Without consulting mobile app market data, your mobile growth strategy is completely unguided. Learn how to benchmark track and set targets BEFORE you spend your user acquisition budget.
3. Rich, scarce, and
actionable insights
on the performance
and user behaviors
of mobile apps
Intelligence Layer
3
Proprietary and
rigorous science
using statistical,
machine learning,
and NLP
algorithms
Source Layer
We use data to build a window into the mobile app economy
Public
store data
Confidential
developer data
Anonymized
user device data
Modelling Layer
+ =
4. 4
Gaming:
Travel & Navigation:
Sports / Kids / Food:
News / Reference / Education:
Social / Music / Entertainment:
Health & Fitness / Finance:
E-commerce & Shopping:
Our Backbone: 22,000 Feeds from 1,400 Top Partners
5. ● “UberEats outpaces Deliveroo
downloads by a factor of 3x in April”
● “Pokemon Go earned revenue declined
45% month-over-month in May”
● “The US market for music streaming
apps represented ~30% of the global
total. The Top 3 services earned >60%
of their global downloads in the US”
Our Data Powers a Comprehensive Intelligence Platform
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Keyword Intelligence
App Store Keyword
Optimization
App Intelligence
Competitive Benchmarking
& Tracking
Market Intelligence
Market Sizing, Screening,
and New Entrant Detection
7. Scenario
● An ambitious and entrepreneurial group of vegan cross-fit’ers have decided to branch
out and launch their own app company, focused on their favorite new hobby meditation
& mindfulness
● They are confident they can build a high quality app. They know the problem, they know
the solution, and they have a revolutionary marketing hook….
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9. ● The genius of the idea has landed them a $1m seed round from a top VC, and they are
finally ready to launch the app
● It took them longer than expected (and more of the VC $) to get to launch, and they only
have $100k in UA budget to work with
● Within 12 months they need to demonstrate $500k of revenue in their initial markets to
successfully raise a series A
7 Minute Mindfulness! (Watch out 8Fit)
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12. 12
They need a data-informed expansion strategy
1. What is my total market opportunity?
2. Who am I competing against?
3. Which geographic region(s) should I target first?
4. What targets should I set to achieve my goal, given my marketing budget?
5. Which keywords should I use to maximize organic discoverability and conversion?
13. Assumptions:
Global, Apple only in year 1, will focus on mindfulness & meditation, not
entering adjacencies of fitness and/or nutrition
Data-Driven Expansion Strategy
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What is my total market
opportunity?
14. Assumptions:
Market is niche and growing. Existing players likely have better unit
economics/marketing firepower. New entrants likely to come in over time.
Data-Driven Expansion Strategy
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Who am I competing against?
15. Assumptions:
Don’t have budget for full localization or marketing launches. Need to find a
good combination of sizeable and fast growing markets for this segment.
Which geographic region(s) should
I target first?
Data-Driven Expansion Strategy
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16. Assumptions:
Let’s do a bit of back-of-the envelope calculations...
What targets should I set to achieve
my goal, given my marketing
budget?
Data-Driven Expansion Strategy
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17. Here we need a bit of (very simplified) funnel math...
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● Target next-twelve-month revenue: $500k
● My monetization? Freemium, subscription at $10/month
● Assume that 1% of users will convert to paid, with an average subscription length of 5
months = CLV of $50
● To reach $500k, you need 10k paying users with an average $50k CLV. Assuming the 1%
paid conversion you need 1 million downloads
● How does that stack up to the overall market opportunity?
18. ● Comps are earning in total 600k downloads per month...
Based on your comp set and the 4 target markets
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Country Monthly Downloads
USA 400k
UK 100k
Canada 50k
Australia 50k
Total 600k
19. Based on your comp set and the 4 target markets
● 600k/month * 12 months = 7.2m per year (assumes any market growth is eaten up by
new entrants)
● So you need:
1m downloads for me / 7.2m for everyone =
~15% market share (on average per month), to achieve your target
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20. ● Assuming your performance in the US will dictate your overall
performance, 15% share would mean 60k downloads per month, or
roughly 2k per day.
● Where do you need to be in the ranks in order to achieve this?
Based on your comp set and the 4 target markets
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21. Let’s think about user acquisition
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● What’s it cost to acquire a user in the target market?
● Let’s head to Chartboost: https://www.chartboost.com/insights/
22. ● Paid:
○ I have $100k marketing budget, and it costs me $3.50 to acquire a user…
○ I need 60k downloads a month in the US to meet my plan….
○ I can spend my entire marketing budget and only acquire 50% of my budgeted
users, in a single month!
Let’s think about user acquisition
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23. Let’s think about user acquisition
● Organic:
○ Of course you need a great product, word-of-mouth, an offline/desktop strategy,
etc...
○ Featuring: Remember Mind Journey? Looks like their featurings delivered 80k of
downloads - that’s 1 month of your plan!
○ ASO: you will need to have done the basics with ASO right to capitalize on any
opportunity for organic visibility and discoverability via search
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24. Which keywords should I use to
maximize organic discoverability
and conversion?
Data-Driven Expansion Strategy
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Assumptions:
Leverage the work your competitors have already done to get into the game
initially, and optimize over time.
25. ● Using data to inform an expansion strategy gives you benchmarks and sanity checks on
your plans that are critical for expectation setting
● The analysis is easily performed and can be done at low cost with minimal time invested
● In the competitive (and increasingly expensive) world of mobile apps, you have to look
for opportunities to outperform others that have more funding / a more established
brand / a better monetizing product / etc...
● You can use all the internal analytics tools, have great engagement on push notifications,
have a conversion rate on your ads, but without a view into market intelligence data you
are flying blind
Conclusion
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