Natural Born Clickers

Stop throwing good money at bad impressions and maximize the value of your investment in digital media.

In 2009, comScore and Starcom produced a joint study of clickers that concluded 8 percent of the Internet audience is responsible for 85 percent of the clicks.

This report elicits an examination of your frequent clickers and whether they are the audience your brand is looking to reach. This is fundamentally important to consider before selecting click-through rate (CTR) as a campaign metric.

My own research suggests something similar to comScore/Starcom. The analysis is constrained to an audience of just clicks and not Internet users. However, the results show a similar skew to the comScore/Starcom results.

In a sample of 200,000 random clickers taken in March 2012, I found that 40 percent of the clicks were produced by 20 percent of the clickers.

random-clicks

This data suggests there is substantial bias to a macro segment that can be described as frequent display ad clickers.

If there were no bias, the graph above would show a straight line, which would mean that the clicks are evenly distributed and therefore would not skew to any particular descriptive characteristics, but as you can see this is not the case.

What are the audience characteristics of the frequent vs. infrequent clickers?

I ran an analysis to describe the differences between the frequent vs. infrequent clickers. Here’s what I found.

Contextual segments:

goog-vertical-audience-analysis-of-heavy-clickers-vs

Browser:

browser-audience-analysis-of-heavy-clickers-vs

Exelate Segments:

exelate-audience-analysis-of-heavy-clickers-vs

Hour of day (EST):

hour-audience-analysis-of-heavy-clickers-vs

Conclusion

Clickers have a macro profile. My interpretation of the charts above leads me to believe that frequent clickers in this sample have a tendency to be interested in:

  • Interests of frequent clickers:
    • Google business news
    • Google Internet software
    • Exelate online streaming
    • Exelate shopping
    • On the Internet between midnight and 3 a.m. EST
  • Interests of infrequent clickers:
    • Google arts and entertainment
    • Google music and audio
    • Safari as a web browser
    • Online in the late afternoon/early evening

This analysis will differ on a client by client basis and I do not claim that the above profile represents all frequent clickers. It just represents the frequent clickers in this sample. The point is that any client should know how their clicks skew in order to make an intuitive judgment as to whether this is the audience of their brand. If it is, then CTR is a fine metric. If it isn’t, then one of two things needs to happen:

  1. Pick a different metric.
  2. Plan the digital media buy at the atomic level. This means only on the intuitively correct page level URLs and only to the intuitively correct audience profiles.

If the advertiser heads down either of these paths, then they need to realize two important points.

  1. If the advertiser takes steps to eliminate frequent clickers from their targeting, the CTR will go down and the CPC will go up as compared to other vendors or campaigns that are not held to these higher standards.
  2. CTR should not be an absolute metric. It should be a relative metric. Given the right constraints, CTR can be used to pass judgment on tactic one vs. tactic two, but it cannot be used from campaign to campaign; so say a CTR above 0.20 percent is good and below is bad.

How to Correct Your Digital Media Campaign

Clicks aren’t enough. If you think your digital campaign has this problem, then you should consider consolidating your targeted media buying into a platform that can help focus inventory toward the right clickers. It’s as important to not optimize to a bias as it is to target the right audience.

Platforms that can help you will have some type of page level targeting and audience extension model as part of their offering.

If the audience and page planning constraints are established prior to the campaign, then the digital campaign does not waste money by chasing audience skews that the advertiser does not wish to target. Your campaigns will stop throwing good money at bad impressions and therefore maximize the value of your investment in digital media.

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