Value vs. Volume: how a US sportsbook achieved 4.7x more net deposits in 90 days

A leading US sportsbook had no shortage of traffic. It had no shortage of installs either. What it lacked was any way to connect those installs to actual revenue.

Without that connection, acquisition was a guessing game. Partners were paid for volume. Budget followed clicks. And the players those clicks produced — their deposit behavior, their repeat activity, their real economic value — remained invisible.

When the operator integrated AppsFlyer with Intelitics, the guessing stopped. Within 90 days: net deposits grew 4.7x, average deposit value per qualified depositor increased 177%, and 73% of traffic was eliminated as low-value and low-intent. Not because spend was cut. Because for the first time, the operator could see exactly which acquisition paths were worth funding — and which weren't.

The problem: volume without value

Before Intelitics, the operator's acquisition stack was built around activity, not economics.

Creating and deploying tracking links required engineering resources — a process that took days to weeks on top of an already full workload. Performance data was fragmented across multiple systems, producing an incomplete and inconsistent picture of what was actually happening. Partners were evaluated on installs. Budget followed install volume.

The deeper problem: the operator could see that users converted. It could not measure how valuable those users were. Deposit behavior, repeat activity, long-term player value — none of it was connected to the acquisition source that produced it.

The result was an acquisition strategy optimized for activity, not economic return. High install counts looked like success. The revenue picture told a different story.

The stack: AppsFlyer + Intelitics

AppsFlyer handled install attribution. Intelitics handled revenue and player value. Together, they closed the gap between the two.

The integration works through a persistent identifier. Intelitics generates a unique Click ID for every user interaction. That ID travels through AppsFlyer during attribution and stays linked to the user throughout their lifecycle. As deposit events occur, Intelitics captures them and connects them back to the original acquisition source.

The result: every install has a revenue trail. Every acquisition source can be evaluated on what it actually produced.

This integration gave the operator three capabilities it previously lacked:

• Connect installs to actual deposit value
• Track repeat deposit behavior over time
• Attribute revenue at the partner, site, page, and placement level

How the data flows

With AppsFlyer and Intelitics working together, acquisition data moves through a closed loop with no gaps between click and deposit:

1. A user clicks a tracked link generated by Intelitics, which assigns a unique Click ID
2. The user installs the app; AppsFlyer captures the install event
3. The Click ID is passed through AppsFlyer and associated with that install
4. As the user deposits and engages, those events are captured and returned to Intelitics
5. Intelitics links cost and attribution data back to the original acquisition source

Every signal — from click to deposit — is connected in one system. No black boxes. No gaps. Full visibility into how traffic translates into revenue.

That visibility turned acquisition from a spend-and-hope exercise into a continuous optimization loop. Low-value traffic was removed. High-performing cohorts were scaled. Every decision was grounded in actual economics.

From partner level to cohort-level intelligence

With installs and revenue unified, the operator moved beyond surface-level partner performance into something more useful: cohort-level intelligence.

Instead of asking which partner performs best, the operator could now ask which specific acquisition paths within each partner drive the highest-value players. The answer was almost never obvious. High-volume sources frequently produced low-value users. Smaller, lower-traffic segments often generated disproportionately higher deposit value.

This granularity also exposed a flaw in how partners were compensated.

Under a cost-per-instll model, partners were incentivized to drive volume. Maximum traffic, regardless of quality. The numbers below illustrate the problem:

The results: 90 days

The impact was measurable and fast.

Traffic dropped 73%. Click volume fell from 22.2 million to 5.95 million — a deliberate reduction as low-intent sources were removed. Less traffic. Better traffic.

Net deposits grew 4.7x. Despite the traffic decline, net deposits increased 366%. Fewer clicks, significantly more revenue.

Click-to-FTD conversion improved 5.5x. Conversion rates moved from 0.009% to 0.050% — a direct reflection of higher-quality traffic reaching the funnel.

Average deposit per qualified depositor increased 177%. Value per depositor rose from $1,581 to $4,388. Not just more depositors — substantially more valuable ones.

By eliminating inefficient spend and concentrating budget on acquisition paths tied to real revenue, the operator improved CAC, LTV, and unit economics simultaneously.

Key takeaways

This implementation did more than improve performance, it fundamentally changed how acquisition decisions were made. By connecting install attribution data to revenue and cohort-level signals, the company optimized acquisition around actual player value, not installs. This unlocked several critical capabilities:

• Install → Revenue Connection
  Acquisition sources could now be evaluated based on the revenue they generated, not just installs or conversions.
• Deposit Visibility
  Full visibility into deposit activity, including repeat behavior and player value, enabled a deeper understanding of user quality.
• Cohort-Level Insights
  Performance could be analyzed at the partner, site, page, and placement level, revealing which specific acquisition paths drove value.
• Revenue-Based Optimization
  Budget allocation shifted from volume-based metrics to deposit value and long-term player economics.
• Faster, More Confident Decision-Making
  With a unified view of performance, the company could quickly identify inefficiencies, eliminate low-value traffic, and scale what was working.

This transformed the acquisition function from a fragmented set of tools into a unified marketing intelligence system that continuously informs and improves decision making.

See what your acquisition data is hiding

Intelitics is deployed through a structured process from setup and integration, to validation and launch with a solid team to get you to the finish line in just a 3-4 weeks. Here’s what you can expect in our implementation process:

1. Kickoff & Requirements – Align on tracking setup and technical requirements
2. Instance Build & Integration – Configure tracking, data flow, and revenue events
3. Domain & Infrastructure Setup – Implement DNS records to enable secure tracking
4. Testing & Validation – Ensure attribution and event tracking are accurate
5. Launch – Activate postbacks, onboard users, and begin optimization

If you’d like to learn more about how Intelitics’ marketing intelligence system can uniquely optimize your acquisition strategy, book a demo here.