Recommending a product is much more than just displaying a list of related items. It's about providing suggestions that are truly relevant to each visitor, at the right time and in the right place. But what do we mean by relevance?
In the context of e-commerce, a relevant recommendation is based on several dimensions: it must be contextual, i.e. in line with the current purchase path (browsing, history, shopping basket), while taking into account of the user's specific preferences and expectations. It is not simply a matter of highlighting best-sellers or popular products, but a fine-tuned, individualized approach that anticipates needs and encourages engagement.
In this sense, personalized recommendation is not just a technical function: it is a true strategic lever for e-merchandising. Whether the objective is to increase conversion, improve the customer experience or strengthen customer loyalty, personalized recommendations meet specific objectives that have a direct impact on sales performance. Let's take a closer look.
The key objectives of personalized recommendations
Maximize conversion
One of the primary objectives of product recommendation is to optimize conversion, by facilitating the transition to purchase at each stage of the customer journey.
- In the same session: offering relevant alternatives can make all the difference. More and more often, a visitor comes directly to a product page via SEO, SEA or Google Shopping. But if they're not convinced by the item they're looking at, they're likely to leave the site. Recommendations help to avoid this pitfall by suggesting similar products. Rather than leaving the user at a dead end, we immediately show them other suitable options, thereby maximizing the chances of conversion.
- On a multi-session ‘journey’: recommendations are based on the browsing history to extend the experience over the course of multiple visits. Right from the home page, a customer returns and finds suggestions in line with their previous searches. ‘I've understood what you're looking for, here are some products that might interest you’. This personalized approach smoothes the buying journey and maintains engagement, increasing the chances of conversion over time.
Increasing the average basket
Personalized recommendations also play a key role in increasing the average basket by encouraging the purchase of complementary or additional products.
- Cross-selling: this is one of the fundamentals of e-merchandising. On a product sheet or in the shopping basket, offering complementary items helps to optimize each order. A customer buys a smartphone? Suggesting a suitable case or headphones will naturally increase the value of the basket while meeting a need.
- The "next product to buy": some recommendations are aimed not just at completing an immediate purchase, but also at anticipating future needs. By analyzing purchase behavior, we can suggest products that are a continuation of those already consulted or purchased. Has a customer just bought a coffee machine? Chances are he'll need pods soon.
Increase margins
Personalized recommendations are also a strategic lever for improving margins, by influencing consumer choices toward more profitable products.
- Upselling: offering a premium version or a more powerful model on a product sheet can steer shoppers toward a product with greater value. For example, a customer interested in an entry-level smartphone might be offered a slightly more expensive model, but with better functionality. If the suggestion is relevant and well put together, it will naturally increase the value of the order while boosting customer satisfaction.
- Substitution: when a product is out of stock or less attractive in terms of margin, suggesting a more profitable alternative is an effective approach. On a product sheet or in the shopping basket, the recommendation can direct the buyer towards a private label or a similar item offering better margins. ‘Looking for that branded product? Why not try our private label, which tastes just as good and is better for your budget? It's a win-win strategy that reconciles purchasing power and margin optimization, while giving consumers a choice.
Strengthen customer loyalty
A returning customer is a conquered customer. And personalized recommendations play a key role in this dynamic, by facilitating repeat purchases and anticipating needs.
- Simplifying replenishment: in the world of consumables, recommendations are the natural way to help customers with their recurring purchases. Amazon excels at this: by analyzing buying habits, the platform knows when to offer a new ink cartridge or pack of coffee, at just the right moment. In e-commerce, this approach captures repeat business and prevents buyers from looking elsewhere for what they need.
- Anticipating future needs: as interactions progress, the recommendation process refines its understanding of the customer expectations. After the purchase of an electrical appliance, suggesting compatible accessories or spare parts at the right time encourages repeat purchases and strengthens the relationship with the brand. This attention to consumer habits creates a fluid and effective experience that naturally encourages customers to return.
Don't miss our article: The importance of product recommendations for personalizing your e-commerce site
Measuring the impact of recommendations
The effectiveness of recommendations cannot be measured solely in terms of directly attributable sales. In reality, very few shoppers discover a product via a recommendation without first going through a search result or a list page - between 5% and 15% of them, depending on the context. Strictly attributing sales to recommendations is therefore biased reasoning, especially as their role is not limited to immediate conversion.
The key indicator is sales influenced: how many purchases were made after interacting with a recommendation? It's not simply a question of the presence of a ‘You'll like it too’ block, but of relevance. An effective recommendation doesn't just fill a space: it adapts to the buyer's profile and context, maximizing its impact.
The numbers speak for themselves. Amazon, a pioneer in this field, attributes 35% of its sales to recommendations [1]. According to McKinsey, personalized suggestions can increase the conversion rates by 10-15% [2]. And almost half of consumers admit that they have already made an impulse purchase thanks to a well thought-out recommendation [3].
