marketplace.

Chosing the right price can heavily influence the visibility that your product will gain organically on the search results pages of the marketplaces.

Join the webinar, register now to receive invitation.

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AI Fundamentals: Essential Knowledge and Applications for Fashion & Luxury

Artificial Intelligence (AI) is transforming industries, and understanding its core concepts is crucial for leveraging its potential. This post aims to demystify AI and explore its practical applications in fashion eCommerce.

Understanding AI: Key Concepts

AI Defined:
AI isn’t a magical tool but a broad field of computer science focused on creating systems capable of tasks that typically require human intelligence, such as speech recognition, decision-making, and language translation.

AI is rapidly becoming part of every day operations for fashion brands, from trends analysis to customer services, AI will increase efficiency in all activities of the value chain.

Terms to know in AI

• Algorithm: A set of rules a computer follows to solve problems or complete tasks, forming the backbone of AI systems.
• Data Set: A collection of data used to train and test machine learning models. The quality and quantity of this data are critical for performance.
• Training and Testing: Training involves teaching a model using a dataset, while testing evaluates its performance with new data.
• Supervised vs. Unsupervised Learning: Supervised learning uses labeled data to improve accuracy through feedback, whereas unsupervised learning discovers hidden patterns without explicit guidance.
• Model: The result of applying an algorithm to data, representing learned patterns for making predictions or decisions.
• Neural Networks: Inspired by the human brain, these interconnected units (neurons) work together in layers to process information.

Machine Learning vs. Deep Learning

Machine Learning (ML):
A branch of AI that uses algorithms to learn from data and make predictions. ML models are generally simpler and require less data and computational power compared to deep learning.

Deep Learning (DL):
A subfield of ML that employs neural networks with many layers to analyze vast amounts of unstructured data, such as images and text. DL models are more complex and demand significant computational resources.

Practical AI Applications in Fashion eCommerce

1. Automated Product Descriptions:
AI can revolutionize product description creation by leveraging existing company data to generate descriptions automatically. This approach reduces time and costs, ensures consistency across markets, and supports multiple languages. It also allows for manual review to maintain quality.

2. Enhanced Customer Support:
AI-driven intelligent agents can interpret and index information from various document formats to provide accurate, immediate answers to customer queries. This reduces the load on customer service teams, enhances customer experience, and streamlines operations.

3. Personalized Shopping Experiences:
By understanding customer behavior, AI can offer tailored product recommendations, making the shopping journey more engaging and efficient. Digital shop assistants can interact in multiple languages and provide context-aware suggestions.

4. AI-Driven Customer Insight and Service Enhancement
Today, we explore how leveraging AI can significantly enhance our services by listening closely to market feedback. Utilizing systems like Trustpilot and advanced AI tools, we analyze vast amounts of unstructured data from various sources, including textual feedback, social media reviews, support tickets, and audio messages from call centers. Our goal is to transform this unstructured data into actionable insights, visualized through dashboards or used to trigger marketing automation journeys.

To tackle these challenges, we adopted a project approach focusing on creating advanced sentiment analysis solutions. These solutions not only identify key topics and customer sentiments but also integrate this structured data into our business analytics systems. This enables us to improve service and product quality, make informed decisions, and directly address customer needs.

Case Study Highlights:

1. Sentiment Analysis: AI-driven sentiment analysis consolidates customer feedback across digital platforms, highlighting issues and opportunities. This allows for real-time response and service improvements.
2. Automation of Insights: The system automates the collection, indexing, and reporting of data, saving significant time and resources.
3. Audio Data Analysis: Speech-to-text models convert audio messages into structured data for analysis, aiding in customer service and enhancing decision-making processes.
4. AI-Powered Chatbots: Implementing AI-driven voice assistants provides 24/7 customer support, reducing costs and maintaining service quality.

Path to AI Implementation:

1. Understanding Business Processes: Map out and define business processes and objectives.
2. Technological Assessment: Evaluate the impact of AI and prepare data accordingly.
3. Pilot Projects: Start with small, quick projects to generate initial value, then optimize and scale.
4. Team Expertise: Assemble a team with AI-specific skills to manage and expand AI initiatives.

ROI and Benefits:

• Operational Efficiency: Automation reduces task execution time and minimizes errors.
• Cost Reduction: Streamlined processes lead to significant cost savings.
• Actionable Insights: Data-driven decisions enhance strategic planning.
• Product Innovation: AI fosters new product development, giving a competitive edge.
• Risk Management: AI helps in identifying and mitigating risks, ensuring compliance.

AI in Shopify eCommerce: Shopify offers various AI-powered tools for content creation, translation, and reporting, depending on the subscription plan. It’s essential to align AI tools with specific business processes to maximize benefits.

