Whales in the wild: What big data reveals about the biggest game spenders
summary
Slice Intelligence uses a 5M-person panel and 9M anonymized purchase receipts to analyze ~500K mobile spenders across 4,000 titles and finds 16% of users drive 80% of revenue. The team builds a “whale net score” and clusters spenders into 59 species (4 families) by demographic and cross‑game purchases, proving high whale-dependence correlates with revenue. Actionable metrics are stickiness and share-of-wallet; target low‑to‑mid loyalty but high stickiness via cross‑game UA (product: Amplify).
AI-written summary · about
chapters (14)
- 0:00Intro
- 0:30Three questions
- 2:21The data
- 3:35Will net score
- 6:21Is wellness important
- 6:42Species of whales
- 7:14Support whales
- 8:16Blue whales
- 9:32Casino whales
- 10:05Casual whales
- 10:25Gender breakdown
- 12:23Whale analogy
- 16:14Low achievers
- 16:32Booth
related talks
49mData Science in Gaming
34mData Science Challenges in the Mobile Games Industry
21m80% data, 20% luck – How to make profitable games in 2019
34mSuperstar Session: The State of Mobile Gaming 2020
30mOptimizing Mobile Game LiveOps with Data-Driven Decisions
58mData-Based Decision Making Throughout Your Game's Lifecycle
24mUser analysis for premium games in China
39mCurated Panel: Billion Dollar Secrets: Games That Never Die.