Product recommendations are a proven way to support visitors in their selection process while increasing order value. By cleverly capitalizing on behavior and interest, you can show personalized suggestions tailored to what is relevant to that visitor at that moment. Think of alternatives for a viewed product, matching items to items in the shopping cart or previously viewed products during a return visit.
Relevant suggestions based on behavior and context
Recommendations can be based on various data points, such as click behavior, profile information, previous purchases or popularity. By combining this data with current product information from a shopping feed, for example, recommendations can be built automatically and in real-time.
Many common applications:
Previously viewed / recently viewed products - Helps returning visitors quickly resume their orientation.
Popular Items or Recipes - Shows what others often view or buy within the same context.
Others Also Viewed / Others Also Bought - Based on collective behavior of other users with similar browsing behavior.
Recommendations can be presented on product pages, category listings, the homepage, or via dynamic components such as slide-ins.
Alternatives and matching items
In addition to displaying targeted products, the module can be used for:
Additional to direct recommendations, alternative or matching products can be shown, for example:
When a visitor views a specific item, similar products that others found interesting can be shown.
When a product is added to the cart, additional or complementary products can be suggested, up to a preset amount.
Examples of labels commonly used for this purpose:
Pick up now or checkout items at checkout - targeting impulse purchases.
Additional items - such as accessories or related services.
These applications are suitable for increasing order value without overcharging the user during the purchase process.
Return visit retention
When visitors revisit the website, displaying previously viewed products or interests provides leads for redirection. In addition, recommendations based on the shopping cart or behavior during previous sessions can contribute to re-activation or the subsequent completion of a purchase.
Examples:
Exit shopping cart at exit-intent - Show the contents of the cart before a user is about to leave.
Popular items within previously viewed categories - If the basket is empty, this allows relevant offerings to still be presented.
Flexibility in logic and presentation
Recommendations can be fully tailored to the specific target, time or channel. Tools like WiQhit offer the ability to drive this logic through custom queries, allowing, for example:
Only items under a certain amount are shown,
Offers products with a certain inventory status are excluded,
Or that different recommendation rules apply depending on the funnel stage.
The presentation is also flexible: recommendations can be integrated in-page (e.g., in product views), as part of a overview block, or as slide-in based on behavior (such as scroll, idle time or exit-intent).
Summary
Product recommendations contribute to both ease of use and commercial goals. Smart use of data and context allows you to make suggestions at relevant times that match the user's needs. The combination of behavior, current product data and flexible presentation options makes recommendations a powerful tool within personalized online interactions.
