Loomia is one of a number of fast-moving companies in the ultra-hot marketing technology sector known variously as Optimization and/or Personalization. The companies in this complex sector have differing approaches and technologies, but the concept is to analyze traffic and user behavior on your Web site and to use the data as a real-time input for dynamically tuning the content on your site to better serve and retain users. There are a number of tangents and angles off this central concept that different companies specialize in. Loomia’s specialty is providing product and content recommendations based on both explicit user preferences like ratings and implicit preferences based on where users go on your site, what they spend time on, and what they buy.

Loomia has a great graphic on their site that demonstrates their process, which they’ve given permission for me to post here to better explain what they do.

This space is continuing to heat up due to the effectiveness of optimization technology for tuning content to help user find things they want. It relies on the “wisdom of the crowds” to understand what people are interested in and to constantly tune content accoringly, rather than relying on the subjective opinion of an expert or editor which can only be updated in time-consuming content management cycles. Many companies are claiming substantial increases in time-on-site, conversions and close rates for online sales by using optimization, personalization and recommendations technology. Loomia claims an algorithm advantage over competitors like Aggregate Knowledge and Baynote by being able to drive personalization and optimization on a much smaller sampling of data, meaning faster time to relevant recommendations for users.

The big win announced by Loomia yesterday is a deal with the Wall Street Journal to provide content recommendations for WSJ readers based on preferences of other readers.

Recommendations provided by Loomia will appear in a module next to WSJ.com articles, under the header “People Who Read This…Also Read These Stories.” These recommended articles are based on a user’s current reading as well as their past behaviors around related content on WSJ.com, such as time spent or printing an article. These behaviors are matched against other users who share similar interests, generating article suggestions that are more relevant and personalized.   

The full release is available on Loomia’s press page.