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What to look for in a product recommendations engine

Jessica Farelly
By Jessica Farrelly

An effective product recommendations engine can improve a user’s experience on your ecommerce site, and ultimately help increase sales. 

Simply put, a product recommendations engine is an intelligent tool that uses shopper behavior and data to surface personalized recommendations to a visitor based on certain factors. 

Why is this important? A 2018 Accenture Interactive study showed “83% of consumers are willing to share their data to enable a personalized experience.” This means customers want to have personalized experiences online, just as they might have in store. 

What should a product recommendations engine offer?

There is no one-size-fits-all approach to ecommerce recommendations – in fact, your product recommendation algorithm should offer control and flexibility so you can implement a strategy that makes sense for your business. Keep reading for examples of the types of recommendations you can offer on your store, where you should place them, and how to optimize them. 

product recommendations engine

Cross-sell recommendations

Promoting products that complement something a site visitor has already shown an interest in can often help increase average order value as well as improve overall user experience. 

Example: A customer views a 47” television

Cross-sell: Offering a speaker system or a 5-year extended warranty 

Up-sell recommendations

Offering customers a slightly more expensive (but perhaps better quality) product than the one they’ve just viewed. 

Example: A customer views a 47” television ($249)

Up-sell: Offering a more expensive but more robust 47” TV ($289) or a 52” TV ($339)

Similar recommendations

When a customer visits a product page, provide alternate options of products that are comparable. This can help the customer see items they may have missed which are closer to what they were originally looking for. 

Example: A customer views a 47” Sony TV

Similar recommendations: You might also like — 47” LG TV or 49” Sony TV

Trending products

Trending products feature a list of your most popular items to help shoppers get a glimpse of what’s popular and selling fast on your site. These may or may not be products in the same category as they’re viewing. 

Example: A customer views a 47” TV

Trending products: Most popular products include Amazon Fire TV, Bose speakers, etc.

Personal product recommendations

A good product recommendation algorithm is able to make suggestions based on an individual shopper’s order history or recently viewed items. This isn’t limited to the product detail page, personal recommendations can be made site-wide. 

Example: A customer purchases a 47” TV 

Personal product recommendations: Recommended for you — compatible speakers, accessories etc.

Session recommendations 

Session recommendations focus on products a customer has reviewed during their current visit, and suggest alternatives they might also like. 

Example: A customer views a 47” Sony TV

Session recommendations: Based on your “recently viewed” products — 47” Insignia TV, 52” Samsung TV, Logitech headset, Insignia headset

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Where should a product recommendations engine work on your site?

Not all recommendations need to be on the product detail pages. On the contrary, there are many different strategic locations throughout your ecommerce store where a product recommendation algorithm can help enhance your user experience. 

Home page

Using recommendations engines on your home page means being able to greet returning customers with personalized recommendations from the very start of their visit, which can set the tone for their whole experience. 

Category pages

Category pages are a great place to feature recommendations since you can highlight trending products within the categories themselves. 

Carts and checkouts

Once someone adds an item to their cart or visits the checkout page, you can provide up-sell as well as cross-sell recommendations to boost the average order value

Manage your product recommendations engine with control 

The good news is, your product recommendation engine can be controlled by you. This means you can set exclusion and attribute rules to meet your business goals, and ensure the recommended products are always relevant to the shopper. 

What is an exclusion rule? 

Exclusion rules allow you to control which items are removed from recommendations. For instance, if something is out of stock or irrelevant to the item being viewed. 

Within exclusion rules, you can specify whether they’re global exclusions (preventing all products with a specific attribute from being recommended), contextual exclusions (recommending products with the same filtered attribute as the customer was already viewing), or contextual groupings (can be triggered when a customer is viewing another item from the same group). 

What is an attribute rule? 

Well, that’s how you can boost or block which products are to be featured in recommendations based on specific features, and control the order in which they’ll appear. Attributes (or features) can be anything from color, brand, product category, etc. Again, this is so you can control the recommendations while still being in-line with your customers’ expectations. 

Using attribute rules, you can select which products in a particular category or brand to promote and/or block, as well determine the order in which these categories or brands should be promoted. 

A product recommendations engine can improve your customers’ experience

Offering personalized recommendations can help you curate hyper-relevant suggestions for your shoppers site-wide. The Accenture Insights study confirms, “91% of consumers are more likely to shop with brands who recognize, remember, and provide relevant offers and recommendations.”

Driving conversions, increasing average order value, and driving repeat purchases is at the core of these personalized recommendations. Using both intelligent automation and creative control, your ecommerce store can reap the benefits, all the while improving your customers’ experience with your online store and brand.