The attribution setup behind a $3M ARR subscription app portfolio

With paid acquisition at the center of its growth strategy, this subscription app publisher needed more than install attribution. The team needed to understand which campaigns were bringing in users who actually subscribed, generated revenue, and justified more budget.

Today, the company has reached $3M ARR, runs acquisition across dozens of markets, and measures its paid traffic through Adapty Attribution.

For the founder, Adapty has become something even more important than an analytics dashboard.

It is where daily user acquisition decisions happen.

The company started as a small operation.

The founder spent more than two years building and launching subscription apps, initially alongside a full-time job and later as his primary focus.

As paid acquisition started working, the challenge has shifted.

Getting installs was no longer enough.

The team needed to answer much harder questions:

• Which campaign is bringing users who actually pay?
• Which country is profitable?
• Which campaign should get more budget today?
• Which campaign should be stopped before it burns more spend?

And most importantly, can those decisions be made using actual subscription outcomes rather than modeled acquisition data alone?

For a subscription business, there is often a delay between acquiring a user and understanding their real value. A campaign can generate cheap traffic and still be a poor business decision if those users do not start trials, convert to paid subscriptions, or retain.

The team needed to find a way to connect acquisition directly with subscription performance.

The company found its strongest growth motion in web-to-app campaigns.

A user sees an ad, clicks through a tracked web flow, reaches the product, installs the app, and eventually starts a subscription.

Adapty Attribution connects those steps back to the original acquisition source.

Instead of looking only at ad-platform reporting, the team can understand which campaign brought the user and connect that acquisition data with subscription events inside Adapty.

That changed how the team approached paid acquisition.

This became particularly important as the company expanded acquisition across many countries simultaneously.

A campaign performing well in one market does not mean the same economics would work somewhere else.

With campaign and subscription data connected, the team could evaluate markets independently and scale based on actual business performance.

Adapty Attribution gave the team a single view of the metrics that mattered for subscription growth.

Instead of separating acquisition data from monetization data, the team could evaluate campaigns using spend together with downstream subscription performance.

The workflow became straightforward:

1. Launch new campaigns and creatives.
2. Attribute acquired users back to their campaigns.
3. See which campaigns generate trials, subscriptions, and revenue.
4. Compare performance across countries and time periods.
5. Increase spend for the profitable campaigns.
6. Reduce or stop campaigns that are not working.

This feedback loop made it easier to move from simply acquiring users to acquiring users with sustainable economics.

The company used the same approach not only to scale its first successful product, but also when launching and testing additional subscription apps.

The strongest indication of how deeply Attribution became part of the company’s workflow is how often the founder uses it.

He is personally responsible for marketing and opens Adapty throughout the day to monitor campaign results.

One of the first numbers he checks is Ad Profit.

• Is acquisition profitable today?
• Which campaigns should be reduced?
• Which ones can be scaled?
• Where should the next dollar of budget go?

For these questions, Adapty became the primary decision-making interface.

A sophisticated attribution setup can quickly become another infrastructure project.

That was not what the team wanted.

During the initial Adapty Attribution implementation, the founder worked directly with the Adapty team to configure the necessary setup both inside Adapty and on the advertising side.

The initial integration was completed during a working session, with additional questions handled as they came up.

For a small and efficient team, that mattered.

The goal was not to become attribution experts.

The goal was to start running campaigns and make better growth decisions.

As the company improved its acquisition operation, paid traffic became a major growth engine.

The publisher continued launching new products, testing new categories, expanding into more countries, and applying the same attribution-driven approach to its portfolio.

Today, the business has reached $3M ARR.

The founder is clear that product-market fit, creative execution, market selection, and the team’s own work all contributed to that growth.

But he also sees Adapty Attribution as one of the core tools that made scaling paid acquisition possible.

Scaling a subscription app through paid acquisition is not just a traffic problem.

It is a feedback problem.

Growth teams need to know which campaigns bring users who trial, subscribe, generate revenue, and eventually pay back their acquisition cost.

Adapty Attribution connects acquisition data with the subscription data already living inside Adapty, giving teams a clearer view of where revenue actually comes from.

For this publisher, that visibility became the foundation for daily campaign decisions and helped support the journey to $3M ARR.