Google has sent QR Code stickers to about 190,000 businesses across the US that have been tagged as a Favorite Place (they have a mobile version of their website). Favorite Places are the mobile equivalent of Place Pages (aka Google Places).
Google Video explaining Favorite Places
TechCrunch has quoted Google Earth VP John Hanke, “Google will be adding these businesses incrementally. ‘They are selected based on their PlaceRank,’ says
John Hanke, VP of Google Earth, Maps, and Local. PlaceRank is like PageRank for places It tries to figure out how prominent a place is based on factors such as ‘references on the Web, reviews, photos,’ says Hanke, ‘how many people know about it, how long its been around.'”
PlaceRank isn’t new – but I believe this is the first acknowledgment of its use with Google Maps in a local search context. Bill Slawski reported it back in 2007 in this post, which is well worth reading (like the rest of his site). Here is a link to the patent that describes Place Rank (two words) and Interestingness.
Undoubtedly, Local Search SEOs will be excited by a new unit of measure (will we get another green pixel bar? – I think not). I think this is a good move, but are Americans and the West in general ready to use QR Codes?
The patent offers some clues about the ranking algorithm.
 In an embodiment, this ranking, which can be referred to as place rank, is computed based on the weighted contributions of various non-cartographic meta attributes about a geospatial entity. Rather than directly measuring a characteristic of a physical place, such as its population, these attributes reflect traits of abstractions or representations associated with the geospatial entity. Examples include an attribute of a description of an entity (for instance, the amount of detail in the description of an entity or the number of times a description has been viewed), an attribute of a definition of an entity (e.g. the context or downloads of a definition of an entity, or attributes about the creation of an entity in a public forum), an indicator of the popularity of a geospatial entity (such as the number of views, downloads, or clicks on the entity or a placemark associated with the entity or an attribute based on a ranking or score assigned to an entity), or the relationship of an entity to its context, such as the category to which an entity belongs. Attributes that fit into each of these categories are described in greater detail below:
Here is my summation of the ranking detail in the patent:
So, there are numerous factors in this algorithm that might seem too complicated for an individual SEO to influence, which basically suggests that gaming PlaceRank will be very difficult. 🙂
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