The Pitfalls of Incrementality Testing and Why a Personalized Approach Matters

Incrementality testing is often heralded as the solution to understanding the true impact of marketing campaigns. It isolates the effect of advertising, showing what incremental value your ads add to business outcomes like revenue, conversions, or customer acquisitions. However, despite its benefits, incrementality testing is not without challenges. Missteps in execution or over-reliance on standard methods can lead to inaccurate results, wasted ad spend, and misguided marketing strategies.

In this article, we’ll explore what can go wrong with incrementality testing and how Stella’s personalized approach ensures more accurate, actionable insights compared to traditional one-size-fits-all models.

‍

Common Pitfalls in Incrementality Testing

Despite its appeal, incrementality testing can be rife with challenges. Let’s take a closer look at some key issues that arise when incrementality testing is not conducted with proper care.

1. Neglecting High/Low Price Point Differences

One significant issue with many incrementality tests is failing to account for variations in product price points. Different products have different purchasing cycles. For example, high-ticket items may take much longer to convert compared to smaller, low-cost products. If your holdout group consists of mostly lower-priced products, but your test group includes higher-value items, the results will be skewed.

For accurate incrementality testing, it's essential to normalize price points across your test and control groups. Failing to do so can lead to misleading conclusions about which campaigns are driving true incremental revenue.

2. Ignoring Conversion Lag

Not all customers convert right after seeing an ad. Depending on your industry or product, there may be a significant lag between the time a consumer views your advertisement and when they make a purchase. If your incrementality test doesn’t consider this conversion lag, it could prematurely conclude that an ad isn't effective, when in reality, it just needs more time.

Failing to account for conversion lag is one of the most common missteps in incrementality testing, particularly for businesses with longer sales cycles.

3. Geo Holdout Errors

Geo holdouts are a common tactic in incrementality testing. This method divides geographic regions into test and control groups to measure the incremental impact of an ad campaign. However, if not done properly, geo holdouts can result in faulty conclusions. If regions differ significantly in terms of audience size, demographics, or purchasing behavior, comparing them will not yield accurate insights.

Selecting comparable regions is crucial, but many advertisers overlook these nuances, resulting in incomplete or skewed data.

4. Overlapping with Promotional Periods

Running incrementality tests during promotional periods, holidays, or seasonal sales is another common mistake. Consumer behavior shifts drastically during these times, making it difficult to isolate the true impact of your ad campaign. Holiday surges, for example, may inflate conversion rates in both test and control groups, giving a false sense of campaign success.

To avoid this, advertisers should carefully plan the timing of their tests, ensuring they are not affected by seasonal trends or external promotions.

5. Concurrent Campaigns on Other Channels

One of the biggest challenges with incrementality testing is accounting for concurrent campaigns running on other marketing channels. Channels don’t exist in a vacuum—interactions between them are often what drive the final conversion. If a TV campaign is running alongside a digital ad test, for example, it can be difficult to discern which channel is truly driving incremental results.

Properly controlling for the interplay between channels is key to drawing accurate conclusions, but many tests fail to consider this factor, leading to over-attributing success to the wrong channel.

6. Insufficient Volume and Statistical Significance

Perhaps the most fundamental challenge with incrementality testing is ensuring that the test has enough volume to reach statistical significance. Without a large enough sample size, tests often yield inconclusive or misleading results. A common mistake is to conduct tests with insufficient data, leading to "directional" insights that aren't truly actionable.

‍

Challenges with Traditional Incrementality Testing Approaches

While incrementality testing has significant value, it can often be overly reliant on generic models that don’t account for the nuances of individual businesses. Many companies attempt to use a one-size-fits-all approach, which results in tests that fail to consider important factors such as pricing differences, varying consumer behaviors across regions, and the impact of multi-channel campaigns.

According to a competitor's analysis, incrementality testing can be complex and resource-intensive, requiring careful planning and significant technical expertise. Additionally, external factors—such as seasonal trends or unexpected events—can introduce noise into the data, making it challenging to ensure clean, actionable results. In many cases, incrementality testing is as "directional" as simple surveys, providing surface-level insights that are difficult to translate into meaningful actions.

‍

Why a Personalized Approach is Key

Stella takes a personalized approach to incrementality testing, ensuring that all the complexities and potential pitfalls are accounted for. Unlike the typical, standardized models used by many platforms, Stella's methodology is tailored to each individual business, ensuring that you get accurate, meaningful results that reflect the reality of your marketing efforts.

Custom Test Design

At Stella, we don’t take a cookie-cutter approach to testing. Our team works directly with you to design a test that takes into account factors such as your product price points, geographic differences, and any concurrent campaigns that might affect the results. We also factor in conversion lag, ensuring that we give each campaign the appropriate amount of time before drawing conclusions.

Ongoing, One-on-One Support

Unlike many platforms that rely on automated dashboards and generalized insights, Stella provides ongoing, one-on-one support throughout the entire testing process. We don’t just hand over a report and walk away. Our team is with you every step of the way to help interpret the results and implement actionable changes to your campaigns.

Cross-Channel Analysis

Stella’s methodology goes beyond single-channel analysis, taking into account the interplay between different marketing channels. We understand that channels don’t exist in isolation, and our testing framework reflects this reality. This ensures that your results are comprehensive and accurately reflect the incremental impact of each channel, rather than over-attributing success to one area.

Data Accuracy and Validation

One of the most significant advantages of Stella is our focus on ensuring that your data is clean, reliable, and actionable. We use advanced techniques to control for external factors like seasonality, regional differences, and concurrent campaigns, ensuring that the insights you gain are grounded in reality. We also make sure that your tests have the appropriate volume and duration to reach statistical significance.

‍

Conclusion: The Value of a Personalized Approach to Incrementality Testing

Incrementality testing can be an invaluable tool for marketers, but it’s not without its challenges. When executed poorly, these tests can produce misleading or inconclusive results, leading to wasted ad spend and misguided strategies. Traditional approaches that rely on standardized models often fail to account for the unique variables that affect each business, from pricing differences to cross-channel influences.

Stella solves these issues by offering a personalized, one-on-one service that ensures your incrementality tests are accurate, reliable, and truly reflective of your marketing efforts. By focusing on data accuracy, cross-channel analysis, and ongoing support, Stella helps you unlock the true value of your ad campaigns and make smarter, data-driven decisions.

Ready to discover how Stella can help you improve your incrementality testing and optimize your ad spend? Reach out to us today and see how we can transform your marketing strategy with tailored insights and expert guidance.