Personalize your e-commerce offerings based on each users taste. Convertale recommendation engine finds related products to each user in real-time, resulting in an increase of up to 15% in sales and conversion rates through up-sell and cross-sell.
Convertale analyzes each users product view, search and purchase data in order to understand what they are interested in at that very moment. Know what they are looking for even before they know it.
Your site is instantly personalized with relevant products for each user based on their current intent and past behavior. Turn your visitors into customers by providing each customer a different experience.
Providing a personalized shopping experience for your clients helps you turn your visitors into customers, resulting in increased sales and conversion up to 15%. Up-selling and cross-selling done right.
Personalize your home page for each user based on their view, purchase and search history and recommend the most relevant products.
Recommends alternative and complementary products to the visitor in a specific product page. Increase conversion rates, up-sell and cross-sell.
Analyses cart products and recommends "buy-together" items. Allowing you to cross-sell related items.
Convertale crawls your product catalog in real-time without any need for XML files. With real time catalog updates, your items are instantly removed from recommendations when they are out of stock.
Convertale is a simple, fast and real time plug and play recommendation engine for e-retailers. Convertale uses cutting edge research and innovation to deliver the most meaningful and relevant product recommendations.
Convertale's state of the art recommendation technology is a hybrid of several techniques for best accuracy and scalability.
We know that no single algorithm is perfect. We support and blend a number of techniques that best fit your requirements. We keep our recomendation engine updated with the latest from the industry and academia.
Accurate recommendation techniques require expertise and heavy computation. Our distributed computation scales perfectly under heavy usage and with large data sets.
Behavior of your users and the community is analyzed in real time to understand user and item similarities and user preferences. e.g. “We know you liked Sin City. The Movie Kill Bill was recommended to you because users who have similar behavior liked Kill Bill”.
Address: Yildiz Technical University Teknopark B2 106
Davutpaşa Istanbul Turkey
Phone: +90 212 328 02 90
Fax: +90 212 328 02 90
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