Presentation from White Nights Berlin, Feb 2018. Key points: - Why do market research for games? - What data are available for market research? - How can one combine these data sources to understand markets? - How can you take market research further and plan for success?

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!

36. Any questions? 36

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!