This article is based on the webinar “fashion + AI” in collaboration between Digital Fashion Academy and Alpenite.

Conclusion

AI offers significant advantages in fashion eCommerce, from automating product descriptions to enhancing customer support and personalizing shopping experiences. By integrating these AI-driven solutions, businesses can improve efficiency, reduce costs, and deliver superior customer experiences.

Author: Marc Sondermann
Entrepreneur and Former CEO
Fashion Magazine

The past decade has witnessed a seismic shift in the fashion industry, fundamentally altering how brands operate, communicate, and connect with consumers. The traditional model of fashion weeks and seasonal collections has been replaced by a more dynamic, year-round engagement with audiences. This transformation has been driven by the rise of digital communication, social media, and a new generation of influencers who now play a pivotal role in shaping trends and consumer behaviour.

The Old Guard: A Top-Down Approach

Ten to twelve years ago, the fashion landscape was relatively straightforward. Fashion weeks were the epicenter of trendsetting, dictating seasonal demands. Luxury brands would unveil collections that trickled down to fast fashion retailers, who replicated these designs for the mass market. Communication was top-down, with designers crafting collections and traditional media amplifying their messages. Retail and wholesale networks were the primary sales channels, ensuring a consistent flow of products from runway to consumer.

Disruption and Decentralization

Fast forward to today, this model has been upended. The rise of social media and digital platforms has democratized fashion communication. Influencers and content creators have become the new gatekeepers, often eclipsing traditional fashion publications like Vogue. Brands have had to internalize their communication strategies, becoming publishers in their own right. This shift allows them to directly engage with consumers, leveraging social media to build and maintain brand loyalty.

Seasonality has also been disrupted. Instead of rigid seasonal collections, fashion now operates on a continuous cycle, with brands constantly interacting with consumers. The direct-to-consumer model has gained prominence, complemented by e-commerce and digital marketplaces. The COVID-19 pandemic accelerated this shift, with virtual sales and personal interactions via platforms like WhatsApp and Zoom becoming commonplace.

Skills for Success in the Modern Fashion Landscape

To navigate this transformed industry, the skill set required has evolved. Success now hinges on a blend of traditional managerial acumen and cutting-edge technological expertise. Communication, once the domain of external agencies and traditional media, now requires in-house teams adept at digital storytelling and influencer collaboration.

Big fashion conglomerates, particularly those in France, have professionalized their operations, emphasizing meticulous control over every aspect of the brand. Leaders like Bernard Arnault of LVMH exemplify this shift, prioritizing precision and consistency across all touchpoints. This level of control, akin to multinational corporations like Procter & Gamble, necessitates a new breed of fashion professionals—”fashion engineers” who combine creative flair with technological prowess.

The Future of Fashion: Balancing Creativity and Technology

Looking ahead, the integration of technology and creativity will continue to define the fashion industry. E-commerce, data analytics, and artificial intelligence are becoming integral, automating processes and enhancing decision-making. However, the essence of fashion—cultural sensitivity and the ability to create compelling narratives—remains irreplaceable.

Technology will facilitate these processes, but the human touch is crucial for interpreting and responding to cultural trends authentically. The next wave of innovation will likely involve even greater personalization, leveraging data to tailor experiences and products to individual consumers. The challenge will be to harness these technological advancements while preserving the creativity and empathy that make fashion resonate on a deeply personal level.

Conclusion: Embracing Change

The last decade has redefined the fashion industry, bringing both challenges and opportunities. Brands that adapt to this new reality, embracing both technological advancements and the timeless appeal of human creativity, will thrive. The future of fashion lies in this delicate balance, where innovation meets tradition, and technology enhances, rather than replaces, the artistry at the heart of the industry.

Watch the full interview

For luxury fashion brands, traditional e-commerce KPIs — such as Add-to-Cart Rate, Conversion Rate, and Digital Revenues — are typically adapted from transactional models. This KPI framework works indeed well for companies that are e-commerce-driven. For example, Amazon is built around selling physical products, but its business is fundamentally driven by e-commerce, with KPIs focused on online transactions. On the other hand, platforms like Udemy and Epic Games, which sell digital products such as courses and games, rely entirely on online sales without the need for physical inventory or logistics.

For fashion brands like Zara or MyTheresa, where the in-store experience is less central or the physical presence is minimal, these KPIs are also effective.

However, luxury brands present a more complex picture. For them, e-commerce is just one part of an integrated, immersive brand experience, and conventional KPIs may not fully capture the richness of customer interactions, brand perception, or loyalty — key elements of success in high-end retail.

