Generating Revenue with Product Recommendation Engines

Recommendation engines have taken the online purchasing experience to the next level. E-commerce websites use product recommendation engines to make relevant suggestions to their shoppers. The most common examples are the “you might also like” or “other people who bought this item also bought” sections on websites. Product recommendation engines are powered by rules-based algorithms to show personalized suggestions to visitors.

What is a Product Recommendation Engine?

recommendation engine for e-commerce analyzes huge volumes of data, to make personalized suggestions to shoppers and website visitors.

A product recommendation engine is a sophisticated software tool that uses a business rules engine to manage complex algorithms in order to generate highly-relevant recommendations to customers — such as special discounts, promotions, and offers.

Factors that Influence Suggestions

Here are some of the most popular types of customer data online businesses use to recommend items to website visitors:

  • Browsing Behavior
  • Customer Reviews
  • Wish List
  • Recently Viewed Items
  • Previous Purchases
  • Session Duration

Using this information, the recommendation engine serves up relevant items to shoppers. 

Effective Recommendation Tactics

Let’s take a look at some of the most common ways companies across industries are using product recommendation engines to drive revenue.

Using Ratings and Reviews to make Recommendations

Positive customer reviews are a great way of influencing purchasing decisions.

A product recommendation tool that displays recommendations using ratings and reviews will also factor in things like the number of clicks, the session duration of each user, and viewing habits. 

Frequently Purchased Together 

A common sales strategy popularized by e-commerce brands is to show similar items on the checkout page. These types of suggestions enhance the shopping experience by showing shoppers useful suggestions that go well with their purchases.

Note that these recommendations are also effective after purchases have been made. For example, when businesses send confirmation emails, they can recommend items that complement the purchased products.

The ‘frequently bought together’ recommendations work by segmenting shoppers into groups with similar preferences and shopping habits.

Recommendation Engines Advantages

Recommendation engines boost brand awareness, revenue, and the customer experience, These are some of the most impactful advantages of deploying a product recommendation engine.

Improved Click-Through and Session Duration Rates

Unsurprisingly, highly-relevant and personalized recommendations generate much higher click-through rates than nonspecific suggestions.

Bundle Up Products

Packaging together several items is a great way of upselling or cross-selling products across different price points to drive additional revenue. For instance, when a customer adds a gaming laptop and chair to their cart, a recommendation engine can offer a discount for a high-end headset that complements the purchase. 

Average Order Value

Recommender systems offer amazing opportunities to upsell and cross-sell by showing shoppers related products that are likely to be of interest to them. 

The ‘complete the look’ suggestions are an effective way of persuading customers to turn smaller transactions into much larger ones.

Drive Revenue

Clearly, when the average value order is increased, customers are spending more per transaction, which translates into additional revenue for the business. 


Recommendation engines are built to provide an enhanced overall buying experience by using personalized recommendations for products that customers might not have come found without assistance.

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