Facebook Graph Search 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, 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 on 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 sharing information 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 created by Punchh and on the market well before Graph. Today, 260 restaurant brands use the Punchh technology: a combination of a smartphone-based app for customers integrated with the restaurant’s POS system.

Restaurateurs can communicate directly to their Punchh-using customers to track their purchases, gauge their experiences, reward them for loyalty as well as reward them for referring their restaurant to others.

In turn, restaurant customers have a channel through which they can share information about visits to that restaurant with others within their social graph.

Such valuable word-of-mouth communication between customers and restaurants truly is something to Like!