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Incrementality and Incrementality Testing: A Primer

  • Incrementality is a way to measure ad effectiveness by measuring the lift in desired outcome by comparing two audience groups, one that has been exposed to an ad and another that hasn’t.
  • Incrementality is one of the best ways that marketers can understand the real-world impact that their ad campaigns are having on their business.
  • Viant’s industry leading reporting capabilities help marketers run multiple types of incrementality tests, providing data that can be analyzed to make budgetary and other business decisions

In order to understand the full reach of an ad and how a particular campaign has impacted your brand, incrementality can be incredibly useful.

Incrementality takes a look at positive, negative and neutral impacts of an ad, essentially measuring ad effectiveness. Incrementality measures the lift in desired outcome by comparing two audience groups, one that has been exposed to an ad and another that hasn’t. This helps show the percentage of conversions an ad campaign has created.

With the big emphasis on measurement and proving ROI in marketing today, maximizing one’s budget is more important than ever. Incrementality is one of the best ways that marketers can understand the real-world impact that their ad campaigns are having on their business.

Here’s everything you need to know about incrementality and incrementality testing:

Why is incrementality important for marketers?

For brands, it’s essential to understand whether or not a campaign strategy is working. By utilizing incrementality, marketers can go beyond traditional metrics that sometimes don’t go deep enough to fully gauge the effectiveness of an ad.

Rather than assuming the only reason shoppers have purchased furniture on sale is because they saw a commercial, incrementality looks at the differences in interactions between people who saw a commercial and people who did not. Incrementality identifies which specific interactions led shoppers to attend the sale, in turn making a purchase.

Instead of assigning all credit to the commercial, incrementality provides a baseline for conversions that occurred. Understanding this baseline can help marketers make smart decisions for their businesses and modify strategies as needed to optimize ROI.

What questions can incrementality help you answer?

One of the biggest questions incrementality can answer is whether or not an ad is actually helping to generate revenue, or if revenue comes from unrelated interactions that would have happened naturally on their own.

By answering this question, marketers can then determine an answer as to whether they should increase or decrease the amount of budget they are putting into a specific ad campaign. They can also answer the question of what could happen if a business decides to stop spending money with specific vendors, tools and platforms.

Additionally, incrementality can answer which elements of the ad itself are impacting the desired outcome. For example, is it the talent in the ad? The creative? The placement? Understanding all of these factors and how they intersect can help generate success.

What is incrementality testing?

Incrementality testing evaluates ad spend and measures the impact of your ad. Think of it as an experiment that withholds ad exposure to one group while continuing to run ad exposure for the second group. This data-driven test offers a comparison of conversion rates between the two, essentially gauging how much an ad campaign actually works.

By applying incrementality testing, marketers can calculate how much to increase or decrease ad spend to match what they’re finding in their results. It helps identify a baseline that can then be analyzed to make budgetary and other business decisions.

How do you calculate incrementality?

There are two ways to calculate incrementality. Which you choose depends on the ease calculation for you personally – both will work:

(Test + control) – 1 = Incrementality


(Test – control) + control = Incrementality

With either of these equations, we can see the difference in performance between our control group and test group. Worth noting, these equations are basically also how larger-scale growth is calculated – for example, year over year growth – which makes sense, as incrementality itself is a growth metric.

How do you optimize to increase incrementality?

While you should always be sure to account for variables, there are six key areas that you can manipulate within your campaign to affect incrementality. Think of the below as the category that’s being compared:

Device Delivery:

Evaluate incremental lift for consumer engagement based on which device a video ad drives more actions versus those not exposed to the video ad. For example, viewing the ad on a CTV resulted in more consumer website visits versus the same video ad on desktop, and viewing the ad on either device resulted in more visits vs the control (unexposed to ads).


Test different targeting groups to see which audiences are more responsive to a specific message. For example, a “parents with school-aged children” target audience made more online purchases than a “heavy viewers of Disney Channel” target audience after being exposed to your ad versus non-exposed control groups.


Compare how an image or written message drives incremental actions across audiences exposed to the image or message versus audiences not exposed. For example, if an image of female friends laughing at brunch performs better than an image of a couple watching TV together.


Test your video ad across different publisher categories to see best performers. For example, does your display test ad drive more consumer activity when served on sports or entertainment content categories compared to the control? 


Explore the type of ad format that is best for specific campaigns.  For example, when looking to drive in-store foot traffic, does video or display get better results for your mobile campaign when evaluating test and control results.


Optimize for your best performing channels by testing incrementality of your ad versus control. For example, did the ad outperform the control group on desktop versus DOOH? 

What are incrementality best practices?

1. Understand your control group’s behavior and how the group of consumers exposed to your ad performs relative to it. The true campaign success metric is how a group of consumers exposed to your ad performs compared to your non-exposed control group.

2. Make sure you have a clearly defined hypothesis – for example, a format that will lead to better conversions or a target group that will increase your reach.

3. Use your test results to scale up KPIs – for example, channels, reach, return on ad spend (ROAS), etc.

4. As you receive results, check first to see if they support your hypothesis. If they don’t, adjust your hypothesis based on your learnings and run the test again.

5. Make sure you’re not rewarding undesired consumer behavior, for instance, don’t run so many coupons that your audience will no longer make purchases without them.

6. Ensure you’re accurately measuring incrementality across platforms and devices, as well as getting a holistic view of your audience, by working with a partner that offers an identity resolution solution.

Regardless of which path you choose, incrementality is a smart way to understand how well an ad campaign works and what steps a business should take to drive growth.


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