Attribution Digital Marketing Facebook Ads Google Ads

The Value of View Through Conversions

View Through Conversions (VTCs) counts customers who were shown an ad, but didn’t click, and later made a purchase on your site. Should you count VTCs or ignore them? How do we calculate their true value?

My personal experience with View Through Conversions (VTCs) is that they provide very little real world lift in sales, in particular when dealing with lower funnel remarketing campaigns. The value increases if you are advertising to a brand-unaware audience, but the value is likely still very small.

But what is the actual value of a View Through Conversion vs a Click Through Conversion? You can theoretically calculate this by running a placebo A/B test of your actual ad vs a Public Service Announcement ad.

Below is such an A/B test that was run on the AdRoll network back in 2013:

Placebo A/B Tests to Measure View Through Conversions

Display Network A/B Test

You will likely need assistance from your Ad Platform or agency to properly run this sort of test, and to properly segregate the A and B groups.

Setup a Placebo A/B Test

  1. Create 2 separate (but equal) non-overlapping campaigns
  2. Campaign A will serve your “normal” ad
    Campaign B will serve a Public Service Announcement ad
  3. Run both campaigns for a few weeks
  4. Calculate VTC “lift” as follows:
Valid VTC Formula

Real Life Example

Campaign A
(Real Ad)
Campaign B
(PSA Ad)
Data from a real world A/B test performed in 2013 on the AdRoll network

VTC “Lift” = (329 – 261) / 329 = 20%

In this real life example, the irrelevant PSA Ads still managed to generate 80% of the View Through Conversion volume that the real ad generated. To be more clear, 261 people saw an ad to adopt a cat, and later went to to purchase a boating license.

So 80% of VTCs can be given a value of zero. Of the remaining 20%, more analysis is needed to figure out exactly how they influenced sales. The Real Ad did seem to generate more VTCs than the PSA ad, but the real question is those VTCs result in extra incremental sales or are they simply tracking sales generated by another channel such as e-mail? I don’t have a scientific answer to this, but anecdotally, I think the answer is that the VTCs did NOT result in incremental sales.

NOTE: A few years later we ran a similar Placebo A/B test on Facebook with the help of SocialCode. That test showed ZERO lift from VTCs, and the PSA Ads actually outperformed the real ads from a VTC standpoint!

So how should you value View Through Conversions?

Here are my recommendations:

  • Give View Through Conversions a value of ZERO. Unless you can prove otherwise via an A/B test, assume VTCs are not providing any lift to your campaigns. This is especially true for re-marketing campaigns as the visitors have previously visited your site, and may be actively engaged in checkout when the ad is shown.
  • Run your own Placebo A/B test. If someone insists on using VTCs in performance metrics, then you should insist on running an A/B test to calculate the true value. You should run at least two tests: One for remarketing audiences and another for brand-unaware audiences.
  • Be cautious and skeptical of anyone pushing the value of VTCs especially if they are an ad agency or ad platform that will benefit from including the extra VTCs in their performance metrics.

By Alex Czartoryski

Alex is the director of digital marketing for Manitobah Mukluks, Canada’s fastest growing footwear brand, where he helps the luxury winter boot manufacturer accelerate growth profitably via digital marketing. Alex has over 20 years experience in e-commerce and digital marketing.

5 replies on “The Value of View Through Conversions”

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?


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.


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?


Leave a Reply

Fill in your details below or click an icon to log in: Logo

You are commenting using your account. Log Out /  Change )

Google photo

You are commenting using your Google account. Log Out /  Change )

Twitter picture

You are commenting using your Twitter account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s