The Power of the Long Tail
This Post is mainly to respond to some questions Point2 users have about long tail search in the real estate vertical, and about a particular stat we've quoted: "60% of local homes searches have a neighborhood component to them." The comment came from a Google official in a slide show presentation on Search and the Real Estate Vertical.
The context is that of all the search conducted for real estate, homes for sale, or property (i.e. the real estate vertical), 60% of the search terms contained a neighborhood component. This is also called the longtail of search, which constitues more narrowly defined search terms. While "San Francisco real estate" represents a broad search, an example of a longtail search with a neighborhood component would be: "Nob Hill San Francisco real estate". I don't have the specific Powerpoint or research that were presented,nor do I want to misrepresent what they discussed. But I can demonstrate what this means, leveraging research we conducted at Point2.
If you are not Google and you want to measure the amount of search volume, you need to have a site that generates a lot of long tail traffic. Plus, you need to rank at the top for the broad terms, because they drive the most traffic. This way you are likely to have a good representation of the relative size of long tail traffic vs. broad search traffic.
We used Point2 Homes and chose the city of Ottawa Canada because Point2 Homes ranks well for top search terms used by consumers, like "Ottawa real estate" and "Ottawa homes for sale." Of course Point2 Homes represents a good platform for this test because it is optimized to generate a large set of long search traffic.
Over a 2 day period, Point2 Homes generated 547 visits to Ottawa and it's neighborhood level pages. Of those 547 searches, 259 or 47% contained an Ottawa neighborhood name, proving that consumers use neighborhood terms when searching for real estate in this area.
The ugly screen shot above shows you a piece of the working spreadsheet. Where the first column lists the keyword term, the second column is simply identifying ones with a neighborhood name. The 3rd column shows the search volume for the keyword term.
We have tested several other Canadian cities and the results are very similar with longtail traffic, generating between 45% and 50% of the visits.
You can see from that screen shot that the first neighborhood searches that we identified include: "homes for rockliffe ottawa," "house for sale ottawa west," "houses for sale glebe ottawa," "condos in the riveria + ottawa" and, "country club village ottawa."
Real estate is very local and while not all areas are the same, the patterns we see across the US are very similar. For this research, we did not use US cities because we do not yet have a good set of cities on Point2 Homes that rank at the top for broad terms.
It's clear that there is a lot of traffic out there in the long tail and thus it's clear that we need to take advantage of that traffic and describe content accurately to match what search engine users type into their search bars.
