Case Studies

Real results.
Real enforcement.

Data-backed proof of what structured monetization governance delivers for gaming publishers.

🏆 Featured — 1 Year
Measurement Duration: 12 Months — Report 2025

Business Case Study

A major mobile gaming publisher needed to scale ad moderation across multiple regions and formats. Internal team limitations meant problematic ad categories slipped through, causing player churn and store rating drops.

1.49M
Ads Watched
98,279
Blocked
8.86%
Report Rate
61,467
Reviewed
132K
Reports Filed
27.6%
Gaming Ads #1
AD OPS workflow integrated with zero SDK friction — direct mediation dashboard access only.
Top categories: Gaming (27.6%), Health Hazards (18.1%), Fraud & Scam (12%), Financial (10.1%), Political (7.3%), Gambling (6.8%).
Google Ads was source of 58.4% of problematic creatives. AppLovin 18.2%, Meta 8.9%, Unity 7.2%.
Blocking: Unity 63.5%, GAM 34.7%. Every block logged and validated.
Player retention and store feedback improved measurably after problematic ad frequency dropped.
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📅 6 Months
Measurement Duration: 6 Months — Report 2025

Business Case Study

A six-month mid-year audit for a scaling publisher portfolio. Provides a focused benchmark on recurrence patterns, network enforcement velocity, and the impact of Helpshift ticket closure rates on player satisfaction.

775K
Ads Watched
59,101
Blocked
10.77%
Report Rate
28,396
Reviewed
83,596
Reports Filed
31.1%
Gaming Ads #1
Gaming ads (31.1%), Health Hazards (17.5%), Fraud & Scam (11%), Financial (10.5%), Political (6.9%), Gambling (6.5%).
Google Ads 62.4%, AppLovin 17.2%, Meta 7.3%, Unity 6.69%, Liftoff 6.2%.
Blocking: Unity 60.5%, GAM 38.7%. Moloco, Facebook, Amazon, Pangle among others.
10.77% report rate — 22% higher than the 12-month average, showing stronger early detection.
Helpshift radar showed balanced response times across all 9 tracked networks (35–39 avg score).
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🏆 Featured — 1 Year
Measurement Duration: 12 Months — Report 2025

Business Case Study

A major mobile gaming publisher needed to scale ad moderation across multiple regions and formats. Their internal teams faced limitations in handling the volume and complexity of issues across multiple regions and formats.

1.49M
Ads Watched
98,279
Blocked
8.86%
Report Rate
61,467
Reviewed
132,831
Reports Filed
27.6%
Gaming Ads #1
AD OPS workflow integrated with zero SDK friction — direct mediation dashboard access only.
Top categories: Gaming (27.6%), Health Hazards (18.1%), Fraud & Scam (12%), Financial (10.1%), Political (7.3%), Gambling (6.8%), Healthcare (5.6%), Weapons & Violence (4.5%).
Google Ads: 58.4% of problematic creatives. AppLovin: 18.2%. Meta: 8.9%. Unity: 7.2%. Liftoff: 5.4%.
Blocking: Unity 63.5% (39,062 creatives), GAM 34.7% (21,359). Followed by Moloco, Facebook, Amazon.
Strategic strength: analysis based on 775,962 ads and 83,596 user reports giving statistically significant insights.
Result: player retention improved, store feedback improved, internal teams acted faster and more precisely.
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📅 6 Months
Measurement Duration: 6 Months — Report 2025

Business Case Study

A six-month mid-year audit providing a focused benchmark on recurrence patterns, network enforcement velocity, and the impact of Helpshift ticket closure rates on player satisfaction across a scaling publisher portfolio.

775,962
Ads Watched
59,101
Blocked
10.77%
Report Rate
28,396
Reviewed
83,596
Reports Filed
31.1%
Gaming Ads #1
Top categories: Gaming (31.1%), Health Hazards (17.5%), Fraud & Scam (11%), Financial (10.5%), Political (6.9%), Gambling (6.5%), Healthcare (5.6%), Weapons & Violence (4.7%).
Network sources: Google Ads 62.4%, AppLovin 17.2%, Meta 7.3%, Unity 6.69%, Liftoff 6.2%, IronSource 0.1%, InMobi 0.1%.
Blocking: Unity 60.5% (17,939), GAM 38.7% (11,485). Moloco 61, Facebook 60, Amazon 23, Pangle 18.
Helpshift radar: Liftoff 35, AdMob 37, Amazon 36, Moloco 35, Unity 37, Microsoft 37, Pangle 39, Facebook 38, GAM 39.
Strategic: even a 10.77% rate of bad ads harms perception if not addressed quickly. Governance protects brand loyalty.
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