The recommendation engine itself is software centering on algorithms. These algorithms combine individual data with crowd data, in combination with the product data, of course, to show visitors what they’re most likely to be interested in.
Look at it this way: you have three data types — individual user data, product data, and crowd data. The engine brings these three together to produce a product recommendation that is likely to show the customer what they want to see, according to an algorithm that’s appropriate for that particular time and place in their customer journey.
For example, let’s take a typical product page recommendation, of the “Customers who viewed this also viewed” type. Here, we combine crowd data (how many viewed the products) and individual data (the customer’s top-ranked interests first), and product data (the interests associated with each product). By showing what was popular among those who viewed the same item and have similar interests, the things we show are much more likely to stoke engagement and result in a purchase.
The way these three types of data are put together to produce an effective result is via algorithms, and every product recommendation engine algorithm uses them in some way or another.
Recommendation Widget Display
All that combining data with algorithms would be pointless, if you didn’t show the end customer the resulting recommendations in a display matching the look and feel of your website. That’s where the product recommendation display widget comes in.
Display widgets are essentially HTML/CSS injected into your site with any styling you want (and no coding required). You can even tell your recommendation engine to “inherit” the CSS classes from your site, to get a head start on the right design. Widgets are usually horizontal, but can be vertical, or even shown as popups, for instance, to show a popup after someone adds an item to their cart to recommend other items that were frequently bought together with that item.
Displays can also be in email, including third-party emails using embedded email recommendations, which insert the recommendation widget into your email HTML. In some cases, you may even want to handle the display within your own CMS, and simply use the recommendation engine to inform it of which products to show, via JSON recommendations.
Displays basically take the raw product data and put it into an aesthetic interface that looks like it’s made to be part of your website (or email), according to the algorithmic magic discussed earlier. Displays can also go beyond basic functions and add extra features, such as social proof, quick-add-to-cart button, and more.
Conclusion
Product recommendation engines contibute to online stores in a way that is critical in 2022. Hopefully, this post has given a clear picture of what’s actually going on “under the hood” when showing your customers the products they want to buy using a recommendation engine.
