Product recommendations

What are product recommendations?

The product recommendation system analyzes website traffic and suggests new products, services or content to e-consumers. They may relate to a product in their online shopping cart. For example, a customer buying shoes online could be offered a shoe polish. An ideal product recommendation system would suggest products that are maximally tailored to the site visitor's needs, expectations, and interests. 

There are two primary functions of the product recommendation engine:

• Analyzing the behavior of visitors. Data such as site pages visited, time spent on the site, purchase history, terms searched, and so on are considered. 
• Displaying recommendations based on previously analyzed data. 

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Modern product recommendation engines, for example, use machine learning to show the customer products that are more likely to interest them rather than random items. 

Such engines can be found in streaming services like Netflix or HBO Max, social media like TikTok or online stores like Alibaba, Amazon. Today, about 71% of e-commerce sites already offer product recommendations. This figure is even higher in Scandinavian countries, where it can reach 90%.

Types of product recommendations

There are three basic types of such systems:

1. Content-based It displays similar products based on what the user is searching for, browsing, or has previously purchased. 
2. Collaborative They function by recommending products which is done after collecting and analyzing data about how site visitors with similar profiles use the site.
3. Hybrid systems – these combine the first two models and display product recommendations based on both user actions and similar behavior. 

Typical product recommendations are:

• Recommendations for related products: this is a list of items from the same or related category. They are similar to the one selected by the customer and the system picks them based on, for example, the same manufacturer, application, size, etc. 
• Recommendations based on previous purchases. A product recommendation system lets you suggest things like lenses to a customer who has bought a digital camera from your online store before. 
• Search-based recommendations. Product recommendation engines can review search history to suggest items based on keywords used by consumers.
• Recommendations based on popularity. In such a recommendation system model, the customer will see the products that are most popular among buyers in a given category.
• Recommendations based on what others have bought/viewed. In this case, the system will suggest items to the person who is browsing based on what other customers have bought. 

What does this look like from the customer's perspective? The suggested items can be displayed to the customer in different places on the site and at various stages of the purchase procedure. The customer is presented with a list of products, each of which is accompanied by a headline such as: 

• Customers who viewed this product also viewed,
• Recently viewed,
• Buy together with,
• The most popular in this category,
• Users who bought this product also bought.

Recommendations in an online store – where do they appear? 

Customers decide to complete their shopping carts at different times. Therefore, there is no single ideal place for product recommendations. It's important to have recommendations pop up frequently, but you don't want to overwhelm customers with them. If intrusive messages pop up everywhere, customers may get annoyed and decide to shop elsewhere. In what places on the site do product recommendations most often appear? These include:

• home page
• category pages
• product tabs
• shopping cart section
• order summary
• “thank you for your purchase” page  

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Product recommendations vs. customer segments

It's obvious that a new user to a store will see a different set of recommendations than a returning customer. Therefore, the product recommendation system, i.e. what a user sees and where they see it, should take into account various user personas. Such separate segments can be, for example:

• New customers. First-time visitors to your store can see recommendations for the most popular or best-rated products. 
• Returning customers. Customers who have been to the store before can see suggestions, such as similar items or items that other customers have also bought. 
• Customers who often take advantage of discounts or promotions. In this case, it’s worth displaying to customers recommendations for the most popular items that are on promotion. 

Shopping recommendation system. Advantages

Wondering what advantages a product recommendation system has? 

• Greater personalization. There is no doubt that e-commerce is moving toward maximum personalization. With the right configuration of your product recommendation system, you can start creating intelligent prompts for a better shopping experience. 
• Increased conversions. Research shows that shoppers who click on recommended products are 4.5 times more likely to add them to their shopping cart and complete the purchase. The same company reports that 24% of orders and 26% of revenue come specifically from product recommendations. 
• Higher engagement. Even shoppers who clicked on a recommended product but didn't buy anything had higher engagement rates. These customers were 20% more likely to revisit the site.
• Knowledge of customer behavior. Product recommendation systems most often offer access to statistics on site traffic and customer behavior. With this data, you can improve your store's offerings as well as the site itself.

If we consider the online customer's point of view, what benefits do product recommendation systems offer? 

• Better shopping experience. A customer visiting an online store can more easily find products of interest,
• Time saving. With personalized recommendations, the user doesn’t have to waste time searching for products,
•  Discovering new products. The user learns about new brands or similar products. 

Shopping recommendation system – summary

A shopping recommendation system plays an important role in the success of your e-commerce business. Popular search engines facilitate customers' ability to find products online but provide no guidance when it comes to settling on a final purchase. This is where e-commerce product recommendation engines come in. If you are looking to increase sales in your online store, write to us here and now - we can select for you some e-commerce experts - freelancers.