That Mysterious “Other” – Tales from Google Consumer Survey

Yes, I'd like to explore this mysterious Other, too...
Yes, I’d like to explore this mysterious Other, too…

Tim Dain is the Executive Director at SIRMLS and one of the most forward-thinking MLS people in the industry today. He’s also a bit of a tech geek and likes to experiment with techie things. Well, he sent me something he did through Google’s new consumer survey service, and I thought it was interesting enough to share. (With permission, of course.)

The Survey

First of all, here’s the link to the survey that Tim conducted. The question he asked was:

“How do you find information about residential housing that is for sale or rent?”

The possible answer choices were:

  • Local MLS or REALTOR
  • Other

Seems like a simple, straightforward question. The results, however, were somewhat… interesting:


That’s with weighting turned on. As Google tells us, the weighting is designed to make the survey more accurate:

Weighting is designed to remove bias from a survey sample and make the results better represent the target population. For example, if there are fewer female respondents for a given survey than the target population (all U.S., Canada, or U.K. Internet users in our case), we can upweight the female responses by a factor that brings them inline with the target population.

Consumer Surveys weights results by inferred gender, age and geography when possible to make the sample as representative as possible of the internet population. In validation studies, weighted data has been more accurate than unweighted data. If you prefer to see unweighted data, you can turn off weighting to see raw results.

Well, the raw results were even more skewed:

Unweighted raw results
Unweighted raw results

The Mysterious “OTHER”. What the hell does that mean?

I asked Tim about that. He said this was just a test of the Google Consumer Survey platform, and that if he were really looking for information, he’d spend more than 10 minutes thinking of a random question to ask 1,500 random strangers. 🙂

But ya know, I do love this part of his response to me:

Q: Why would I pay $150 to ask one question to 1500 random people?

A: To get the answer to a different question. From time to time my board members and committees could benefit from knowing how consumers act or react to changes in the marketplace, our services, or some other area of the profession.

Yep. MLS execs, board members, committee members, and brokers and average on-the-street real estate agents could all benefit from knowing how consumers act or react. This new Google Consumer Survey tool could be a powerful thing for people who want to know what the consumer is thinking, and know how to ask the right questions to get the insight they want.

Speaking of Insights…

First of all, let’s not carried away with so-called “insights” from a test survey that was run primarily as a test of the Google platform. But at the same time, there are some fun things we can’t not talk about on a blog. In an academic paper, maybe not, but on a blog? Heh.

For example, check this out:

survey-kl2ov52gx6k3u-question-1 (2)While the obvious “big question” is what the hell Other is, take a look at the responses selecting Zillow, Trulia,, and the Local MLS/REALTOR broken down by age.

Zillow wins every single age category… except one. For whatever reason, more people between 45-54 get their information from the local MLS or local REALTOR (besides the Mysterious Other, that is). Why might that be?

Can we theorize that people who are in this late middle age (to which I am too swiftly heading with each passing day) are experienced buyers and sellers who have been through a few transactions, and know the value of a competent REALTOR? Or can we theorize that perhaps they’re just not tech-savvy enough? Obviously, the survey doesn’t tell us why they picked what they picked, but isn’t that interesting?

How about this one:

survey-kl2ov52gx6k3u-question-1 (3)Once again, “Other” wins handily among this demographic. But check out the gap between Zillow and, and then and the Local MLS/REALTOR. People earning over $100K (the $150K+ didn’t have enough data) prefer Zillow 2:1 over, which they prefer in turn 2:1 over the local MLS or REALTOR.

Whoa. What’s that about? Now, Google says the results are not statistically significant, because the responses were too few (not a whole lot of $100K+ year people sitting around clicking on internet surveys) but… hey, it’s something interesting to look at and wonder about.

The final item I’ll leave you with:

survey-kl2ov52gx6k3u-question-1 (4)Subpopulation A are people 18-34 years old; subpopulation B are the 35+ people. This result seems perfectly reasonable, since most 19 year olds aren’t buying houses anytime soon. (BTW, Zillow wins that younger segment handily, except for… you guessed it… Other… which suggests to me that Zillow might be far stronger in the rental segment which might be what these younger folks are looking at.)

But the question you have to ask is… if today’s 24 year old is going somewhere else to get information on housing, picking up the habits of going somewhere else to get that information, how confident should we be that they will be contacting a REALTOR when they’re 44 with a lifetime habit… of going somewhere else to get their housing information?

Click on the link above, go play with the data (Google platform is fun), and feel free to draw your own conclusions. Or, given that this was just a fun experiment and a lot of the responses are “statistically insignificant”, draw no conclusions at all.

Thanks to Tim Dain, and thanks to you for checking it out. Give me your thoughts if you have any to share 🙂





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Rob Hahn

Managing Partner of 7DS Associates, and the grand poobah of this here blog. Once called "a revolutionary in a really nice suit", people often wonder what I do for a living because I have the temerity to not talk about my clients and my work for clients. Suffice to say that I do strategy work for some of the largest organizations and companies in real estate, as well as some of the smallest startups and agent teams, but usually only on projects that interest me with big implications for reforming this wonderful, crazy, lovable yet frustrating real estate industry of ours.

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