UNIQUE ASPECTS OF CUSTOMER JOURNEYS

Several factors uniquely shape the luxury customer journey. First, competition among luxury brands is far less intense compared to the mass-market segment. When a customer chooses a specific handbag from a brand, a slightly subpar online experience is unlikely to drive towards another brand. The switching barrier is much higher than in transactional businesses, where seamless online interactions often dictate customer loyalty.

Moreover, luxury brands have long been anchored in the in-store experience. They are neither web-first nor web-only businesses. E-commerce was introduced not to replace but to complement their brick-and-mortar presence, enhancing overall performance rather than serving as the primary sales channel.

It’s also essential to recognize that these brands don’t sell digital products; their physical products are meant to be part of a larger experiential journey. The nature of luxury goods makes the in-person element particularly crucial. Customers want to feel the fabric, admire the craftsmanship, and immerse themselves in the brand’s ambiance. These tactile interactions are a vital part of the decision-making process, much like test-driving a car before purchase. In this context, a luxury purchase transcends a simple transaction — it becomes an emotional and immersive experience.

A central figure in delivering this immersive experience is the client advisor, whose role extends far beyond facilitating a purchase. Acting as brand ambassadors, client advisors are instrumental in establishing meaningful relationships with customers, understanding their unique preferences, and providing personalized recommendations. Through attentive and knowledgeable guidance, they help transform each visit into a memorable experience, fostering loyalty and encouraging repeat visits. In luxury retail, the client advisor’s expertise and attentiveness are not just service enhancements; they are pivotal to achieving lasting success.

Finally, the high price point of the goods often makes customers hesitant to buy online without first experiencing the product in person. They want to ensure that key aspects such as size, color, and material meet their expectations, while also gaining confidence in the overall quality and feel of the item.

Taken together, these factors make it clear that in the luxury industry, online and offline experiences are deeply intertwined, making it difficult to assess e-commerce performance in isolation with conventional KPIs.

IS “E-COMMERCE” THE RIGHT WORDING?

These observations highlight that customers often prefer to include a store visit as part of their purchase decision-making journey. Brands, in turn, actively encourage this by steering customers toward the in-store experience, where deeper, long-term relationships can be cultivated, rather than prioritizing a quick online sale.

Transaction data underscores the importance of in-store engagement: despite offering the same products, metrics like Units per Transaction, Average Unit Retail, and, consequently, Average Order Value are consistently higher in stores, while Return Rates are lower. This highlights how online and offline channels play distinct, complementary roles, creating a seamless, integrated luxury shopping experience.

Given the close integration of online and offline experiences, it’s worth reconsidering whether “e-commerce” is even the right term. A more fitting description might be “online presence”, as digital channels in luxury retail aim to complement, rather than replace, the immersive in-store experience that defines the brand.

E-COMMERCE KPIs AND SYSTEM THINKING

When revisiting the discussion of primary e-commerce KPIs, it becomes evident why traditional online-centric metrics fall short in capturing the full complexity of the luxury brand ecosystem. While metrics like Add-to-Cart Rate, Conversion Rate, and Digital Revenues can still provide useful insights in certain contexts, they are not suitable as “north star” metrics for a strategy that emphasizes the offline experience.

A well-regarded approach to optimizing system performance is the Toyota Kata method, which focuses on assessing the current state and conducting iterative experiments to gradually move toward target conditions aligned with the broader vision. The success of this approach depends on a measurement system that captures trends and ensures that changes are consistently moving in the right direction.

Take the example of a racing car: reducing the car’s weight might seem like an easy win for increasing speed, but if the measurement system focuses solely on weight as a leading indicator for velocity, replacing the engine with a smaller one might be viewed as an improvement. However, this could result in a slower car due to reduced power.

Similarly, adopting e-commerce Conversion Rate as a “north star” metric poses the risk of optimizing for a local maximum. Enhancing the online experience could inadvertently draw attention away from store visits, leading to diminished overall business performance. While improved digital metrics may align with better company results in some cases, this is not guaranteed. To use a fitting geographical analogy, relying on such a metric is like navigating with a compass that occasionally points north and occasionally doesn’t — hardly the kind of tool you’d trust to guide your journey.

WRAPPING IT UP

At this stage of the discussion, a crucial question emerges: if the traditional e-commerce KPI triplet falls short, what is the better alternative? Unfortunately, there’s no simple answer. The challenge with conventional KPIs is that they attempt to isolate the digital segment, whereas for luxury brands, the online and offline experiences are deeply intertwined. Any improved approach must offer a holistic perspective, though this inherently makes such KPIs more complex to calculate than straightforward metrics like the online Add-to-Cart Rate.

