Media incrementality is by no means a new—or even flashy—analytics practice. That said, as we enter our new cookieless landscape and winning via digital proves more challenging, media incrementality is resurging in popularity and considered table stakes for many brands. Here is our Stella refresher on media incrementality—so that you can better understand how this analytics solution will deliver a clearer understanding of your business drivers, without worrying about the cookiepocalypse.
THE BASICS
The most common way of measuring media incrementality is through control and exposed testing, either via geos or audiences. That said, media incrementality is extremely powerful, allowing marketers to truly understand the impact of their media efforts with observed rather than modelled data on key performance indicators (KPIs) such as sales, traffic, and more. Media incrementality provides a clear picture of how effective media is against sales.
A non-controversial solution, media incrementality is observed, where the user can easily see how a market that has media on differs in a KPI vs a market that does not have media on. Models, by their nature, are hypotheticals; though we can project a very strong level of confidence in a model—typically 80%—there will always be some room for interpretation. Market Mix Models, the gold standard, provide the most comprehensive view of media performance, but require a good amount of historical data. Incrementality does not.
OLDER PRACTICE, NEW LANDSCAPE
As the digital world becomes increasingly cookieless and we lose real-time touchpoint data, media incrementality is regaining popularity, where simple digital attribution solutions are less in favor. What’s more, even when we do have real-time data—from platforms like Meta or Google—it is last touch data—biased data—that does not take all of the touchpoints in a consumer journey into consideration. Media incrementality, on the other hand, does not rely on cookies.
Another reason for media incrementality’s resurgence is technology advancements. With the ability to conduct control and exposed testing within platforms and BI tools, we can now analyze the performance of media exposure versus non-exposure in a relatively real-time manner.
We can also now blend media incrementality with other analytics solutions to create the most effective solution for clients, amplifying deliverables. No analytics solution is wrong—they all have their need state and unique benefits! As an example, we recently worked with a client who was investing significant sums of money into brand search. They wanted to dominate their brand space and ensure maximum visibility. However, the age-old question persisted: would customers still come to them even without investing heavily in brand search? Traditional attribution models failed to provide a conclusive answer due to biased data influenced by user behavior. By conducting media incrementality testing specifically on brand search and feeding the results into an overall attribution model, we were able to provide our client with a more comprehensive understanding of the true impact of their brand search efforts.
UNDERSTANDING THE SCOPE
Setting up the media incrementality test is a meticulous process that requires careful consideration of multiple factors. Our approach involves creating scorecards to ensure that the control and exposed markets or groupings are as similar as possible in terms of historical sales, demand, trajectories, retailer composition, and more. Additionally, we mitigate any external factors such as seasonality, competitor activity, store count, and economic influences to ensure the reliability of the results.
Once the tests are set up and the data is collected over a sufficient period of time, we apply statistical tests to determine the significance of the lift observed in the control market. The results are then fed into BI visualization tools, enabling us to provide our clients with a continuous, real-time understanding of media incrementality. This allows for ongoing optimization based on concrete data.
Media incrementality testing can also be applied within channels, further enhancing our clients' marketing strategies. By allocating a budget specifically for incrementality testing within each channel, we can measure the impact of additional investments and determine whether the returns justify the spend and at what point do the channels hit diminishing returns.
We take our solution a step further than most vendors by then feeding results into our proprietary curve simulation tool called Spark. This way we can determine at various spend levels (beyond what was tested) what expected sales results would be. This approach ensures that our clients do not rely solely on fixed periods of time but evaluate marketing initiatives from an incremental perspective.
THE RESULTS ARE UNDENIABLE
But actually, they are! Ultimately, it is what we understand from the testing that differentiates media incrementality. Especially when proven with statistical testing and results feeding into curve builds, you can plainly see the business impact to business driven by media. What media incrementality delivers is a certified, holistic understanding of the effectiveness of your brand’s marketing efforts—without the need for cookies.
If you are interested in a stronger understanding of what is driving your business—connect with us.
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