Harnessing the power of 'Like' on Facebook

Shopping is a social activity. Recognizing this, many e-commerce sites have tried to utilize online social networks like Twitter and Facebook to enhance the e-commerce experience. But how can retailers use social media to target their customers and gain valuable insights?

Most of us are familiar with the 'Like' feature on the social networking site Facebook. When a shopper chooses to Like a page on a website, Facebook also captures additional data about the shopper. Along with the click, Facebook creates a record of the link (web page or object), the user who performed the action to create the link (username), the action itself (Like), and the time of the action. This record can be retrieved from Facebook through Open Graph APIs that can reveal intelligent insights based on user activities which in turn can help address each user uniquely.

The Like feature lets people who use a retailer's web page share stories about the things they love to do—like reading, running, or cooking. These stories appear on the user's Facebook timeline and in the user's Facebook news feed, where friends can discover, share, like and comment on them. This helps the retailer get more distribution. Critically, distribution is initiated by real and credible users, and is absolutely free.

Now imagine if the records being generated by the 'Like' button could be made available to retailers. For example: An online book retailer sees that 3,000 users hit the 'Like' button across a variety of books ('objects' in technical language) in the store. If the retailer wants details of the 3,000 Like actions, they can be acquired from Facebook's Open Graph using a Graph API. The API can be set up to periodically and automatically download data from Facebook into the retailer's enterprise information system.

Once inside the retailer's IT system the data can be processed to map each of the objects to a particular category of products or brands, or directly to the products to determine what actually interests the shopper.

Once the above insights are mapped against the shopper on the retailer's enterprise information systems, they can be combined with the customer's purchase history and purchase patterns captured earlier, to figure out what exactly the shopper is trying to accomplish in a particular browsing session (the shopper's intent). Based on this information, the retailer can get answers to the following questions: Can we make personalized offers? Based on the customer's interest, can we make the campaigns more targeted and personalized?

Effective utilization of Facebook Open Graph features will definitely provide retailers an extended platform to better understand their shoppers' interests, and can go a long way in establishing and extending the much needed connect with customers. As Facebook continues to innovate, I see exciting times ahead for both the shoppers and retailers, making it a win-win situation for both.

About the Author

Sanjay Agara heads the global practice on technology & architecture consulting with a specific focus on retail customers for Wipro. He has been part of the IT industry for about nineteen years, a significant part of which has been spent on consulting with large retailers globally. He has played the role of a trusted advisor to CIOs and CTOs on many of their enterprise level initiatives. He comes with a sound understanding of domain, combined with knowledge of enterprise-wide technologies to deliver solutions that not only meet business objectives but also help in maximizing value to the enterprise

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