In other words, recommending a product is not just about displaying suggestions. Properly leveraged, recommendations can be a powerful lever to guide shoppers' choices and optimize sales performance. But they still need to be mastered.
The keys to success
For a recommendation strategy to be successful, a number of elements need to be mastered.
Always offer highly personalized recommendations
The aim is not to recommend just any product to just anyone, but to precisely target the needs of each user. Each recommendation must be contextualized and adapted to the consumer's specific preferences and expectations. If recommendations lack personalization, they risk not only losing effectiveness, but also damaging the user experience, resulting in a drop in sales performance. The challenge is to ensure that each suggestion is relevant, thoughtful, and addresses an immediate or latent need.
Define visible recommendation zones
Multiplying the number of recommendation zones on a site is pointless if they are not well placed. The aim is to make them visible where the user is likely to see them, taking into account factors such as fold or Z-reading. The key lies in relevance and visibility: an effective recommendation must not get lost in a sea of content. Far from being a mere decoration, the recommendation zone must be strategically positioned to maximize its impact and not just fill the visual space of the site.
Define a clear strategy for each recommendation zone
Before implementing a recommendation zone, it's essential to have a clear strategy in mind. Each zone can serve different purposes: generating more shopping baskets, increasing margins or boosting conversions. The key to success lies in being clear about the objective behind each recommendation. Too often, e-tailers implement recommendations without measuring their effectiveness or clearly defining what they are trying to achieve. A successful recommendation is based on a clear understanding of the objective to be achieved and how each zone will contribute to this objective.
Ability to easily cover your entire catalogue
The ability to cover your entire product catalog is essential if recommendations are to be truly effective. This is where artificial intelligence plays a key role. Recommendation systems have been around for a long time, but it's crucial to have advanced technology that can automatically manage and analyze all of your products. This makes it possible to provide relevant recommendations without the need for constant manual adjustments, ensuring smooth, scalable management of your catalog, regardless of its size.
Use offline data to optimize recommendations
It is essential to integrate offline data into your recommendation strategies. In many sectors, online conversion rates can be relatively low, and ignoring in-store purchases can lead to irrelevant recommendations. To avoid abnormal results and ensure that your recommendation system is truly effective, it needs to be able to train on data from offline sales. This will give you a better understanding of overall buying habits and enable you to make more accurate suggestions that are tailored to actual consumer behavior.
Using business rules to constrain AI
Artificial intelligence offers great flexibility, but it's also important to be able to guide it with business rules to maximize results. For example, you can define specific rules to encourage up-selling, such as displaying similar products but with a higher margin. However, these rules need to be applied in a strategic and measured way. If there are too many of them, it can quickly become time-consuming and detract from the effectiveness of the system. The challenge is to find the right balance between AI automation and the use of business rules to maximize the relevance of recommendations.
Take your business strategies into account
A good recommendation system must be aligned with your overall business strategies. Rather than imposing ad hoc guidelines, such as highlighting a specific brand or category, it is crucial to define a coherent strategy for search, ranking and recommendation. Once this strategy is in place, the system will be able to integrate it seamlessly and offer relevant recommendations in line with your business objectives. This maximizes the impact of recommendations while respecting your strategic priorities.
Measure, measure, measure
Ongoing measurement is essential to optimize your recommendations. Every action and every interaction must be monitored and analyzed so that recommendations can be adjusted in line with performance. This optimization process should never be left to one side, as it maximizes the impact of your strategy over the long term. The continuous improvement of recommendations is based on regular evaluation of results and adjustments based on the data collected.
Personalized product recommendations are no longer a simple asset, but a real strategic lever for e-tailers. By transforming every customer interaction into an opportunity for conversion, loyalty and increased margins, they enable multiple and complementary goals to be achieved. However, to maximize their effectiveness, it is essential to focus on relevance, define strategic recommendation zones and implement continuous measurement. By adopting a methodical and personalized approach, e-merchandisers can transform the customer experience and optimize their sales performance at every stage of the buying journey.
Find out more about e-merchandising levers: An introductory guide to e-merchandising
At Sensefuel, we've developed a solution that goes beyond traditional recommendations to enable you to fully exploit this strategic lever. Our Deep Learning technology analyses each interaction to make increasingly relevant suggestions that are in line with your sales objectives. Thanks to a dedicated cockpit, you keep control of all your e-merchandising: optimized search engine, dynamic recommendations, product ranking management and sales promotion. A single tool to streamline your ecommerce stack and improve performance.
[1] Moengage
[2] Mc Kinsey
[3] Survey of product search habits on e-commerce websites, Sensefuel, 2025 edition