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Geographic & Demographic Impact on PPC: Part 1

The Rimm-Kaufman Group launched a study about a month ago to try to determine the impact of geography and demographics on PPC user behavior. We theorized that just as catalogers know that certain regions of the country and certain specific zip codes respond to catalog offers at a much greater rate than average, perhaps we’d see similar behavior in Paid Search.

HYPOTHESIS

We anticipated that areas with low population densities would have fewer brick-and-mortar stores and that people using paid search links would therefore be more likely to be buy than average. We expected traffic value to be also strongly linked to wealth.

METHODOLOGY

Digital Element was kind enough to provide their highly accurate mapping of IP addresses to zip codes for two of our larger clients: one an online pure-play, the other a major brick and mortar chain. We are enormously grateful to Digital Element as their data played a critical role in the study. We tried this previously with a cheap database purporting to do the same mapping and found that data to be unreliable and almost unusable as it was formatted.

Using the Digital Element data we tied about 3 million PPC clicks to their zip codes for one data set and almost 2 million click-throughs for the other. We then tied each zip code to census data we purchased which provided information about the location, average household income, population, land area, average age, average home value, number of business addresses, number of residential addresses, etc.

From this and our own conversion tracking, we were able to determine the impact on traffic value of each of those factors independently and in combination with other factors. We hoped to find a model that yielded strong correlation, allowing us to bid differently by zip code, better marrying bids to the anticipated value of the traffic.

We used the open source stats package “R“, many different statistical modeling techniques, several different data representations — by individual zip codes, and by data aggregated to zip3 and zip2 where necessary for data accumulation (many thanks to Kevin Hillstrom for that idea!); we looked at logarithms, squares and inverses of the values — to determine the best model.

FINDINGS

There is very little correlation between any of these factors, alone or in combination, on traffic value in the cases we studied. Our best, reasonably simple, model used the combination of average home value and population within the zip code. However, this model had an adjusted R-squared value of 0.15, meaning only 15% of the variance in performance could be explained by the model, the other 85% was some combination of random noise or other factors not available in our data.

There were a handful of zip codes and regions that appeared materially better than average, but on balance, we have to conclude that knowing the zip code of the user doesn’t have much value for retailers in Paid Search bid management. It may be much more predictive for financial institutions trying to anticipate lead values, and it may have tremendous value for advertisers to have this information on their websites to target offers appropriately, note store locations and local offers, etc. But for national retailers, it appears that the person in rural Arizona searching for a leather ottoman is no more, or less likely to buy it than the person in downtown Chicago.*

We did find that the folks in rural areas were much morelikely to conduct searches than average. Taking the volume of clicks and dividing by the population within the zip code, we found that nearly 45% of the variance in clicks per person could be explained by population density.

People in rural areas and densely populated urban areas are more likely to use PPC ads than folks in suburbia and small towns, but by and large they’re no more likely to buy when they do.

As a physics student in college, my favorite physicist was Johannes Kepler. Kepler developed an incredibly complex model to explain planetary motion. The test for any such model was whether it could accurate predict the position of planets in the future. Using the new, improve telescope designed by Galileo, Kepler found that his model was off by 2%. Just 2%! But that 2% was enough to convince him that his model was wrong. He scrapped all that previous work and went back to the drawing board, eventually determining that the planets followed simple elliptical orbits.

Kepler had the integrity to reject his own theory as a first step towards getting at the truth. We’re no Keplers, but we can and will admit when we’re wrong.

“So, if you didn’t find anything, why is there a Part 2 post?!?” A reasonable question.

In the other piece of the study we looked at the impact of having a physical store in the zip code of searchers on both their propensity to search and their conversion rates. What we found was both fascinating and quite the opposite of what one might expect. Stay tuned!

*We’re not saying that geo-targeting doesn’t make sense in many cases. It absolutely does. For regional chains conversion rates are often better in areas where the brand is known and trusted; for local service businesses it’s essential. However, as my friend and client Eric Nadler put it: “If some fat, 55 year-old, man searches for “ballet slippers” I want to serve him an ad! He might have grand-daughters!” In many respects the act of searching takes care of the demographic/psychographic profiles for you.

