Clicks, Unicorns, and Magic Fairy Dust Part 1

Collective put out an interesting study on the profile of clickers. To quote a colleague, this horse can’t possibly stand another beating.

Unfortunately it can. If you’ve run campaigns, you’ve probably seen advertisers use click metrics as a measure of driving traffic to a client’s site to raise awareness. Last year, Collective surveyed advertiser and agency executives and found 64% still use CTR to evaluate ad network performance! No wonder brand dollars haven’t moved online. The horse is still under threat of more pain. We need to stop the abuse now.

Studies from Lotame and Collective suggest you may be hurting the performance of campaigns by focusing on clicks. To illustrate, you need to understand who’s clicking on your ads.

Walk through this with me:

  • Collective says:
    • 18% of clicks are from accidental clickers.
    • 1% of all unique cookies account for 100% of clicks. A portion of that 1% is made up of serial clickers – people that, for reasons unknown, click on ads A LOT.
  • Say you get 0.1% CTR on 1,000,000 impressions. That’s 1,000 clicks.
  • Combine the previous three bullet points. Think for a second. “Performance” is a misnomer:
    • Say 5% of the 1000 are clicks from “good traffic”. The ones that care about your message. I think I’m being generous with 5% given the amount of accidental clickers and serial clickers, but if in doubt, use 25%. Use any number up to 50%. Won’t matter.
    • I’m calling these clicks “unicorns” because that’s what you’re chasing – “good traffic” embedded in clicks that may or may not be fantasy.
  • So here’s where we stand in looking at the “good traffic” in the 1000 clicks you got:
    • Unicorns at Ratio of 5%: 50
    • Unicorns at Ratio of 25%: 250
    • Unicorns at Ratio of 50%: Fantasy – not with 18% accidental clickers and a disproportionate amount of clickers being serial clickers.

But it doesn’t end there.

Look at those numbers. If you optimize against clicks, you may be letting 750 to 950 actions out of 1000 you don’t care about overwhelmingly represent the 50 to 250 actions you may care about. Then what happens through optimization?

You increase the probability of someone clicking an ad with no information about that person. Exceedingly, the larger population of serial clickers and accidental clickers take over. The inmates are running the asylum:

  • A placement with high clutter with an ad in the middle of a navigation area increases accidental clicks. Your optimization methodology sees more clicks, so heavy up on that site.
  • A placement with a high concentration of serial clickers shows higher click performance. So heavy up on that site.
  • 99% of unique cookies NEVER click on an ad. You have no way of optimizing towards your audience in that pool if you look at clicks alone. Your unicorns can’t find reinforcements.
  • Vicious cycle goes on as your ROI goes down the tubes. However, your CTR looks fantastic as it increases. Unfortunately, you haven’t raised awareness because the clicks you’ve brought on don’t care and the ones that do have been “optimized” out.

This is why I believe the two studies both showed no correlation between clicks and brand lift. You can use a higher ratio than 25% to start if you’d like, but that ratio won’t hold long term. You’re just delaying the inevitable – you shrink the Unicorn Ratio down through “optimization” and ultimately all you have are a bunch of dead unicorns (PETA Disclaimer: no equines mythical or otherwise were hurt in the writing of this post).

Absent a brand lift study, there’s no single good way to know you’re reaching the right people, but there ARE ways to optimize to better metrics than clicks. If you’re optimizing against the wrong metric, you’re actually reducing value and getting zero ROI. Doing that heavy lifting is better than wasting your ad spend. I’ll focus on some of the other options for metrics in upcoming posts. I’d do it here, but I’m out of space and the horses and unicorns need some rest…

Categorized as: Blog Page, Digital Advertising

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