Personalize your entire site

Product recommendations on product details pages are only the beginning. Our system knows how to deliver over 20 types of personalized product recommendations across different page types. Top sellers, recommendations based on search engine keywords, similar items, cross-sell and up-sell can be presented on category, search results, shopping cart, product and even the homepage. With our zero integration technology personalized product recommendations can be automatically injected to the entire site without any resources from your IT/Design team.

Customization

We will customize the product recommendations to match your website's look & feel including colors, layout and more. Here are some examples of Barilliance recommendations embedded in customer websites:

Zero integration effort

Integration is done by simply adding a couple of javascript lines and takes a few minutes. We do not require any interface to your data. You have no risk, no commitment and no investment.

Email personalization

Instead of sending the same emails to all customers, use our API to send customers personalized product offers based on their favorite categories or brands, items they purchased, viewed, abandoned in their shopping cart and more.

Unmatched ROI

Thanks to our advanced Zero Integration technology, our costs of adding customers and supporting them are much lower than any competitor. Therefore we can offer the service at a very affordable price, which is marginal compared to the expected increase in revenues.

Advanced product recommendations algorithms

The product recommendation engine keeps track of every activity shoppers perform on your site - from the products they looked at, added to cart and purchased, to their favorite categories. It gathers this individualized information over time and builds a rich consumer profile. This profile combined with other shoppers' activity is the basis for the product recommendations that are presented to shoppers.

Our system responds to shoppers' activity in real time. For example if a shopper lands on the site's electronics category we would display top items in that category. However if the shopper will look at digital cameras and will come back to the category page, we will present relevant digital cameras as opposed to general top sellers.

The recommendation engine is also semantically aware:it understands the specific semantics of your site. For example, if a shopper is looking often at discounted products or the promotions category the engine will label the shopper as price sensitive. This information will be used by the product recommendations engine to promote similar products at the same price point.