Analytics

Unlocking Insights: The Power of Incrementality Testing

Learn what incrementality testing is, how it works, and how you can use them.

Unlocking Insights: The Power of Incrementality Testing

Kayle Larkin

Head of Marketing

Are your paid advertising campaigns effective? Conducting incrementality tests can help you strengthen your ad campaigns and understand the impact of your marketing efforts.

Incrementality testing is the umbrella term for multiple types of tests that measure how aspects of your marketing strategy and ad campaigns resonate with your customers and drive conversions — or don’t.

In this article, you will learn:

What Is Incrementality Testing?

Incrementality testing is a valuable tool for measuring how certain elements of your marketing strategy affect user behaviors.

In an incrementality test, there is a control group and a test group. The control group serves as the baseline for your test. The test group is the segment of users who are subject to the variation of your incrementality test.

Both groups are randomly selected and will have different experiences when being exposed to — or intentionally withheld from —  your paid ads for the length of the test.

The variation or variations between what the control group experiences vs. what the test group experiences depend on the type of incrementality test you’re running (more on that below).

When your test is complete, you can compare the data from the test group against the control group data to see the incremental difference.

Ultimately, the results of the incrementality test allow you to measure how the different experiences affected each group’s behaviors.

Types of Incrementality Testing

These are types of tests or experiments that fall under the umbrella of incrementality testing:

Lift tests

Also known as a lift study, lift testing involves intentionally withholding an ad, ad campaign, or ad series from your control group and exposing your test group to the ad or ads.

Lift tests give you a way to measure how effective your ads are at driving conversions within your target audience. There are different types of lift tests, which include conversion lift tests, channel lift tests, and brand lift tests. Explore more information about lift testing.

Split tests

Split tests are also called A/B tests. You can use split testing to help you identify who your target audience is and how they behave by comparing their responses to two versions of an ad, ad set, or ad campaign.

In a split test, there is only one variation between the ad or ad campaign each audience sees. In some split tests, the ad or ads are the same and the audience segment or demographic is the variant (this is how you can use split tests to find your target audience).

While this may sound similar to lift testing, the primary difference is that you don’t intentionally withhold a group from seeing your ads in a split test. Get the details about split testing.

Multivariate testing

As the name implies, there are multiple variations between the ad or ads that are displayed to the test group and the control group in a multivariate test.

These multiple variations in a multivariate test are what sets this type of experiment apart from split testing.

Multivariate tests are the solution for discovering how your audience responds to types of an ad or ads that are significantly different.

Example of Incrementality Testing

Let’s say an e-commerce company wants to start running paid ads on Meta to promote a new product category.

Since they have not run paid ads on Meta before, they want to see the incremental impact these paid ads have on driving online purchases compared to a scenario without the ads.

These are some steps the company may take to run their incrementality test:

  1. They determine the hypothesis. In this case, they hypothesize that their audience segment who sees the paid ads will purchase at a higher rate than the audience segment who doesn’t see the paid ads.
  2. They establish a pre-campaign baseline. The e-commerce company measures the average daily revenue from online purchases over a period of time before the paid ads campaign starts.
  3. They divide the target audience into two groups: the test group and the control group. The test group is exposed to the paid ads during the campaign, and the control group is not. Keep in mind that the test group and the control group are similar in terms of demographics.
  4. They run the test. They deploy the paid ads on Meta with only the test group being exposed to the ads.
  5. They collect data. The company tracks and records daily revenue from online purchases from both the test group and the control group during the campaign period.
  6. The test concludes and they complete the analysis. The e-commerce company runs the test for 30 days and compares the average daily revenue generated by the test group to the control group.

By calculating the difference in revenue between the two groups, they are able to see the incremental impact the paid ads had on revenue growth.

In this example, the e-commerce company sees that the revenue total for the test group is significantly higher than the control group.

Based on this information, they determine the paid ads on Meta are effective and decide to continue investing in paid ads on this platform.

How to Run Incrementality Tests

How you run an incrementality test will depend on the type of test you’re running.

Incrementality testing is an umbrella term for the multiple types of tests or experiments you can use to measure the impact of your ad campaigns.

The way you’ll conduct an incrementality test also depends on the platform you’re running it on.

For example, Google provides a Brand Lift option, which is a free tool that allows you to optimize your video ad campaigns in Google.

Brand Lift in Google can give you insight into your video ad campaigns in terms of ad recall, brand awareness, and customer consideration.

To take advantage of Brand Lift in Google, contact your Google account rep. Find more details about Brand Lift.

Another example is running lift tests on Meta.

Meta has a Channel Lift test that can help you measure the incremental impact advertising on Facebook and other Meta platforms has on your business’s other paid and organic channels.

You can participate in a Meta channel lift study by enabling the Channel Lift event in your Elevar account, and then by working with your Meta account rep to run the test.

Why Incrementality Tests Are Important

Running an incrementality test can be the key to unlocking insights about your advertising effectiveness and overall marketing strategy.

Incrementality tests can tell you:

  • Who you should be putting your ads in front of.
  • The type of creative that resonates with your target audience.
  • Whether to start, stop, or continue certain ad campaigns.
  • Which platforms or channels allow you to reach more customers.
  • The best location for placing your ads within a given platform.

This isn’t an exhaustive list. The benefits of incrementality testing are vast and vary from one type of test to another.

Ultimately, incrementality tests are important because they can help you make informed decisions about your advertising budget and shape future strategies for your marketing initiatives.

Continuously iterating on the incrementality tests that you run can help you maximize your return on investment, or ROI, and drive growth for your business.

Final Thoughts

In all their forms, incrementality tests are powerful tools for seeing the true impact of your marketing efforts.

Running incrementality tests can guide you to making more effective decisions and bolster your advertising strategies.

If you have questions about incrementality testing or need help solving a data tracking challenge, we’re here to help. Contact our expert Analysts for reliable support.

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