Don't do it like a virgin – Automated revenue management in gaming
summary
Claims a 50% uplift in IAP revenue by deploying automated revenue management that uses machine learning, predictive analytics and deep data pooling. Describes a platform that ingests store purchase histories, sets dynamic pricing per consumer and per-country (example: suggested 16¢ vs $0.99), creates bundles, and adds a visual loyalty overlay via an SDK with 30+ tactics. Pilots report doubling revenue, Russia tripling free-to-bill, Italy +66% on an item and retention rising from 32% to 46%.
AI-written summary · about
chapters (10)
- 0:00Intro
- 0:45Market overview
- 1:30Why is this important
- 2:23Model Nationals
- 5:22The Problem
- 9:00Dynamic Pricing
- 10:11Readjusting Pricing
- 11:46InGame Economics
- 15:15Loyalty
- 19:53Questions
related talks
25mMaximizing IAP Revenue With Pricing Optimization
17mHow AI automation increases games IAP LTV by 25%
20mUsers acquired - Now what?: Maximising revenue from existing players
37mAd Monetization, IAP, Subscription Model – What is the Future of Monetization?
16mAI that boosts in-app purchases and monetisation
29mFuture-Proofing Monetization: AI-Driven Subscription Management with RevenueCat's Ecosystem
24mMastering AI Pricing
27mAI-Powered Pricing: Smarter Decisions, Bigger Profits
