My colleague Matt Booth and I had the chance to talk with the folks at Yokel this morning. The company offers a local search engine (currently in beta) for offline shopping. The value proposition is that its search algorithms are acutely tuned in to a much smaller and more relevant data set (local retailer and product information) than general search engine algorithms.
A search for sunglasses in San Francisco (the rain has finally ceased for a bit here), for example, will bring only product and retailer results for sunglasses in the area. A Google search, by comparison, will return more general results. There is a trade-off here because Google, of course, has greater reach, traffic and mapping capabilities. Taking the extra step to click on the "local results" on Google’s search engine results page will bring you to Google Local, where local retailers are nicely laid out on a map. But product information is still missing.
This in part represents the advantages of vertical search, which we've conveyed time and time again. Search results are more relevant to shopping, buyer intent is more clearly discerned, and ad inventory (paid inclusion or sponsored results) is therefore more valuable. This search relevance is the principal that Eurekster is built around in the social search space (BusinessWeek points out today that Eurekster could be an acquisition target for Microsoft in building more social search capabilites).
The challenge for Yokel and others in the local shopping space is acquiring and structuring data, and in working with stores to get inventory data. The more "real time" inventory data is, the better capability exists for closing the loop on online search/research and offline transactions (in-store pick up, etc.). The better tracking afforded by this in turn boosts the value of paid inclusions and the accuracy of ROI analysis, not to mention serving users and driving traffic.
There is a lot more to talk about here, and we'll explore these issues further in the near future.