Maximizing IAP Revenue With Pricing Optimization
summary
A practical framework for setting prices per country and for individual offers, with sequential store tests, monthly adjustments and a three‑month calibration that uses public macro data plus game KPIs and machine learning to predict willingness to pay. Claims: global pricing yields ~20–40% revenue uplifts outside the US; case studies include a casino title and a hidden‑object game showing 10–43% monthly gains, and Jam City’s Harry Potter (optimizing ~50 countries on a $2M+ game). Advice: manage thousands of SKUs, time promotions to prime time and use targeted first‑purchase discounts.
AI-written summary · about
chapters (5)
- 0:00Start
- 3:40Global Pricing
- 11:19Case Studies
- 14:44Personalize the Special Offer
- 19:38First Purchase Discount
related talks
25mDon't do it like a virgin – Automated revenue management in gaming
20mUsers acquired - Now what?: Maximising revenue from existing players
23mThe unreasonable effectiveness of data for better monetisation
31mLevelling up – How to move from a small indie to an established publisher
27mAI-Powered Pricing: Smarter Decisions, Bigger Profits
22mThe Rise of Player-Powered UA: How Incentives Will Shape the Future of Mobile Growth.
18mProduct Management for Optimization
19mHow to Leverage Predictive Analytics to Enhance iOS Marketing Performance