Author: Enrico Fantaguzzi
Co-founder and Director
Digital Fashion Academy

Former Gucci, Yoox, Tod’s
PMP(r), Prince2

From Boutique to Algorithm: How AI is Redefining the Role of the Fashion Sales Assistant

In the age of AI, fashion eCommerce is finally catching up with the personalized attention shoppers once received in physical stores. At the heart of this transformation is Dressipi, now part of the MAP Digital, an AI-powered product data enrichment platform that helps fashion brands deliver personalised shopping experiences at scale.

Speaking during a Digital Fashion Academy session, Dressipi co-founder Sarah McVittie described how the platform was inspired by the intuitive skill of a brilliant shop assistant. “I once walked into a boutique in New York and a stylist picked out five outfits for me—all perfect. I bought them all. That kind of intuition is what we’ve worked to replicate using AI.”

I once walked into a boutique in New York and a stylist picked out five outfits for me—all perfect. I bought them all. That kind of intuition is what we’ve worked to replicate using AI.

Sarah McVittie

Decoding Style with Data

Initially a B2C project, Dressipi shifted to B2B after major UK retailers expressed interest in licensing its taxonomy system. Today, Dressipi enhances product feeds with a deep layer of styling, contextual, and dynamic data—including neckline types, fabric flows, and trend alignment—based on thousands of attributes.

This data doesn’t just optimize websites for conversion. It helps retailers understand what drives customer preferences, return rates, and even emotional resonance. For example, women with larger busts are more likely to return a crew-neck top than a scoop neck, these details impact algorithmic product recommendations.

Real-World Impact: The House of Bruar

John Hodge from The House of Bruar, a Scottish luxury retailer, shared how integrating Dressipi’s technology improved their recommendations. “We tested Dressipi against our existing engine and saw a 5% uplift in incremental value,” he said. “Outfits now reflect our brand DNA and are personalized to the customer’s preferences and context.”

Their team also benefited operationally—reducing manual effort for product tagging and visual merchandising while improving consistency across imagery and attributes.

“Outfits now reflect our brand DNA and are personalised to the customer’s preferences and context.”

John Hodge

Returns, SEO, and the Future of Discovery

Beyond styling, Dressipi tackles a critical challenge in fashion eCommerce: returns. By identifying patterns, such as whether returns are due to size, style, or stock fragmentation—the platform optimises for kept items, not just purchases.

Moreover, as search evolves to prioritize natural language (think “What should I wear to a summer wedding in Edinburgh?”), enriched product data becomes crucial. Dressipi supports brands in creating semantic layers for SEO, marketplaces, and even AI chat interfaces, bridging brand language with customer language.

The evolution of Customer Journey with AI

Drawing on the discussion with Sarah and John, the introduction of AI like Dressipi is significantly changing the customer journey in online fashion retail, aiming to replicate and enhance the personalised experience previously only available in physical stores.

Here are some key ways the customer journey is evolving:

Natural language search

Shift to Natural Language Interaction: The way customers search is changing from traditional keyword-based queries (like “black dress wedding”) to more natural language phrases (such as “looking for a pencil skirt for work that’s smart but a bit glamorous”). AI helps retailers optimise their product data and metadata to be discoverable through these natural language searches.

Highly personalised recommendations

Generic recommendations like “customers like you bought X” are ineffective in fashion due to variations in size, shape, height, weight, gender, and changing preferences. AI uses detailed product data (physical attributes, context, dynamic trends) and understands how specific features look or feel good on different people. This enables the system to create tailored outfit and product suggestions based on the customer’s taste, lifestyle, colour palette, and even physical characteristics, showing them their “best possible shop window”. The system learns from customer interactions over time.

Reduce ecommerce returns

Improved Fit and Reduced Returns: Understanding factors that contribute to returns, such as sizing issues (15-20% of returns) and style suitability (30-50% of returns), is crucial11. By incorporating fit data and understanding how attributes (like necklines) impact suitability for different body types, AI can help predict return likelihood2…. Algorithms can be optimised for “kept items” rather than just conversion rate, meaning customers are shown products they are more likely to keep12. This leads to a more positive post-purchase experience and reduces the frustration associated with returns.

Increase engagement

Style Guidance and Outfit Inspiration: Customers often need guidance on how to put items together. AI creates on-brand outfit suggestions that help customers visualise how to wear products for different occasions (e.g., work, evening, weekend). This helps customers see the versatility of items and encourages investment. The system understands what occasions are applicable for a specific product and suggests items that go well together8.

Consistent and Relevant Browsing: AI ensures that recommendations and product listings use consistent imagery, avoiding a jumbled look1314. Crucially, it takes into account current stock levels, including specific sizes, so customers are only shown products that are actually available to them. The rich, consistent data also allows for more effective and consistent filters and facets on the website, improving the browsing experience.

Marketing analysis

Deeper Customer Understanding and Segmentation: The detailed data generated by AI allows retailers to move beyond basic demographics and create powerful customer segments based on behaviour, preferences, and lifestyle (e.g., equestrian customer, pro farmer). This understanding enables the delivery of experiences and language tailored to these specific segments, making the customer feel understood and increasing engagement.

