Facebook's Graph finds restaurant Likes but falls short of authentic endorsements
Facebook CEO Mark Zuckerberg recently announced the company was refining its search feature dubbed Graph, a tool it heralded as particularly good for finding restaurants. Unlike a traditional Google search, which hunts for Web page links relative to search terms entered by the user, Graph scours Facebook pages looking for other users’ Likes that match the searcher’s preferences.
For example, if a Facebook user wanted to know more about restaurants in Chicago, he can use Graph and fortify the search by asking for “Chicago restaurants Liked by my Facebook friends.” He could even go further by specifying only Facebook friends who live in Chicago or even Chicago restaurants Liked by Facebook friends working for a particular company in Chicago and so on and so on.
Graph’s ability to use people-centered information rather than mere SEO terms engenders trust between Facebook users based on Likes. In other words, if my graph of Facebook friends Likes these restaurants and/or their Facebook pages, then I may trust its suggestions more than those from a search engine.
Graph falls short, however, in several areas. By searching only for Likes, it neglects much richer customer data such as details of actual restaurant visits and opinions about food and service. It also overlooks the power of word-of-mouth referrals between friends in a social graph.
For example, to someone unfamiliar with a particular restaurant, a mini-review shared within his social graph that says, “I just went to Burger Life in Fayetteville, loved the Pretzel Bun with my Tilapia Burger and Pam the server went the extra mile,” is far more compelling to social media friends than a mere Like.
The technology that makes this happen was on the market well before Graph. Not only does it provide restaurant customers a channel through which to share information with their social graph about brands between each other, it also gives operators a channel through which they can engage those customers and track every purchase at the point-of-sale.
Most interestingly, those operators also can reward customers for their loyalty and for referring their brand and its products to others via social media word of mouth.
Such valuable word-of-mouth communication between customers and restaurants truly is something to Like!
Jitendra Gupta / Jitendra Gupta is a Co-Founder and Head of Product at Punchh, a mobile engagement and actionable insights platform that includes branded mobile apps for campaigns, games, loyalty, online ordering, payments, referrals, reviews, gift cards, surveys, and integrates with social networks and operators’ POS systems to gather 360° customer insights. Punchh helps restaurants increase same store sales and profitability by driving repeat visits, word of mouth, new customer referrals, and higher returns from marketing campaigns.