Founded in 2015 under the philosophy “Games are a resting place for the heart,” EAGLE is a Tokyo-based game developer specializing in casual and social games. Their flagship title, Piggy Clicker: Idle Farm Tapper, has surpassed 2 million cumulative downloads as of April 2026, a milestone built on a business model that depends almost entirely on in-app advertising revenue.

For a game like Piggy Clicker, the business equation is straightforward: more users mean more ad impressions, which means more revenue. But sustaining that growth cycle requires solving two problems at once: scaling user acquisition while keeping ad monetization efficient. That balancing act is exactly where EAGLE found itself stuck.

For casual games that rely on in-app advertising as their primary revenue source, increasing User Acquisition (UA) volume while maintaining Return on Ad Spend (ROAS) can be a difficult task. EAGLE faced challenges where UA through conventional advertising channels had slowed down, and acquisition volume failed to recover even when ROAS targets were lowered. Furthermore, they faced structural constraints, such as difficulty accessing ad inventory on other platforms and limited delivery to ad slots that reach a broader user base.

"Initially, ROAS was good and acquisitions grew, but the volume gradually dropped," recalls Ryoma Hachisu, President and CEO of EAGLE. "We tried various operational improvements, such as narrowing down delivery targets, but overall, the situation was shrinking".

The deciding factors for EAGLE to adopt Moloco were the high accuracy of its AI and the quality of partnership support. EAGLE has integrated the Moloco SDK to enhance revenue generation and User acquisition.

Optimizing for users that are highly compatible with EAGLE’s advertising revenue model, not for broad IAP behavior
The core insight behind Moloco’s’s approach is a targeting distinction that matters enormously for ad-monetized games. While general-purpose optimization typically targets a broad range of user behaviors, Moloco AI - powered by the Moloco SDK - focuses specifically on high-value users. The system accumulates signals that progressively refine bidding accuracy around the behaviors that actually drive revenue for EAGLE’s business model. 

Accessing inventory that was previously out of reach
By leveraging Moloco's ability to distribute campaigns across multiple networks without being limited to any single platform, EAGLE was able to access ad inventory that had previously been out of reach. This revitalized competition in the auctions their ads entered: more competition meant better pricing dynamics and, ultimately, higher eCPM.

A seasonal budget built around AI learning
Adjusting the timing of our budget allocation in response to market conditions led to the subsequent results.

Working closely with Moloco’s support team, EAGLE made a deliberate strategic call: rather than spending aggressively during the expensive Black Friday through Christmas period, they suppressed budgets across media, used that window to accumulate AI learning data, and then concentrated their budget from December 25 onward when unit prices stabilized.