Market Research for Game Developers
- 1. White Nights 2019 Benjamin Nolan & Lauren Fitch Advanced Mobile Market Research
- 2. Intro What are we doing here again?
- 3. What are we looking to cover today? ● What kinds of data are available about the market, and what do they tell us? ● How can we combine this data to inform our decision making? ● How far can one go with market research? @prioridata / @bnolan0
- 4. Who is this guy?
- 5. What’s Priori Data? 5 ...and what’s a Priori Data?
- 6. MOBILE MARKET INTELLIGENCE • 4.5m Apps + Games • Downloads, IAP $, Install $, MAU, DAU, D1,7,30 retention estimates, etc. • Country-level breakouts • Years of historical data: daily, weekly, monthly, quarterly time periods • Daily data refresh • Export any view/aggregation of data to CSV/Excel 6@prioridata / @bnolan0
- 7. Why is market research important? 7 ● Priori started tracking 18k new games in last 30 days. ● 729 made 10,000+ downloads ● ≈4% experienced short term success ● In 2018, using YTD data, we see ≈183k launches ● Of those, 3.8% managed 100k downloads ⇒ Many fail, therefore building high quality product with a market fit is key @prioridata / @bnolan0
- 8. What goes into Market Research?
- 9. Well, if you’re Facebook…. 9@prioridata / @bnolan0
- 10. But if not…. 10@prioridata / @bnolan0
- 11. What are we trying to do? 11 ● Shorten time to success ● Know where to focus ● Reduce chance of failure ● Reduce time/budget burn @prioridata / @bnolan0
- 12. Worked Example
- 13. What assumptions are we making? 13 ● We’ve got a great idea for a Zombie game, but want to understand what genre works for us ● We’re monetizing primarily via IAP (In-app Purchases) ● We’re looking primarily at Apple and Google (no data for Amazon, etc) @prioridata / @bnolan0
- 14. How do we do this? 14 ● We find out which markets are most likely to provide ROI, and focus on them ● We know which markets are most likely to be very difficult to win in, and focus less on them @prioridata / @bnolan0
- 15. How can we look at markets? 15 ● Size ● Revenue Potential ● Cost Per Install ● Concentration ● Average retention / stickiness ● etc @prioridata / @bnolan0
- 16. Market size (demand) - Subcategories 16@prioridata / @bnolan0
- 17. Revenue Potential (IAP) - Subcategories 17@prioridata / @bnolan0
- 18. Cost of UA 18 Data via: @prioridata / @bnolan0
- 19. Market Concentration 19@prioridata / @bnolan0
- 20. How can we put this all together? 20 ● Build a model to understand market difficulty ● Build a model to understand market opportunity ● These are early versions - still much more to be done, and I’m sure there are already studios out there doing even more advanced stuff, given some of the questions we get from our API clients. @prioridata / @bnolan0
- 21. Opportunity Model v1.1 - Categories 21 RPG - High opportunity, low(er) difficulty @prioridata / @bnolan0
- 22. Ok, so we have our category - what next? 22 ● We need to think about testing, translations etc ● Therefore we need to think about which markets make sense for us ● We can do a country level version of the opportunity vs difficulty model ● Obviously there are other considerations for this - for further reading, check out Matej’s video on global launching @prioridata / @bnolan0
- 23. Opportunity Model v1.1 - Region Level 23 High opportunity - crazy monetization from JP,KR @prioridata / @bnolan0
- 24. Opportunity Model v1.1 - Country by region Level 24 Relatively high delta between ARPDL + CPI, but high market concentration @prioridata / @bnolan0
- 25. What’s in store for V1.2, 1.3... 1.n 25 Integrate launch velocity as a difficulty factor @prioridata / @bnolan0
- 26. 26 What’s in store for V1.2, 1.3... 1.n Integrate average retention as a demand signal @prioridata / @bnolan0
- 27. 27 What’s in store for V1.2, 1.3... 1.n Integrate stickiness (longer term retention) as a demand signal @prioridata / @bnolan0
- 28. 28 What’s in store for V1.2, 1.3... 1.n Integrate cross app usage / audience data to help w/ targeting @prioridata / @bnolan0
- 29. What would you do? for best idea!
- 30. How could you make it better with other data? 30 Once category established, add GR feature data to understand which features are correlated with high performance and more revenue in your category.
- 31. How could you make it better with other data? 31 Add in to show more complete picture of market opportunity AD NETWORKS Bribe them to give you average $/DAU per cat
- 32. How could you make it better with other data? 32
- 33. What other data/questions can we take into account? 33 ● Google Trends Data ● Alternative Store Data - if my audience is in non english speaking markets, where else can I reach them? ● How do my users transact - think about carrier billing, rewarded actions (ad views, etc), etc vs traditional paid + IAP
- 34. 34 How far could you take this? Trend & Demand Data (AdWords CTR, New launches, etc Market Opportunity Data (downloads, rev (inc AdRev), loyalty data, market conc’n, CPI, etc) Game Design Data (e.g GameRefinery + Quantum Shake data to understand key features for our target audience ● Understand what’s hot right now ● Understand in which categories/markets there is a higher chance of success ● Understand what features drive positive consumer reaction and sentiment in your chosen market ● Target your marketing to where it will be most effective
- 35. Want more? 35 ● Slides will be online tomorrow on my SlideShare/ link on Priori Twitter ● My beautiful colleagues are here, they have laptops and can help you dig out the data you need. ● WWW.PRIORIDATA.COM for more!
- 37. So what happens after you build and launch your game? ? 37 Go find the purple hall and catch Miikka in 10 minutes to find out!