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Understanding Google My Business & Local Search

Maps for Recovery & Yelp for Discovery – a great combo

Last night, reports started circulating (see TechCrunch who broke the story as well as Greg Sterling at SEL & Scoble for analysis) that Google was in late stage conversations to acquire Yelp for $500 million. It is deal that, whether it occurs or not, will have huge impact on the makeup of the local landscape. With Yelp in play, additional consolidation in the space is likely to occur rapidly.

I have no idea whether this deal will go through but I have been an active user of both products and can understand why it is in Google’s and Yelp’s interest that it would. I am more intrigued though by the user experience and what will become of that if a merger does take place.

Since June when I purchased an iPhone, I have travelled without a laptop, using the iPhone exclusively as both computer and to navigate the unfamiliar local environments. Over that time I have experimented with a great number of local apps but in the end have always returned to and continue to use two: Google Maps and Yelp.

I would use Google Maps mostly for the “recovery” process of local navigation; what is the address of Kossars’s? Where is the hotel in relation to the subway exit? What is the quickest way to get 8th Avenue and 14th St? In large urban areas at least, it provides incredibly accurate AND useful results.

Yelp on the other hand, I would use for “discovery”. What tasty ethnic restaurant would meet our budget? Where can we get Ethiopian food? What is cheap and near the hotel? In fact, upon arriving in NY and meeting my “nephew” near my hotel for dinner we had both identified the same restaurant as a likely choice. He by asking his college roommate and me by asking Yelp.

Google clearly had the recovery process nailed and Yelp had a well developed discovery process. It struck me at the time that what was missing in the local space was the ability for the Yelp like discovery process to take place across all local businesses not just restaurants or hotels.

What did Yelp have that Google didn’t?
– More granular data about pricing, dishes and other specifics in the restaurant arena
– A greater quantity of passionate reviews and reviewers
– A more faceted search process

I had always thought that it was the reviews and business details that made Yelp so useful. But in the end, the ability to quickly and easily direct the program to narrow the choices of what met my needs, made Yelp really work for me. This is, at least in a limited way, faceted search. Where the user, by working a little harder at giving the machine more information, can get better results. Some parts of the structured search were provided automatically but all were provided seamlessly.

With Yelp, the process of selecting a restaurant, particularly on the iPhone, allows the user to narrow down the data set to a meaningful number of useful results. What neighborhood, what price range, what quality range are user inputs that quickly allow the service to rank and present a list of restaurants that is satisfying. Yelp really seemed to want to know what I, the user wanted.

Google, on the other hand, has always treated search as a commodity and the user as a simpleton. It has always taken the single field, brute force, we’ll make a great guess at what the user wants approach to providing the answer. With its many algorithms and huge amount of available horse power, this has worked well for web search. It, does however, have severe limitations in local search where ground truth is the ultimate measure of success, not relevance.

But for a structured search like Yelp’s to work and for Yelp to keep growing, they need data and lots of it. That is something that Google has plenty of in local.

So while I think Google would be acquiring a great number of valuable assets if they were to acquire Yelp (a large social network, 8.5 million reviews, a local sales force, a rapidly growing audience), it could also be acquiring a new way of looking at search in the local space. One that clearly works very well.