04Case history

Confidential Dossier.

Due to the competitive sensitivity of live product metrics, ad network setups, and analytics pipelines, full outcomes and diagnostic details are shared directly with qualified studios, founders, and product leads rather than published openly. Read the public operator case →Request references

PUBLIC OPERATOR CASE · MEDIATION

Rebuilding a live mediation stack from waterfall to bidding.

The exact revenue movement remains confidential. The architecture, operating problem, and decision sequence do not need to be.

Problem

A mature, ads-led mobile games portfolio was operating through waterfall-era assumptions while the market moved toward in-app bidding. Adding more demand without changing the auction structure would have created more configuration, not necessarily better competition.

Approach

The mediation layer was rebuilt across AppLovin MAX and ironSource LevelPlay. The work connected bidder coverage, waterfall fallbacks, placement behavior, QA, reporting, and partner ownership so the migration could be judged as one revenue system.

Outcome

The live portfolio moved from waterfall to bidding without turning the migration into a sequence of isolated network changes. The durable outcome was a new architecture and operating cadence for reviewing auction quality, fill, latency, and player impact together.

Implication

A mediation rebuild is not complete when the SDK is live. It is complete when teams can explain where impressions clear, why fallbacks exist, which placements behave differently, and what signal should trigger the next change.

Operating context 575M+ downloads85% ads / 15% IAP at portfolio peakAppLovin MAX + ironSource LevelPlay
CONFIDENTIAL RESEARCH FILE

These cases sit on 15 years running mobile game growth at scale: 575M+ downloads, $38M+ in revenue managed, and a mediation stack rebuilt on AppLovin MAX and ironSource LevelPlay from waterfall to bidding. I've led diagnostic and systems interventions across monetization, analytics frameworks, and UA pipelines. Common case profiles I share in discussion:

PROFILE 01 · ATTRIBUTION

Re-attributing Cohort ARPU

Rebuilding multi-channel tracking to resolve duplicate attribution reporting, redirecting UA budget from low-LTV sources to profitable cohorts.

PROFILE 02 · MONETIZATION

Genre-Specific Revenue Mix

Optimizing hybrid ads and in-app purchase offers across a high-scale casual portfolio based on audience-specific session pacing.

PROFILE 03 · SYSTEM

Bid Optimization & LTV

Connecting campaign acquisition cost to downstream retention and LTV curves, replacing CPI-led bids with target-ROAS decisions.

THE GAME SCIENTIST · DATA INTEGRITY APPLIED
05References

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