If you are running a Display or Retargeting campaign you have probably been exposed to View Through Conversions (VTC): View Through Conversions are conversions where a customer saw — but did not click — a display ad on the display network before completing a conversionThere is a lot of debate on if you should count View Through Conversions or ignore them. How can you be sure they legitimately assisted in the conversion?

A/B Testing vs a Blank Ad

Display Network A/B Test

  1. Create 2 different but equal non-overlapping campaigns
    (If you use AdRoll your rep will be happy to set this up for you)
  2. Campaign A will serve your “normal” ad
    Campaign B will serve a Public Service Announcement ad (in our case it was an ad for the SPCA)
  3. Run both campaigns for a few weeks
  4. Do the math:

Valid VTC Formula

Real Life Example

Campaign A
[Default Ad]
Campaign B
[Blank Ad]
Impressions 99,467 97,412
VTCs 329 261

Valid VTCs = (329 – 261) / 329 = 20%

This means that only 1 in 5 View Throughs actually assisted with conversions — the other 80% had no effect and should be ignored. These results are specific to BOATERexam.com — your results will vary depending on your business and ad creative.


  1. Really ingenious idea for testing VTCs’ real value. This would work on AdWords, but not so much on Facebook Ads where I need to associate the ad with my account to get standard ad placement. Any ideas on how to conduct a similar test on Facebook Ads?


    1. Hi John,

      Even the test as described here is flawed, because the audiences are not fully separate. Eg: The same user may see BOTH the A and B ads, and so there *may* be a branding influence from the branded A ad that then gets attributed to the unbranded B ad as a VTC. The challenge with splitting the groups into 2 distinct audiences if that you are unsure if the split is “fair” or if there is one group that is inherently more likely to purchase.

      Thinking about this as I write, the solution (for both FB and AdWords) might be to dynamically create 2 separate remarketing audiences on your site by alternating between 2 different remarketing tags for new visitors. You would then create 2 custom audiences from these 2 base audiences (Audience X = Audience A – Audience B; Audience Y = Audience B – Audience A). Then run the same ads in parallel for each custom audience. If I get the chance to try this out, I will post all the technical details here.

      On another note, related to Facebook VTC, keep in mind this scenario: A user has Facebook open in a browser tab (in the background), with auto-updating right-hand ads going. The user visits your website, and receives the facebook remarketing pixel is fired. The facebook site in the background tab detects that the remarketing cookie is now set, and starts serving up your ads. In the meantime, the user hasn’t left your site yet. He browses through your products, and makes a purchase. On your purchase page, the facebook pixel fires again, indicating a conversion that is tied to the remarketing ad that was displayed in the Facebook tab. So the facebook ad gets credit for the VTC even though the user never saw it, and never even left your site.


  2. Hey Alex,

    Great approach – I had the exact same idea which I googled.
    Your page was the first one to show up, which is why I landed here. 🙂

    My question regarding this method is: What do we do with people changing devices?

    I don’t know if your plan was just to see how large a share of the view through conversions actually was due to the ad and how much was due to exposing people who would convert anyways?

    I still believe that to see the full effect of the ad, we need to locate conversions that happens when people are exposed to an ad on one device and later converts on another device.

    What’s your thoughts on that if you have any? (I’m asking since I cannot come up with a solution myself)


    1. Hi Martin,

      The main goal for me was to figure out what share of the VTCs actually had an effect on conversions.

      I think to calculate the “full effect” of the ad is beyond me. But to calculate the impact across devices, one place to start would be to look at the “UserId” tracking feature is Google Universal Analytics in conjunction with the Display network support — you *theoretically* should be able to see ad views across multiple sessions and devices for a single user.

      I hope that helps (and I’d love to hear what you come up with)


    1. The actual ad used was not a blank ad but a PSA ad (Public Service Announcement for the SPCA I believe). The was all handled by our AdRoll rep, so I am not sure of the exact steps necessary to set this up manually in AdWords.


  3. Thanks Alex.This is an interesting split-testing result.I always had a doubt whether regretting helps in conversion.When people see the the targeting ads on reputable sites like Forbes,They tend to relive the brand is trustworthy.It leads to conversions i guess.How’d you got approved from adwords for a blank ad?


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