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Comments
21 Responses to “Geographic & Demographic Impact on PPC: Part 1”
  1. We’re working with a couple of people right now to help them get their stores listed well in local search results, both SEO and PPC, so will be interested in seeing the “more” results from this experiment.

    thanks!

    Jonathan
    http://www.GreatLegalBenefit.com/today

  2. Louis says:

    “In many respects the act of searching takes care of the demographic/psychographic profiles for you.”

    Well said!

    I’ve been reading this blog for a while now and want to say this: This is the best PPC blog. Period.

    Thanks!

  3. Thank you for your comments, gentlemen. Louis, your check is in the mail :-)

  4. Ryan Beale says:

    I have to agree with Louis. This is an excellent PPC Blog. RKG constantly adds value through real life examples/tests. Thank you for sharing your findings.

    Best,

    Ryan

  5. Ryan, thank you for your kind words.

    This blog is made better by comments from smart folks in the industry sharing their perspective. It’s all about the discussion, so please do chime in!

    George

  6. John Lee says:

    George,

    Why am I not surprised that you were a physics student in college? ; )

    Just a thought (and perhaps over-complication) – but did you consider overlaying your test data with that of similar catalog distributions? I’d be curious to see how they compare side-by-side with PPC.

    Either way, I love the depth to which you guys dig into the PPC world here at RKG!

    -John

  7. Thanks John,

    For this study we looked at data from one brick and mortar chain and one online pure play.

    Kevin Hillstrom has done some great analysis on catalog firms and the online interactions created by that dynamic.

    Without the geographic piece, we’ve done a lot of studies with our catalog clients on the impact of book drops on PPC. No question that dropping catalogs influences more than just brand search, it influences non-brand/competitive search as well.

    The hard question in these cases is: are both the catalog and the PPC ad necessary to getting those orders, and to what degree? Again, Kevin has done some amazing stuff in this area.

  8. Billy Wolt says:

    “We did find that the folks in rural areas were much morelikely to conduct searches than average. Taking the volume of clicks and dividing by the population within the zip code, we found that nearly 45% of the variance in clicks per person could be explained by population density.

    People in rural areas and densely populated urban areas are more likely to use PPC ads than folks in suburbia and small towns, but by and large they’re no more likely to buy when they do.”

    I think this tells the entire story. If people in rural areas are searching online more, I’m sure they are buying online more as well, they just have more time to spend looking.

    Your tests may have shown no difference, but that could be because people in rural areas A)are price hunting B)window shopping or C)did not like the retailer in your tests

  9. Thanks Billy,

    I think we’re saying the same thing. The rural folks search more than average and convert at the same rate as average, therefore they buy more online than average.

    A disproportionate number of PPC shoppers come from these groups. However, the key piece from a bidding perspective isn’t the search volume, it’s the sales dollars (or margin dollars) per click. Since that seems to be largely the same for all demographics/geographies we can’t bid more for that traffic than we can for other traffic.

    However, you’re absolutely right that we’re talking about data on two retailers, here. By no means a comprehensive study.

    George

  10. Chris says:

    “People in rural areas and densely populated urban areas are more likely to use PPC ads than folks in suburbia and small towns, but by and large they’re no more likely to buy when they do.”

    — which makes me ask, “Were you calculating conversion based on visits or visitors?” Your sentence referencing “people” suggests it was visitors, but I want to be sure. The interpretation of the results could be otally different.

    Also, I love the suggestion that rural people have more time to spend looking online. I’ll be sure to tell my country cousins about all the spare time they seem to be hiding from us city cousins! :)

  11. Chris, thanks for your comment and for catching me in sloppy language. We measured dollars per visit, not per visitor. If I have time, I’ll run the numbers the other way to see if it makes a difference.

    I certainly don’t suggest that folks in rural areas have more time on their hands. I happen to live in a rural area with a small horse-farm and realize that between longer commutes and land upkeep, time is dear. Indeed, this is the point. Because it takes more time to drive to the store, these folks tend to be remote shoppers (online and catalog).

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