In the next article, we’ll take a deeper dive into the e-commerce funnel and introduce new indicators that are better suited for a comprehensive analysis.

The good news is that while the north star metric should be holistic, the action plan can still focus on specific areas. However, for optimal results, the strategy will likely need to integrate digital actions, in-store initiatives, and a combination of both.

M.P.

The Shopify features that won over fashion and luxury brands

• Ease of Use: Shopify’s user-friendly interface and intuitive tools make it quick and easy for brands to set up and manage their online stores without requiring extensive technical expertise.
• Cost effectiveness: with Shopify you have the option to start with small budgets and then grow.
• Scalability: Whether a brand is just starting out or already established, Shopify offers scalability to accommodate growth. It can handle large volumes of traffic and transactions without sacrificing performance.
• Security and Reliability: Shopify prioritizes security and reliability, providing robust infrastructure and encryption to protect customer data and ensure secure transactions.
• Native ability to integrate with social networks and digital marketplaces such as Facebook Shopping and Google Shopping.

Despite all the “pros” and the quick implementation timeframe and reduced set-up costs, Shopify brings also a number of contraints and attention points that, if unknown, can lead to reduced or deteriorating performance.

What are the cons or risks connected with Shopify?

• Dependency on Third-Party Apps: While Shopify’s app ecosystem is extensive, relying heavily on third-party apps for additional features and functionalities can increase costs and introduce potential compatibility issues.
• Transaction Fees: Shopify has transaction fees associated with each sale, which can eat into your profits, especially for high-volume businesses. Salesforce Commerce Cloud, on the other hand, typically uses a tiered pricing model that doesn’t include per-transaction fees.

However Shopify has a solution or a different plan for different sizes of businesses.

How to implement and successfully run a Shopify Ecommerce channel?

To take advantage of the SAAS solution provided by Shopify you need to work within the boundaries established by Shopify and get to know the environment of applications available to extend Shopify functionalities.

The good news is that Shopify is really easy to use, but the truth is that you need some essential skills in order to craete a fully functioning fashion ecommerce and run it.

For example you need to know about managing couriers and shipping if you want to deliver your products to your customers. This is one of the overlooked aspects of fashion ecommerce.

To set up your shipping policy which is mandatory in Shopify you’ll need to decide how much to charge your customers for express and standard shipping, or decide to offer free shipping. And these options need to be configured in the shipping rates and zones of Shopify,

This is not an exclusive feature of Shopify, any ecommerce platform will have Shipping Zones and Shipping Rates features available, therefore you need to learn what they are and how to configure them.

How to use Shopify to deliver  Ecommerce and Brand Experience in fashion industry

Agenda

• Multi-channel integration:
  • Marketplace: Sell where people shop by linking your Shopify catalog to multiple online marketplaces.
  • Social media: Expand your audience with integrated tools to sell on Facebook, Instagram, TikTok and other platforms.
  • Online search: Sync your products to Google and post ads for free on various interfaces.
• Omnichannel selling: Reduce the gap between online and offline retail with Shopify POS (Point Of Sale)
  • Buy online, pick up in store
  • Browse in store, buy online
  • Buy in store, ship to customer
  • Online returns and exchanges
• Marketing & Promotions: Implement different promotions and discounting rules to increase ecommerce KPIs such Average Order Value and Units Per Transactions, Revenue and Gross Margin
• Integrated payment manager: accept payments with Amazon Pay, Apple Pay and implement buy now pay later
• Apps and extensions: chose among 8.000 free and paid apps including
  • Wishlist app
  • Translate and Adapt 
  • Instafeed app
• Reviews app
• Internationalization & Localization
  • Currency conversion
  • Languages
  • Domains and SEO
  • Duties and import taxes calculator
  • Market-specific content
  • Product publishing  by market
  • Customized prices by market
• Order Management & Sales Reports
  • Manage large order volumes and inventory.
  • Manage returns, track shipping, restock inventory, manage return fees, and send automated customer notifications
  • Detailed data and Advanced reports for in-depth analysis of store performance.
• Customization: Customization allows you to create a unique look and feel that reflects your brand personality and resonates with your target audience.
• Themes
  • Drag & Drop Interface
  • Pages & Templates
  • Metafields
  • Metaobjects
  • Blog
• Advanced personalization: how to use metafields and metaobjects to personilize the user experience
  • Theme Selection (free and paid)
  • CMS: Page and block modifications / content editing based on the market
  • Product Carousels
  • Adding fields to the product page (e.g., composition, model measurements)
  • Customizable fields (meta-fields) and additional information (What do customers ask for? What can be customized independently?)
  • How to create a store locator in Shopify: using meta objects
  • Magazine / Blog

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