4-Tell Announces Major Enhancements To Boost® Recommendations Engine
Advanced Features Help Online Retailers Drive Sales, Profitability
Portland, OR (PRWEB) November 05, 2012
4-Tell today announced the release of a broad range of enhancements to its Boost® Recommendations Engine. With nine new features, it offers online retailers an entirely new level of flexibility and control in using dynamically personalized product recommendations to convert browsers into buyers.
“We are continually developing new tools and products to help retailers of all sizes optimize their online stores,” says Neil Lofgren, VP of Engineering. “Adding these new features helps increase conversion while providing a more engaging shopping experience at a compelling price point.”
The nine new features announced by 4-Tell include:
- Filters: Facilitates the ability to set up product groups with business rules that filter viewing of recommendations by brand, category, or gender. For example, if a shopper is looking at products for Women, Men's products can be blocked from appearing in recommendations. In addition, for retailers that sell parts, items are only recommended when they fit the viewed product. Fully automated, filters will be updated when a product is added, deleted or out of stock from the product catalog.
- Recently Viewed: Allows real-time viewing of a shopper's current session on a site. Boost® automatically customizes product recommendations with every click a customer makes while browsing, delivering a truly personalized shopping experience.
4-Tell's next generation technology offers flat-fee pricing, easy integration across all ecommerce platforms, and same day recommendations that dynamically begin personalizing product offerings with each click a shopper makes.
4-Tell is an ecommerce software company that increases sales for retailers with personalized cross-sell and up-sell. 4-Tell's product recommendations provide a more engaging shopping experience. Its Boost® Recommendations Engine delivers the next generation technology for true cross-channel personalization, working seamlessly across web, e-mail, mobile and in-store to automatically recommending products that online shoppers are likely to buy.
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