Product recommendations are a proven way to support them in their decision-making process and at the same time increase the order value. By intelligently responding to behavior and interests, you can display personalized suggestions tailored to what’s relevant to that visitor at that moment. Think of alternatives to a viewed product, matching items for those 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 up-to-date product information from, for example, a shopping feed, recommendations can be generated automatically and in real time.
Common applications:
Previously Viewed / Recently Viewed Products – Helps returning visitors quickly get their bearings again.
Popular Articles or Recipes – Show what others often view or buy in the same context.
Others also viewed / Others also bought – Based on the collective behavior of other users with similar browsing habits.
Recommendations can be displayed on product pages, category overviews, the homepage, or through dynamic components such as slide-ins.
Alternatives and Related Items
In addition to displaying targeted products, the module can be used for:
In addition to direct recommendations, alternative or complementary products can also be displayed, for example:
When a visitor views a specific item, similar products that others found interesting can be displayed.
When a product is added to the shopping cart, additional or complementary products may be suggested, up to a preset amount.
Examples of labels that are often used for this purpose:
Grab them now or check out the checkout specials—designed to encourage impulse purchases.
Related items—such as accessories or related services.
These applications are designed to increase the order value without overwhelming the user during the purchasing process.
Retention on Return Visits
When visitors return to the website, displaying products they’ve viewed before or items related to their interests provides a starting point for re-engagement. In addition, recommendations based on the shopping cart or behavior during previous sessions can help reactivate visitors or encourage them to complete a purchase.
Examples:
Abandoned shopping cart upon exit intent – Display the contents of the cart before a user is about to leave.
Popular Articles in Previously Viewed Categories – If the shopping cart is empty, this approach still allows relevant offers to be presented.
Flexibility in Logic and Presentation
Recommendations can be fully tailored to the specific goal, timing, or channel. Tools such as WiQhit allow you to control this logic using custom queries, which makes it possible, for example, to:
Only items below a certain amount are displayed,
Products with a specific inventory status are excluded,
Or that different recommendation rules apply depending on the funnel stage.
The presentation is also flexible: recommendations can in-page be integrated (e.g., into product overviews) as part of a summary block, or if slide-in based on behavior (such as scrolling, idle time, or exit intent).
In summary
Product recommendations contribute to both user convenience and commercial goals. By making smart use of data and context, you can make suggestions at relevant moments that align with the user’s needs. The combination of user behavior, up-to-date product data, and flexible presentation options makes recommendations a powerful tool in personalized online interactions.
