for purchases, when a
recommendation is clicked
for shoppers clicking on
A comprehensive library of recommendation types surfaces relevant products targeting user, context, and place on-site/app. Shopper-based, item-based, content-similarity-based, and contextual popularity-based recommendation types are all part of Relewise.
Customers expect a uniform personalized experience in all interactions – Relewise delivers exactly that. The Relewise architecture makes it easy to integrate into any channel web, POS systems, digital marketing channels, etc.
A rules-based merchandising center allows business users to boost or bury products in personal recommendations. I.e., boost products to clear inventory or guide shoppers toward high-margin products and bury out-of-stock products
Content plays an important part in the customer journey as landing pages, research material, inspiration, reassurance, etc. Relewise supports all content recommendation types both content-to-content and between content and products.
Built on MACH principles, Relewise integrates with every e-commerce platform, personalizing product recommendations, product and content search, category listings, newsletters, etc. On top of that, our engine is lightning fast. In fact, we are confident we are the fastest engine out there, with an average server response time of less than 0.002 seconds! From the first to the last request, no caching is involved!