Sometimes organic search seems straight forward, type in a keyword and returned is a list of 10 recommended websites. Of course, getting to the top isn't so simple, but the notion that once you arrive at the top, traffic will ensue is a hypothesis hard to deny. Local search results don't play into this scheme. They have variables such as size of the map, and definition of a region's center that combine with trust, a citation, or sometimes what I call "sureness factors" to determine what businesses should be recommended. This post isn't a blueprint for better local rankings, but it certainly may provoke some thought as to the variables Google uses when providing local results. Here are the 3 variables of local search.
Here is an example that will help explain the variables. Take a look at the results for "Pittsburgh Dry Cleaner," don't search this on the /maps, do a typical web search. Google returns a map very broadly defining Pittsburgh. It doesn't just show downtown, it shows an entire region. Google is classifying Pittsburgh as a large region, and not just a downtown area. This is the first variable taken into consideration when delivering local results. That is the size of the map which is signaled either by the map viewing size and zoom, or the keyword searched.
Within these results are dry cleaners from the city, suburbs, and a few in between. The reason I believe these results are picked out of all the possible dry cleaners around Pittsburgh is because Google is either a) trying to show there are dry cleaners randomly everywhere in Pittsburgh (possible, but I think not as likely), or b) Google is only showing the dry cleaners it feels the strongest about. In other words, it is most sure these dry cleaners are at the location specified, and of course that dry cleaning is actually going on there (it could all be a front:). Thanks to the handy work of David Mihm, Andrew Shortland, and Mike Blumenthal there are methods to let Google and other mapping search engines know where you're located, and in fact you do what you do. Some of these aspects include:
The third variable I believe that goes into play is the center of the region as defined either by the keyword searched, or by how Google is interpreting the center of a metro region. This is tricky to explain, and I hope to do it through an example below. My belief is that the center of a metro area is the weakest of the three variables.
Here are the results for the same search, "Pittsburgh Dry Cleaners," but this time searched at /maps.
Notice the result vary from D - G. This I believe is because the map on the web results page is at a slightly different zoom level than the /maps results. Since the maps vary in size as defined by the viewing space and zoom level, results are different. And again since Google is defining Pittsburgh as a large region, it's not just showing dry cleaners downtown. If you zoom in you'll find more than one dry cleaner downtown.
Now let's look at a smaller region example within Pittsburgh. Search "Squirrel Hill Dry Cleaner" on the web search. No map. Okay, now search "Squirrel Hill Dry Cleaner" on /maps. Google redefines the map by zoom, and determines a new center. This is where ambiguity comes in for Google. It understands that Squirrel Hill is a specific region in Pittsburgh, but how it defines the center is probably debatable, and again it is showing the dry cleaners based on elements of sureness. Here are the listings for the /maps search "Squirrel Hill Dry Cleaner"
Now on the map begin dragging the map toward the right, after a few drags toward Frick Park the listing all reorganize. A new center is defined, here are the results based on the new parameters of the map. C and B switch. E is new, F and G are new.
For a final demonstration, zoom in all the way down to the second to last notch, and go to the corner of Murray Ave. and Pocusset Street (here is the link). Notice the previous results that were C and E have now become A and B, and there are only two results.
These are the variables at work which are size of the map either defined by zoom and screen space, Google sureness, and finally how the center is defined, a weaker variable.
Jeff is the founder of Catch Search Marketing. Catch offers local businesses free guides to help improve their online marketing knowledge, including a local search marketing training course. Jeff has delivered SEO results for major consumer oriented websites all the way down to local businesses, he has spoken about SEO at Higher Ed Heroes.
Away from the laptop Jeff enjoys anything mountain oriented, and a constant itch for music. .
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