Advanced Recommendation Engine for Successful Online Media and Commerce

Whether your online users are worldwide eCommerce customers seeking to buy products or content, or global knowledge workers in your organization seeking enterprise information, recommending relevant content they might never have thought to look for on their own will significantly increase profitability, productivity and overall success.

Attivio's Active Intelligence Engine® (AIE®) Behavioral Analytics automatically provide relevant, individualized recommendations of products, content, etc., based historical activity data and identification of buying or viewing patterns.

Maximize Media and Commerce Conversion Rates and Profitability

Recommendations are most frequently associated with online media and commerce, and for very good reason: timely, contextual recommendations have been proven to increase conversion rates, average revenue per user (ARPU), number of items per order and other key eCommerce metrics.

Each page view that does not result in a purchase reduces the overall chance of conversion, so it is vital that you help potential buyers find something interesting as quickly as possible. Recommendations are essential to transition hit-or-miss site visits into focused, interesting shopping experiences.

AIE Behavioral Analytics evaluates customer browsing history and identifies items that others who followed a similar path ultimately purchased. The engine also identifies product alternatives as well as bundling opportunities, suggesting other items that were also purchased by others. You can also use recommendations for follow-up offers after a purchase is made, or show recommendations at the moment of purchase.

Offer Recommendations Based on Multiple Criteria

AIE Behavioral Analytics can also compare text descriptions and help identify relationships between content using metadata, topics, genres, concepts or entities, such as the names of people, locations or organizations. You can present these relationships to users in a variety of ways to achieve the best possible user experience.

For example, for a catalog of movies, you could, for each movie, recommend other movies of the same genre; movies featuring the same actor; movies with linguistically or conceptually similar descriptions, etc.

Expedite Information Discovery and Productivity

The benefits of AIE Behavioral Analytics extend to other business scenarios for which a customer purchase is not the objective. Any end user navigating and exploring enterprise information will benefit from automatic recommendations for useful content, based on their online activity.

For example, knowledge workers selecting a given research report could be presented with recommendations for additional documents that cover the same companies, industries, trends or technologies; are written by the same author or team; etc.

Additionally, AIE Behavioral Analytics can generate recommendations based on historical viewing habits of co-workers for enterprise information. For example, knowledge workers can be presented with recommendations for the best article, document, etc., based on a certain starting point or query term. Highly relevant recommendations offered during a knowledge worker's search for enterprise information can provide significantly improved productivity, similar to a dedicated research assistant.