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In the past panel discussions, we've covered topics ranging from game commerce to couponing to keyword/content discovery. Now our attention turns to recommendation engine and brand commerce. A recommendation engine is a staple of e-commerce systems which suggests products that a user might like based on past transactions and the transactions of users with a similar purchasing style. Articles have suggested that recommendation engines can add up to 8-10% in incremental revenues. We want to explore how these engines are evolving in light of new e-commerce trends. Algorithms: Sites, such as Amazon, have use collaborative filtering techniques to power their systems.

-Is it still king or are we moving towards newer techniques?
-How are the performance of the engines being measured?
-How are emerging recommendation systems describing, weighting and assigning lifetimes to data independence / randomness, integrity, consistency, reliability, completeness, context, frequency, recency, accuracy, bots, etc Channels: Users are increasingly mobile and social.
-How do recommendation systems adapt to the type of channel that a consumer uses?

Branding: Recommendation engines have typically catered to the interest of the consumer. Can it be used to improve a company's brand? How do you categorize different brands - e.g. by type of goods and services, customers, channels, ad budget, financial markets, web presence, web traffic, web engagement, store presence, etc. Are there different recommendation styles based on the type of brand? What are some of the best practices when it comes to deploying a recommendation engine? What are the pros and cons of joining an e-commerce network such as an Amazon marketplace.

Official Website: http://www.svforum.org/index.cfm?fuseaction=Calendar.eventDetail&eventID=14095

Added by FullCalendar on August 16, 2012

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