More Local Pigeon Complications

The past couple of months has seen intense discussion in the SEO industry evaluating Google’s Pigeon update and its effects on “Local” results.  A major issue has been the volatility of the results (especially the “7-pack”) and sometimes contradictory conclusions of different commentators.

In this article I want to present some of the findings from our own research, showing that we may not even be able to depend on some of the research data itself!  When comparing data, it may be that we don’t even realise what we’re looking at may not be the same as local users are seeing for seemingly identical searches under the same conditions.

Here’s an example we saw:

Based on a Midtown Manhattan NY location, we started with a desktop web Google search for the search term “hotels”.  This indeed gave Universal search results with a 7-pack related to the Midtown area.

To make the test more accurate and repeatable for our other tests, we then manually set the location to   “551 7th Ave NY” using Google’s “Search Tools” menu.  Here is the resultant 7-pack:

google_map

Those results look pretty relevant.  They are also confirmed by one of my Keyword Ranking Tools.  If that was all we evaluated, then fair enough, all looks in order as far as most “Pigeon” discussions so far.  But what do real users do?  And what do keyword ranking tools do that you might be depending on for your data analysis?  A fair number of those users are going to click on “Maps results for hotels” to get a better look, as well as maybe for more results.  The results shown by Google Maps, for the identical query, referred directly by the Google Universal Search Engine itself, is very different!:

  1. Comfort Inn LaGuardia
  2. Library Hotel
  3. Pod 51
  4. Ace Hotel New York
  5. The Plaza
  6. Gramercy Park Hotel
  7. The Mark
  8. The Hotel at Times Sq.
  9. Cosmopolitan Hotel Tribeca
  10. St. Regis NY

 There are only two results that appear in both the Universal 7-pack and the referred Google Maps result set (Library Hotel /Pod 51).

What about real people, wanting local hotel info, who go straight to Google Maps?

For this, we close the browser and restart a new session, with no history enabled (all our tests are done not logged into a Google account).

To ensure consistency of results for the same location, we started off going to Google and manually setting the location to “551 7th Ave NY”, and then going to maps.google.com, and searching for “hotels”.  These are the results:

  1. Hotel Pennsylvania 
  2. Hudson New York Hotel
  3. Hotel on Rivington
  4. Ace Hotel New York
  5. The Plaza Hotel
  6. Library Hotel
  7. Paramount Hotel
  8. The New Yorker Hotel
  9. The Bowery Hotel
  10. Maritime Hotel

Those are very different again from the Google Maps results for the exact same query, but where the query came from a referral from Google.

An interesting observation is those results cover a wider geographical area.  So Google is seemingly reading some other “signal” about user intent for searches on Google Maps directly, compared to being referred there by the Search Engine itself.

As Google Maps becomes an ever more important “search engine” in its own right, some keyword ranking tools have added “Google Maps” as a search engine to get results from.  We wanted to know how they compared to the “manual” results we got above.

Here are the results from one keyword ranking tool, for a search for “hotels” with Google Maps as the Search Engine, for “551 7th Ave NY”:

  1. hotelpenn.com
  2. equity-point.com
  3. Marriott.com (Renaissance New York Times Square Hotel)
  4. carterhotel.com
  5. nymbhotel.com
  6. casablancahotel.com
  7. newyorkerhotel.com
  8. refineryhotelnewyork.com
  9. equity-point.com
  10. www1.hilton.com

These results are completely different compared to what we got for the identical manual Google Maps search (previous table above).

We believe this is because automated tools “tell” Google the location to search for by using the “Search near” functionality of Google Maps, which appear to give us the same results also (for brevity we didn’t include those results for this article).  But note as above, this is different to what a user may do when they search Google Maps directly.

Note also there’s a few different ways a user could do this and Google could explicitly or implicitly “know” the location to use.

Our interim conclusion isn’t that any one set of data, whether manually generated or from automated tools, is right or wrong.  Rather that there are differences of approach and you should understand the source of the data you’re looking at, and also think about “what would a real user do”.  Because rankings, and conclusions and inferences from them, could send you in the wrong direction if “real” users are using the search engines differently from what you might have thought.  Then just for fun, we wondered what a “real user” would see, sitting in a coffee shop near Times Square, eg at “551 7th Ave NY”, when searching the Google Maps app on their Android tablet. Here’s the top 10 results:

  1. The Hotel at Times Square
  2. The Algonquin Hotel Times Sq.
  3. Hotel Sofitel New York
  4. Manhattan Broadway Hotel
  5. Night Hotel New York
  6. Renaissance NY Times Sq. Hotel
  7. Library Hotel
  8. Paramount Hotel
  9. The Muse Hotel
  10. Row NYC

Not surprisingly, they’re very different also!

One side anecdote from this piece of research, Marriot chain seem to be doing something right with their SEO, as their property was listed in every single search we did.  They may have lessons worth studying in further detail!

I hope to have some more on this type of local research next month.

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