Attribution, incrementality, and MMM: The next-gen mobile marketing measurement triad

In the ever-evolving world of mobile app marketing, one thing remains constant: The need for accurate and insightful measurement. As mobile marketers, you've likely been well-versed in traditional attribution models; but radical shifts in the industry, driven by privacy changes and the increasing need for aggregated data, are pushing us to explore next-gen measurement methodologies.

Let’s explore the interplay between incrementality, media mix modeling (MMM), and traditional attribution in the context of mobile app marketing. We’ll take a look at how these methods are shaping the future of measurement and how you’ll see the most strategic success from finding the perfect balance between them.

To develop a robust measurement suite that encompasses everything from short-term actionable insights to long-term strategic planning, app marketers are transforming their tech stacks to encompass solutions for the following three key measurement methods:

1. Attribution: The process of matching the source(s) of an install or specific event to give accurate credit to the marketing effort(s) and/or channel(s) responsible.
2. Incrementality testing: An assessment of the measurable impact of a marketing initiative on specific key performance indicators (KPIs) such as installs or in-app purchases (IAPs) compared to baseline, organic performance.
3. MMM: A data science-driven statistical analysis used to forecast the influence of marketing initiatives on a company's return on investment (ROI) by incorporating evaluation of external factors and offline activities with digital marketing efforts.

So how do attribution, MMM, and incrementality interact, exactly? In essence, these three measurement approaches complement each other. Attribution provides immediate insights, incrementality helps optimize mid-term strategies, and MMM empowers long-term strategic decisions.

Let’s imagine you've been measuring your user acquisition (UA) campaigns with multi-touch attribution (MTA). You track user interactions with your ads and app across various touchpoints. For example, perhaps a user first sees your ad on Instagram, clicks the ad, visits your app store listing, later sees one of your display ads on Google, and then installs your app. With MTA, each touchpoint is assigned a level of value depending on the model you are using. Your analytics show the specific journey of this user and the impact of each digital touchpoint on the end conversion.

Now, consider the same user acquisition campaign, but using the triangulation method. You not only analyze the user's journey but also factor in external influences. For instance, you consider the impact of a competitor’s campaign or your offline marketing efforts. Additionally, you run incrementality tests to determine the actual, causal relationship between your marketing efforts and conversions.

Getting a bigger picture with these methods allows you to answer questions like:

• Was the install actually due to your organic app store optimization (ASO) efforts?
• Did seasonality play a role in the conversion?
• If there was a positive incremental lift, was the amount of impact worth the investment?
• Did media attention about a competitor impact your campaign’s engagement?
• Were your offline marketing efforts a contributing factor to your digital campaign’s success?

Think of the triangulation method as baking. While you might reference a recipe as your foundation, you will still factor in external variables like altitude, kitchen temperature, and individual oven nuances. Just as bakers adapt recipes based on their environment to achieve the perfect bake, mobile marketers employ MMM to optimize campaigns with context from external factors.

As you develop your own recipe, you may start with that tried and true recipe as a foundation, and look to make your own improvements. You’ll taste the batter at various stages to determine if it's too sweet, too salty, or if any other adjustments to the ingredients are needed. Ingredient adjustment is a mobile marketer’s incrementality testing. Which ingredients are positively or negatively impacting the bottom line? Which are having no impact at all?

In both cases, the goal is to optimize outcomes. Bakers want a perfectly risen cake, while mobile marketers aim for the most effective use of their advertising budget. By factoring in external variables [MMM] and internal adjustments [incrementality] a more accurate and tailored result is made possible.