Integrated Brand Experience: The AI works closely with the brand’s creative team to absorb and reflect the brand’s DNA and styling principles. This ensures that the personalised recommendations and guidance remain true to the brand’s identity and help build resonant brand experiences online. Tailored landing pages can also be created based on customer intent and context.

Final Takeaway

Fashion retailers are realising that data is not just about optimization—it’s about storytelling, styling, and service. As AI reshapes the fashion landscape, tools like Dressipi are making it possible to scale the art of the sales assistant and build genuinely personal digital shopping experiences.

In essence, AI like Dressipi moves the online customer journey from a potentially overwhelming, static catalogue experience to a dynamic, personalised, and guided interaction that better reflects the nuances of fashion and aims to build a stronger connection with the customer

Watch the webinar

Digital transformation has been on the agenda of Fashion companies for a few years now, however even the large players with immense financial resources are struggling with this transformation process.

The biggest issues for fashion companies when dealing with digital transformation:

• The top management is not trained on Digital Management
• Decisions are not yet sufficiently based on data.
• Need for investment in technology
• Need to structure the Organization and processes

What are the benefits and risks from digital transformation?

How to deal with the risks of digital transformation?

In order to favour the adoption of digital best practices it’s necessary to adopt an incremental approach, with the goal of moving the organisation through a maturity growth in digital capabilities. The company growth can be achieved by providing training and coaching to the people involved in the transformation.

What are the enablers for the digital transformation in fashion companies?

The are some conditions that are necessary to start a digital transformation process, such as

• availability of digital skilled personnel,
• a management team motivated to change the organization
• budget for investment in IT solution, especially cloud and AI

How to implement digital transformation in fashion industry:

In order to successfully implement Digital Transformation in fashion brands and retailers, Fashion companies should focus on some specific transformative goals:

• Be customer centric: fashion brands should build the experience around the customer journey and focus on how to implement the customer satisfaction, read more about this in this article “unlocking customer satisfaction“.
• Near real time decision making: fashion brand should use analytics and business intelligence to make effective decisions rapidly;
• Management by objectives and non by process: every process should have a KPI to measure the results;
• Learn how to learn: companies should incentivate the ability to learn of their employees, for example making a catalog of relevant courses accessible to employees and rewarding the effort of employees to keep developing professionally and training.

Some apparel, fashion, and luxury companies won’t survive the current crisis; others will emerge better positioned for the future. Much will depend on their digital and analytics capabilities. […] Although no one in the industry foresaw the intensity of this crisis, some fashion companies are finding that they are better equipped than others—largely because of their digital know-how.

McKinsey – Fashion digital transformation

How to implement effective training programs for employees in the fashion industry

At Digital Fashion Academy we have worked hard to create the most advanced training program in Fashion Business Management adopting the most flexible solutions for our students. But we didn’t stop there, we also adopted the digital solutions for training that allow our students to interact with each other like they were physically present in the room and more.

Our approach requrires students to work together to build strategies and plans, priorities projects and analyse performance of fashion brands.

During the lessons the students are also challenged to examin real life situations and discuss them to understand how things work in the complex world of fashion.

Example of Informations Systems architecture: as is and to be

The following two pictures show two Information Systems ecosystems typical in fashion companies. The first one is an initial stage when the company introduces the first digital commerce applications. The second one represent a final stage where all the digital commerce applications are integrated effectively.

Acceleration and Deceleration of Digital Transformation

The pandemic crisis has accelerated a process of digital transformation that would have taken years to accomplish. However only some activities in the organisation of fashion companies can be actually digitally transformed in a matter of weeks. For example employees well accepted the change in their working habits moving from the offices to their homes, and companies and governments were happy and proactive to support this change by facilitating for example all the situations in which parents-workers were working from home and caring for their children at the same time.

The supply chain instead, was not ready to be digitally transformed and the production of samples and delivery of the collection was affected negatively by the pandemic crisis.

What really changed in a matter of days at the beginning of the pandemic crisis was the customer behaviour. Customer quickly moved from Bricks and Mortar stores to e-commerce websites. Whenever they had the need to purchase something during the pandemic they were able to get it online and delivered at their homes. Of course the needs were also different and therefore some product categories were penalised and some saw a surge of demand, for example home-wear and loungewear increased while luxury and travel accessories decreased.

The next steps in fashion digital transformation

The challenges ahead of us are unclear, but we can learn a few lessons from this crisis:

• Digital transformation needs to be happening in all activities of the value chain from product design to retailing
• Digital transformation needs to be governed by CEOs together with Cross-Functional team leaders
• The technological infrastructure of a company is a competitive asset and can determine competitive advantage
• Organisational models in headquarters and retail need to be flexible and malleable
• Analytical skills, Digital skills and People skills are essential to the success of the fashion companies

The digital transformation assessment of your company

If you are interested in the digital transformation process of your company, you can take the digital transformation self assessment for free here: digital transformation test.