Formerly a Principal Engineer at Amazon, Darren Vengroff is Chief Scientist at RichRelevance where he helps retailers like Overstock and Sears create a more personal shopping experience for consumers. You can read more from Darren on the RichRelevance blog.
Amazon and Facebook are making headlines with the launch of a new application that allows shoppers to receive product recommendations based on Facebook preferences. Once users enables this app, Amazon is able to monitor their activity on Facebook, including what pages they likes, and use that information to recommend products they are likely to be interested in purchasing. Combining accounts with an application such as this, whether specific to Amazon or other merchants, has the potential to be a compelling hybrid of social networking and shopping that creates value for shoppers and for merchants.
While Amazon’s move made headlines because of their market position, the fact is that any merchant can build an app to allow Facebook users to share their interests. Collecting this data is the easy part. Leveraging it appropriately is where the real challenge lies. Ultimately, the success of the recommendations driven by these apps will be predicated on how relevance is extracted — particularly from the social graph — and how recommendations are presented to shoppers.