Heading toward the Facebook recommendation engine

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There’s an interesting thread over at Mike Blumenthal’s blog on the effect of Facebook Places on the local reviews space.

My view is that reviews and updates will coexist, much as blogs and Twitter coexist. People who were less committed to reviews will migrate their activity to Facebook Places updates. But Places could lead toward the ultimate recommendation engine.

In the local space, there’s really only one review site that matters: Yelp. They’ve got a strong set of tools and an active and engaged community. New restaurants and bars, which are often of the most interest, will have a dozen reviews on Yelp a year before they even show up on many Yellow Pages sites.

There are three big challenges with Yelp:

  • It’s been too successful. Many restaurants have hundreds of reviews. Although Yelp provides great tools for analyzing the data, it can still feel overwhelming. It also discourages participation from more casual users. In the early days of Yelp, I was an active reviewer. That’s tapered off substantially — what’s the marginal benefit of me writing the 426th review of a place?
  • These aren’t my real friends. I don’t know how compatible their tastes are with mine. It also affects the propensity to write reviews. People are more likely to do something that helps their friends than something that helps a generic audience.
  • Skewed demographics. Yelp primarily caters to a young, urban demographic. If you’re a mom in the suburbs, its value is more limited.

Facebook Places lowers the bar to participation and ties it into real-life social networks. Instead of writing out a long review, a few clicks is all it takes. Combine that with Facebook’s large user base on mobile devices — its monthly uniques on mobile devices is 4x Yelp’s monthly uniques on the Web — and we’ll see a tsunami of local data. (For more on importance of massive amounts of data, watch Google’s Peter Norvig’s talk.)

While each blip may not be as rich as the data in Yelp, you could build a recommendation engine to infer a lot from that data.

If I see that a place I am considering visiting is regularly frequented by my friends with families, I can infer that it is good for kids. Positive reviews can be inferred by friends going back to a place regularly. There are some friends who I have negative taste relationships with. If I know that they’re regulars somewhere, I know not to go there. Facebook can also make recommendations based on places I’ve visited and the overlaps with places my friends have visited. Facebook also has real demographic information which could be used to tailor recommendations.

Status updates in the social network also prompt discussions. Even if the original poster doesn’t write a review, it may be followed up by “hey, I was thinking of going there. what did you think of it?” Facebook could also close the loop by prompting people to add star ratings, Like or add comments a few days after a check in.

When it comes to restaurant reviews and recommendations, most people are looking for “good enough”. While you could spend hours reading every Yelp review of several restaurants and possibly get a better answer, a recommendation based on your friends’ activity is probably nearly as good. Facebook has done really well with good enough; Facebook Photos dominates online photo sharing, despite many functional weaknesses when compared with flickr.

I built a prototype of this when I was at AOL Search and even with a few users in the system, it worked really well.

More on: Facebook, local search, Yelp

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About Rakesh Agrawal

Rakesh Agrawal is Senior Director of product at Amazon (Audible). Previously, he launched local and mobile products for Microsoft and AOL. He tweets at @rakeshlobster.
This entry was posted in facebook, lbs, local search, maps, yellow pages, yelp and tagged . Bookmark the permalink.

15 Responses to Heading toward the Facebook recommendation engine

  1. I strongly agree that there will be co-existance…not just because of time constraints/willingness but because of other factors as well…

    In rural America, the density is too low for any significant number of updates…in that situation reviews will hang on much longer.

    I also think that it will likely break down by industry…for entertainment, food venues, check-ins and updates make all kind of sense.

    It is not so clear to me that they make sense for the plumber that comes to you or for that service that you use once in a life time (ie a custom jeweler for the engagement ring or the personal injury attorney).

  2. I agree that check ins aren’t really relevant for service-related businesses.

    I’m not sure that that the rare cases you mentioned are well solved by existing review products. I still worry about how much those are gamed given low density.

    I’m much more likely to address those with a status update like “Anyone know a good jeweler in the area?”

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  12. Seems like this is what Facebook wanted a geolocation check-in company for. But there has to be a way of inferring whom your tastes are negatively correlated with (not just your friends!) and what dimensions (eg “good for kids”) constitute your taste.

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