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.

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.