I already run UA. Why do I need retargeting?

The average app loses 77% of its DAUs within the first 3 days after install. Without implementing retargeting campaigns, 77% of that app’s UA budget is essentially going down the drain (Appsflyer study).

Do you provide creative services?

We offer custom creatives and custom pre-launch analysis. Our in-house studio can develop ads of any format but specializes in playable and video ads to maximize performance.

Why is retention important to growth?

Users try out a lot of apps but decide which ones they want to stop using within the first 3-7 days. The key to success is to get users hooked during that critical first 3-7 day period, and then keeping them engaged long term.

Measure incrementality faster with Adjusted ROAS

Measuring true lift typically requires controlled tests, holdouts, or audience splits.

Running those tests takes time, coordination, and enough scale to get meaningful results.

Most teams can’t test every campaign, audience, or creative, even when they want to.

New webpage Churn prediction-Purple-Data

Integrates multiple data sources to analyse your app user behaviour.

Calculates churn probabilities for each user using predictive AI.

Adjusts bid prices dynamically using churn scores for optimal allocation.

TRACK ORGANIC RETURN BEHAVIOR

Understand how likely users are to return without being exposed to ads.

Adjusted ROAS uses real-time behavioral data like last app activity and return patterns to model lift without needing a control group.

REFINE REVENUE FOR SMARTER INSIGHTS

Adjust campaign revenue using observed organic return rates.

Apply it at the audience level for a faster read, or go deeper with user-level precision when needed.

REVEAL TRUE CAMPAIGN IMPACT

Adjusted ROAS helps you estimate which conversions were likely driven by your ads, and which weren’t.

It gives you lift-based insight without the time and scale requirements of a full incrementality test.

SPEND MORE EFFICIENTLY

When you can’t test everything, it’s hard to know where to shift budget.

Adjusted ROAS helps identify campaigns that are more likely to drive incremental impact, so you can focus spend where it counts.

MAKE FASTER DECISIONS

Testing requires setup, coordination, and waiting for results.

Adjusted ROAS gives you modeled insights using live behavioral data, so you can evaluate performance quickly and act with more confidence.

EXPAND HOW YOU MEASURE LIFT

Incrementality testing delivers high-quality insights, but only for what you test.

Adjusted ROAS brings that same lift logic to a broader set of campaigns by filtering for likely organic behavior using real return data.

SCALE SMARTER

Incrementality testing gives you truth. Adjusted ROAS helps you act on it more often.

Use it to expand impact-driven measurement beyond one-off experiments so you can scale based on modeled lift, not assumptions.

faqs

Can Adjusted ROAS replace incrementality testing?

Not completely. Incrementality testing is still the most reliable way to measure true causal impact.
However, Adjusted ROAS helps you apply that same mindset across more campaigns without the time and resource requirements of a full test.

Do I need to test all the time?

No, constant testing isn't necessary. Running periodic uplift or incrementality tests is still the best way to validate your strategy and understand true causal impact. Between those tests, Adjusted ROAS gives you a way to apply that thinking more regularly. It doesn't replace experimentation, but it helps you make smarter decisions day to day using modeled insights grounded in real behavior.

What's the difference between incrementality testing and adjusted ROAS?

Incrementality testing measures true causal impact through experiments. This usually means setting up control groups or holdouts to see what happens when ads aren’t shown. It’s the most rigorous way to isolate lift.

Adjusted ROAS, on the other hand, uses behavioral data to estimate impact without running a test. It looks at organic return patterns to help remove conversions that likely would have happened anyway.

The key difference is that testing proves impact through design, while Adjusted ROAS models it through data. Both help you get closer to the truth: one through experiments, the other through ongoing analysis.

How does Adjusted ROAS know which conversions are incremental?

It looks at how users typically behave when they aren’t exposed to ads. For example, it considers when someone last opened the app and how likely they are to return on their own. This helps estimate how much revenue is truly ad-driven.

Does this work for small apps too?

Yes, especially for teams that don’t have the bandwidth to run full incrementality tests. It provides a practical way to estimate lift using real behavioral data, helping you make informed decisions without the overhead of setting up and managing experiments.

Is it suited for all audiences (active & inactive users)?

It’s most relevant for users who are recently active, since they’re more likely to return on their own. For inactive users, where organic return is rare, there’s less need to adjust the data. In those cases, raw performance is often close to the incremental impact.

OUR CHURN MODEL

why you need a Smarter way

to measure incrementality

SOLVE THE USER CHURN PUZZLE

Enter adjusted ROAS

what you see is what you get

faqs

We ran Incrementality

before it was cool