A Crash Course on Incrementality

0 min read
August 26, 2020


With Q4 around the corner, advertisers are looking to perform their final testing agendas to ensure a wonderful holiday season. Incrementality has become more and more important as costs have risen year over year. We thought it beneficial to provide a quick refresher on incrementality to help out with your holiday and testing agenda prep.


The goal of this article is to not provide an exhaustive study of conversion lift testing. Rather, what are several overlooked aspects of Facebook’s conversion lift testing that may provide an edge on your analysis.

What is Incrementality on Facebook?


Facebook leverages an Intent To Treat model for their *incrementality testing. After deciding on a control size, Facebook randomizes the entire platform to be either in the control cell or in the test cell. 

Conversion lift testing is then taking the total sum of activity that occurred in the test cell and subtracting everything that happened in the scaled control from the test. The only difference between the cells is the spend that occurred on Facebook. Thus, this subtraction shows the incremental impact of Facebook on your business.

Scaled control is an important term as it allows an advertiser to not run tests with a 50% hold out. For example, if an advertiser ran a lift study with a 20% control it would sum all the activity in the control and multiply by 4 to compute the scaled control. 

If 10 conversions happened in the control, then the scaled control would have 40. 


Why multiply by 4? Because the test cell had 80% of the population and multiplying 20% by 4 equates to 80%.


If we assume that the test cell above had 100 conversions then this study produced 60 incremental conversions.





What Does Opportunity Mean?


Technically speaking, conversion lift testing on Facebook is not an A/B test. (Colloquially people tend to use them interchangeably.) With an A/B test, an experimenter takes the results from everyone who was exposed to a stimulus in cell A and compares it to cell B. (Cell B could be a control or have a separate stimulus.)


For conversion lift studies, it is the summation of all activity which occurs in the test cell. Everyone in the test cell has an opportunity to see an advertisement, but not everyone does. 


As exposure is not 100% in the test cell, lift studies are by their nature a conservative measurement tool. Furthermore, incrementality on Facebook does not have to look positive for the platform. We have seen many studies that looked less than favorable for the platform which is one of the best reasons to trust it as a tool.


When choosing Basic Results, Facebook is simply reporting the pixel fires tied to people in the test cell versus those that occurred in the control cell. If you have verified the pixel, then the lift study will be accurate. In short, the veracity of the lift study is controlled not by Facebook but by the advertiser.


Wait, What Are We Studying Again?


One of many pre-test checks we perform at dysrupt is confirming that the question being asked is the one the advertiser wants answered. Whether the holdout is at an account level or campaign level, which accounts are included in the test, etc. all impact the question that the test is asking.


Let us suppose that an advertiser has two ad accounts, A and B. If they place both accounts in the test, then the question they are asking is “What is the incremental impact of Facebook advertising on my business above all other marketing efforts?”



If the holdout is only placed on account A and account B is not included in the study then the question changes. It becomes “What is the incremental impact of activity from Account A on my business versus all other marketing efforts including ads on Facebook from account B?” 


We can suspect that since the control is now exposed to ads from account B, the second version of the study would have a lowered version of incremental impact than the earlier, universal hold out question.

Now What?


We’ll write about how we analyze studies at a later date. After running 257 lift studies for over 30 companies, there are lots of overlooked aspects in the conversion lift UI. One of the largest mistakes we have written about in a previous article. Don’t worry...there are many other nuances to consider. 


We hope this article provides a quick primer of salient features around conversion lift testing. 


And for the non-analytical here is a brief summary of the points.

  • Incrementality is different than an A/B Test
  • Take time to define the question being asked before testing
  • 50% hold outs are not mandatory due to the Scaled Control
  • Incrementality is based on a person’s opportunity to see an ad
  • Lift studies are as accurate as your pixel fires

Reach out to info@dysrupt.com if you ever want to talk measurement around your specific business needs!


* For this article, we will interchange lift, conversion lift and incrementality testing throughout to mean the same thing. 

---

Thanks to Prateek Katyal for sharing their work on Unsplash.




Nate Lorenzen
Founder
Jenner Kearns
Chief Delivery Officer
Jenner Kearns
Chief Delivery Officer
Jenner Kearns
Chief Delivery Officer
Kenneth Shen
Chief Executive Officer
Kenneth Shen
Chief Executive Officer
Kenneth Shen
Chief Executive Officer
Kenneth Shen
Chief Executive Officer
Jenner Kearns
Chief Delivery Officer
Kenneth Shen
Chief Executive Officer
Jenner Kearns
Chief Delivery Officer
Jenner Kearns
Chief Delivery Officer
Jenner Kearns
Chief Delivery Officer
Jenner Kearns
Chief Delivery Officer
Kenneth Shen
Chief Executive Officer
Jenner Kearns
Chief Delivery Officer
Kenneth Shen
Chief Executive Officer
Kenneth Shen
Chief Executive Officer
Isla Bruce
Head of Content
Isla Bruce
Head of Content
Isla Bruce
Head of Content
Jenner Kearns
Chief Delivery Officer
Isla Bruce
Head of Content
Kenneth Shen
Chief Executive Officer
Isla Bruce
Head of Content

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