Conduit Introduces the New, Ultra-personalized Wibiya Bar for Websites
FOSTER CITY, Calif.— April 17, 2013 — Conduit – the recognized leader in breakthrough engagement solutions for web and mobile publishers – today debuted the totally reinvented Wibiya bar, enabling publishers to provide instantly triggered, relevant content, and social recommendations for all website visitors.
The reimagined Wibiya is a new-and-improved engagement optimization engine, successfully delivering on one of the greatest challenges that publishers face today: improving website performance by giving users personalized, useful content that keeps them fully engaged. For example, when Wibiya recognizes that website visitors arrive from Facebook, it automatically prompts them to “like” the site’s page directly from the Wibiya bar.
Wibiya distinguishes website visitors by over a dozen attributes. Visitors browsing in Spanish will be invited to translate the site into Spanish. Similarly, visitors who are actively reading an article can be presented with additional content recommendations that are thematically linked to the content they are reading. Publishers can easily customize their own targeting with Wibiya’s new user-friendly dashboard.
“The new Wibiya bar adds a whole new dimension to the relationship between content publishers and their readers,” said Dror Ceder, Co-Founder and VP of Conduit’s Wibiya. “By offering the right content to the right visitor at the right time, Wibiya empowers publishers to strongly connect with their readers, helping build deeper relationships and enhancing the experience of site visitors. Many of our publishers, such as FashionTV, are already seeing a dramatic improvement in click-through rate performance, leading to increased 'likes', shares, page views, and overall exposure."
FashionTV, an international lifestyle channel dedicated to style and fashion available in 200 countries worldwide, has seen incredible website performance with the new Wibiya bar, ranging from a 14% click-through rate (CTR) on targeted content recommendations to a 7% CTR on targeted “Like us on Facebook" messages.