Why merchandising is becoming an information science

Justin Thomas, VP Sales, EMEA North for Akeneo explains why merchandising is moving from intuitive decisions to attribute level performance analysis and why this matters in the new AI age.

We are moving away from a time when merchandising was driven by instinct, experience and intuition, which provided merchandisers with the ability to spot trends, predict demand and decide what customers might want before the data caught up.

This is because, in the age of AI commerce, merchandising has gone beyond selection to the need to understand which attributes, claims, specifications and product experiences actually drive conversion, discovery and loyalty. Merchandising is therefore becoming more about information science rather than gut instinct.

This is down to a profound change in how products are discovered and evaluated. In traditional commerce, merchants could rely on visual merchandising, brand equity or paid placement to influence purchasing decisions. But as commerce moves from search to discovery, and as AI increasingly controls the buying journey, product data itself becomes the product experience.

Whether a human or a machine is doing the browsing, products are now being parsed, filtered, summarised and recommended based on the quality and structure of the underlying data. In this environment, merchants are shaping the information architecture that determines whether products are surfaced, trusted and bought, and this has created a major shift in how merchandising decisions are made.

Historically, merchants generally relied on broad category performance, supplier relationships and market intuition, but AI-driven commerce introduces a much more granular level of visibility. Retailers can now analyse which specific product attributes increase conversion, which sustainability claims influence basket behaviour, which content reduces returns and which combinations of information drive high margin purchases.

Merchandisers still need to know which products sell but more importantly yhy do they sell. For example, does a product convert because of a technical specification, a sustainability certification, richer compatibility information, a delivery promise or a clearer explanation of use cases? Which product descriptions reduce returns? Which imagery increases confidence? Which attributes matter most to AI discovery engines? These are fundamentally different merchandising questions.

Merchandising therefore changes from being a static record of performance into continuous product intelligence. As a result, many retailers and brands run into organisational barriers as most product data environments were never designed to support this level of adaptability or feedback. Product information often remains fragmented across spreadsheets, disconnected systems and manually maintained workflows. Teams then spend enormous amounts of time correcting and redistributing data instead of learning from it. The result is that merchants frequently lack the visibility needed to understand how product information itself influences commercial performance.

This leads to a gap between product performance and product intelligence. Businesses may know what sold yesterday, but not which product attributes, content structures or enrichment strategies are driving tomorrow’s discoverability. This is why product data is rapidly evolving from a back-office operational function into the strategic engine of modern commerce.

At Akeneo, we increasingly see businesses shifting from static product catalogues toward adaptive product intelligence systems that continuously learn from market signals. This requires a connection between performance data, AI discovery trends, search behaviour and channel feedback, all fed directly back into the product record itself from where it can be continuously optimised.

That fundamentally changes the role of merchandising teams. Rather than manual catalogue management, merchants become strategic orchestrators, and instead of spending time fixing data inconsistencies or chasing suppliers for missing information, they can focus on interpreting patterns, identifying performance drivers and shaping richer product experiences.

They will have to understand which attributes improve AI discoverability, which claims influence conversion in different regions, or which product combinations reduce customer uncertainty and returns. Let’s call them product intelligence strategists.

Importantly, this does not eliminate the value of human judgment. Intuition, creativity and an understanding of consumer behaviour still matter. But instinct alone is no longer sufficient in a commerce environment shaped by AI-driven discovery and infinite buyer intent.

The imperative to make these changes are the changing economics of commerce. Rising acquisition costs, growing return rates and increasing competition mean that every product interaction matters more than ever. Poor product information directly impacts discoverability, conversion, trust and profitability.

Once this new approach is in place. merchandising can be measured in entirely new ways. Retailers can begin to quantify which product enrichments increase conversion, which data gaps cause abandonment and which inconsistencies create returns or distrust. Product data evolves from static content into a dynamic commercial asset that can be continuously tested, refined and improved.

The era of intuitive merchandising is being supplemented, and increasingly challenged, by a world where product performance can be analysed at the attribute level, where AI agents act as a gatekeeper to discovery and where the quality of product intelligence determines commercial visibility.

About Akeneo

Akeneo is the product experience (PX) company and global leader in Product Information Management (PIM); creating a world where every product interaction is an experience that guides consumers and professionals to the best purchase, anytime, anywhere. Akeneo empowers business leaders with software, education, and an engaged community all focused on the practice of product experience management.

Leading global brands, manufacturers, distributors, and retailers, including Chico’s, TaylorMade Golf, Rail Europe, Kering, and more trust Akeneo to scale and customize their omnichannel commerce initiatives. Using Akeneo’s intelligent Product Cloud, companies can create elevated product experiences with user-friendly and AI-powered product data enrichment, management, syndication, and supplier data onboarding; as well as a comprehensive app marketplace and partner network to meet business and buyer needs. For more information: www.akeneo.com