Measure the Success of App Retargeting with AppsFlyer’s Incrementality Feature
We set out to tackle an important challenge: helping advertisers identify the value of their next marketing dollar to drive incremental growth and justify their investment.
Simply put, incrementality is a reflection of the added value gained from your re-engagement activity, whether acquisition or re-targeting. What will my performance look like if I run re-engagement ads vs. not running any at all?
What’s even harder to break down and measure is the incremental impact with so many influencing factors. At the end of the day, what marketers are interested in is whether running any given re-engagement campaign will generate revenue that would otherwise not be generated.
Let’s imagine an A/B test scenario for a food delivery app: your goal is to understand the optimal time after install to re-engage new users and convert them to paying users. The hypothesis? Retargeting campaigns executed 3 days post-install will result in a higher volume of converted paying users than waiting to retarget 7 days post-install.
Once the test ends, the marketing team analyzes results and concludes that campaigns targeting users 3 days post-install show a much higher conversion rate than those retargeting campaigns running 7 days post-install.
What the marketers running this test failed to implement is a control group. Why is the control group critical here, you may ask? It’s critical because it would provide a performance benchmark for what may have happened to those users naturally had they not been served those re-engagement campaigns. In other words, in the above scenario, a segment of app users should not have been exposed to either of the re-engagement campaigns (3 days or 7 days post-install).
Comparing the analysis results to the ‘constant’ (no change in environment for the app users) would produce the true incremental impact of running re-engagement activity on top of existing efforts. Only then can the marketers obtain the full results they need to optimize their budget accordingly.
A control vs. test analysis would have concluded that the assumption of higher conversion rates 3 days post-install was only true because there are already converting users within that pool that would have become paying users regardless of re-engagement campaigns 3 days after the install.
As suggested by our example, Incremental analysis is particularly important when it comes to measuring retargeting campaigns, since these users are already engaged with your app, and therefore are more likely to engage again, organically. How can marketers then know whether their paid retargeting efforts are worth the price of these same users are likely to convert again on their own?
The only way to justify pouring additional funds into re-engagement efforts is by testing their lift.
And that is pivotal for two goals:
- To understand the true ROI from marketing campaigns, enabling marketers to correctly attribute the source of performance growth.
- To optimize cross-channel performance and make informed decisions on the next marketing dollar spent.
Where Attribution Meets Incrementality
While you may already know which of your retargeting networks performs best, it is still crucial to understand the incremental value that each new partner brings on top of your existing partner networks, as well as additional engagements driven by push and email campaigns. In a world where users are being exposed to multiple retargeting campaigns, and at increasingly different touchpoints, advertisers need a tool to decipher incrementality. Conversion funnels were once simple (click-to-purchase), but are now a complex multitouch play requiring sophisticated attribution data to truly understand the user journey.
AppsFlyer’s Incrementality Feature
As an unbiased attribution provider, AppsFlyer holds a critical role in deciphering incrementality. With all data touchpoints funneling into one central place, it gets significantly easier to understand the incremental lift of each individual network or campaign and its contribution to your KPIs.
If you are thinking of venturing out to A/B test or have already started the process and feel overwhelmed, don’t worry, you are not alone. AppsFlyer’s Audiences tool is here to help. The set-up of any test is both time consuming and resource-draining. We have seen many experienced BI teams struggling with data preparation; pipelining processes that are required to run such tests; finding users that share similar traits over extended periods of time, randomizing the data into test and control groups; or even building custom API connections with each retargeting network.
With AppsFlyer providing the tools to support the technical side of executing A/B tests, developers are free to invest in creating the organization culture and processes that are required for running effective and scalable testing.
The focus on retargeting has grown dramatically in recent years, across all mobile verticals (shopping being the leader). With retargeting budgets growing massively, understanding the impact of your retargeting program is necessary for justifying scale. Additionally, personalization is a key goal for digital marketers today; marketing to specific audiences, controlling how many times users see an ad within that audience, what that message will be, with the notion that those users are constantly moving along the conversion funnel and engaging with different touch-points along the way. With a people-based attribution approach, the ideal scenario is keeping messaging personalized, coherent, and consistent. Measuring performance in a siloed manner won’t work if we look forward to the future. Naturally, this leads to the importance of understanding the incremental impact across the entirety of your re-engagement program.
Luckily, AppsFlyer is unlocking measurement solutions for incrementality testing in order to help advertisers connect the dots and zero in on what’s truly driving growth.
Check out Part II of Incrementality Testing with AppsFlyer.