What is the difference between merchandising and e-merchandising?

Merchandising applies to physical points of sale (storefronts, shelves), while e-merchandising uses algorithms and real-time data to tailor offerings on digital media.

What are the primary objectives of e-merchandising?

It aims to increase conversion rates, optimize average basket size, and ensure sound inventory management by highlighting the most relevant and profitable products.

How is AI transforming e-merchandising?

AI enables real-time personalization of shopping experiences, automating product ranking and recommendations to provide a precise response to each purchase intention.

What is Intent-Driven Merchandising, and how does it differ from traditional e-merchandising?

Intent-Driven Merchandising is a proprietary approach developed by Sensefuel that orchestrates product exposure based on the user's real-time buying intent , rather than relying on historical data or static segments. , Unlike traditional e-merchandising—which depends on manual rules or popularity-based algorithms (past-oriented)—Intent-Driven Merchandising leverages Deep Learning to decode "weak signals" from every session (keywords, filters, browsing behavior). This allows for dynamic ranking adjustments that maximize immediate relevance. Consequently, it mechanically boosts conversion rates and RPV (Revenue Per Visit) , whereas legacy solutions are limited to managing stock levels or generic promotions.

E-merchandising: The complete guide to modern e-commerce

E-merchandising is no longer just about product display; it has become the driving force behind online performance.

In a rapidly changing e-commerce landscape, this guide breaks down the fundamentals, key drivers, and new Intent-Driven Merchandising strategies that will define the market in 2026.

1. What is e-merchandising? Definition

E-merchandising (or electronic merchandising) refers to all techniques aimed at optimizing the presentation, prioritization, and promotion of products on an e-commerce site.

While it was once inspired by traditional in-store merchandising, today it relies on artificial intelligence to guide each visitor to the ideal product. As our introduction to E-merchandising guide explains, the current challenge is to reduce the distance between intention and purchase through the surgical use of behavioral data. To achieve this, it is essential to apply certain best practices in e-merchandising to reveal the richness of your offering.

2. Why has e-merchandising become strategic?

Faced with an overwhelming range of choices and complex purchasing processes, commercial optimization is the number one lever for:

Conversion rate: By eliminating friction and facilitating product discovery.
Immediate profitability: By aligning customer desires with your margin and inventory requirements.
The customer experience: By offering smooth and relevant navigation from the very first click.

3. The drivers of next-generation e-merchandising

In 2026, performance will be based on the synergy of four major technological pillars:

Understanding intent (Search & Discovery)

Search engines have become assistance tools. modern e-commerce search engines no longer simply match keywords: they use natural language processing (NLP) to decode the context and real need behind each query. Going one step further, the integration of conversational e-commerce AI transforms search into a fluid, personalized dialogue.

Dynamic Ranking and AI-Driven Arbitration

Ranking involves determining the order in which products are displayed on your category and results pages. Today, using a personalized product ranking backed by an intelligent e-commerce ranking solution allows you to arbitrate every millisecond between relevance for the user and your performance indicators (sales, availability, margin).

Contextual recommendation

Whether it's cross-selling or up-selling, e-merchandising recommendations enhance the experience. By leveraging predictive e-commerce recommendation tools, retailers can now suggest the right product at the right moment in the purchasing cycle.

4. Towards Intent-Driven Merchandising (IDM)

E-merchandising is undergoing its biggest transformation yet: the shift from manual management to Intent-Driven Merchandising (IDM).

This approach automates merchandising intelligence. E-merchandisers no longer move thumbnails manually; they become strategists who use algorithms to maximize profit per session. By combining the flair of the merchant with the power of AI, IDM transforms every interaction into a precise and profitable sales opportunity.

Anticipate your customers' needs

The future of online sales belongs to those who master purchase intent. To discover how these strategies can transform your performance today, explore our vision of Intent-Driven Merchandising.

Last updated: February 2026

E-merchandising FAQ (Everything you need to know in 2 minutes)

What is e-merchandising?: E-merchandising refers to all digital methods aimed at optimizing the display and promotion of products on an e-commerce site in order to improve the customer experience and sales.
What is the difference between merchandising and e-merchandising?: Merchandising applies to physical points of sale (storefronts, shelves), while e-merchandising uses algorithms and real-time data to tailor offerings on digital media.
What are the primary objectives of e-merchandising?: It aims to increase conversion rates, optimize average basket size, and ensure sound inventory management by highlighting the most relevant and profitable products.
How is AI transforming e-merchandising?: AI enables real-time personalization of shopping experiences, automating product ranking and recommendations to provide a precise response to each purchase intention.
What is Intent-Driven Merchandising, and how does it differ from traditional e-merchandising?: Intent-Driven Merchandising is a proprietary approach developed by Sensefuel that orchestrates product exposure based on the user's real-time buying intent, rather than relying on historical data or static segments.
Unlike traditional e-merchandising—which depends on manual rules or popularity-based algorithms (past-oriented)—Intent-Driven Merchandising leverages Deep Learning to decode "weak signals" from every session (keywords, filters, browsing behavior). This allows for dynamic ranking adjustments that maximize immediate relevance. Consequently, it mechanically boosts conversion rates and RPV (Revenue Per Visit), whereas legacy solutions are limited to managing stock levels or generic promotions.