1) The document analyzes marketing strategies for iPhone applications based on a case study of two public transportation apps called RATP Lite and RATP Premium. It identifies patterns in downloads, sales, pricing, and rankings on the App Store. 2) Key findings include that price reductions can significantly increase sales, free versions help promote paid versions, and concentrated advertising periods over 4 days yield better results than spreading ads over weeks. 3) The document proposes that App Store rankings are based on the previous 4 days of sales, with current day sales being most influential, and that sales can be forecasted with 10% accuracy based on previous sales patterns.

1. How to successfully market
your iPhone Application?
#appstudy
Paris, January 2010

2. Introduction
This study originated from observations made on the lifecycle of “RATP Lite”
and “RATP Premium”, two applications we designed to provide Parisians with
public transportation official information
We decided to go further in the analysis by running mathematical programs
Today we make a step further by sharing the results with you through this
creative commons presentation
We hope your challenge and contributions to the study will favor the
emergence of best practices for iPhone apps marketing
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3. Summary
1 - Presentation of the App Store
2 - Case study: RATP apps
3 - The App Store 4Ps
4 - Conclusion
..…….
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4. ..…….
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5. App Store: applications entrypoint
App Store is the unique marketplace
to get iPhone and iPod Touch applications
..…….
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6. App Store: Figures
34 million 24 million
iPhone iPod Touch 58 million
App Store users
3 billion applications have been downloaded
Each user spends an average 4,37$ a month on apps*
Generating over $250 million in revenue per month
Apple has locked a huge market
*Source: GigaOM.com
..…….
http://gigaom.com/2010/01/12/the-apple-app-store-economy
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7. Browsing the App Store (desktop)
Search bar
Apple Categories
editorial
content
Banners 3 Rankings
“New and
Paid apps
noteworthy”
“What’s hot”
Free apps
“Staff
favourites”
Grossing apps
..…….
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8. Browsing the App Store (mobile)
Apple editorial Category
Rankings
content browsing
..…….
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9. The big challenge!
There is no opportunity for advertising within the App Store
Getting the right marketing mix is more important than ever
..…….
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10. ..…….
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11. Case study: RATP apps
faberNovel designed two applications for RATP users:
RATP Lite RATP Premium
• Live on May 13th 2009 • Live on May 3rd 2009
• Free • Paid: 1,59€ then 0,79€
• Ad-funded
• 350 000 downloads • 105 000 downloads
• 126 000 active users • 80 000 active users
..…….
January 2010 • Marketing your iPhone application #appstudy • 11

12. Case study: sales and downloads evolution
Downloads Lite
Downloads
Downloads Premium
Time
Price cut V 2.0
..…….
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13. Case study: pricing evolution on RATP Premium
The initial pricing was 2,99 € according to the business
plan, but that never happened
0 day!!!
We realized that it was too high compared to the market.
We set a premium price of 1,59 €, capitalizing on the
RATP brand
2 months
That wasn’t enough to win significant market share, so we
shifted to a volume strategy with a 0,79€ price
..…….
January 2010 • Marketing your iPhone application #appstudy • 13

14. Case study: week-end sales peak
Sales breakdown by weekday
Monday Tuesday Wednesday Thursday Friday Saturday Sunday
Sales peak during the weekend (+20% on Sunday)
It might be even bigger for games….
..…….
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15. Case study: sales vs advertising
Advertising revenues from the Lite version brings recurrent
revenues to compensate sales relative stability in Premium
Monthly Profits First ad campaign
SalesAdvertising Lite
Premium
Advertising Lite
Sales Premium
63%
55%
45% 37%
May June July August September October November December
..…….
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16. Case study: RATP apps
Those results encouraged us to go further in the analysis
With 8 months of data…
… we ran statistical analysis…
0
… to identify the the App Store 4Ps
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17. PRODUCT PROMOTION
PRICE PLACE
..…….
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18. Product: great upsell opportunity
We monitored the percentage of RATP Premium owners that downloaded
RATP Lite first
80% of users try Lite before buying 50% of users try Lite before buying
Premium Premium
A good free version is crucial to push users towards the paid one
…especially if the price is high
..…….
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19. Product: 4 reasons for a differentiated
product line
Upsell opportunity
Brand visibility
Better segmentation
Clearer product definition
..…….
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20. Price: a price-sensitive market
2
1,59€ 0,79€
A 50% price cut led to 3x more sales
3 Sales
..…….
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21. Promotion: web campaign ROI was not so great
We booked 500 000 impressions* on a major website…
…generating 4 sales!!!
With an average CPM** of 6€ in France
That’s 750€ of advertising for one client
… to make a 2€ revenue!
*Impression = display of an advertising banner ..…….
**CPM = cost of 1000 impressions
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22. Promotion: cross-marketing increases
click-through rate
Cross-application advertising
seems a better solution
Click-through rate 8
0,07%* 0,59%*
Web advertising Cross-application
advertising
* Source: appfigures for RATP Lite ..…….
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23. Place: availability on the device is key
An app has to be lighter than 10Mo to be available in 3G (on the iPhone)
When we launched RATP Premium, it was way too big (27Mo)
SALES x3,5
RATP Premium available in 3G, on the iPhone  biggest sales peak ever
..…….
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24. Place: the App Store ranking algorithm
Macro observations led to 2 likely hypothesis*:
Ranking is based on sales of the previous
1 week
The formula is a 7 days weighted
2 average
We ran a program to identify the best combination of weighted coefficients…
… and here is what we found
* See http://tii.libsyn.com/index.php?post_id=522655 for precisions ..…….
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25. Place: the App Store ranking algorithm
The ranking only takes account the last 4 days of sales
Sales of the current day are determinant
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26. Key learning: advertising campaign timing
WIN FAIL
Focused campaign on Advertising on a specific day
4 consecutive days and repeating over the weeks
Self-perpetuating good position
Advertising effort will be diluted
in the rankings
Ranking will not be maintained
Higher Good
sales ranking
..…….
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27. One more thing… in progress
We can forecast future sales based on previous sales with a precision of 10%
450
400
350
Real Sales
300
Our forecast
Nombre de vente
250
Sales
200
150
This algorithm is based
on an ARMA model :
100 Autoregressive Moving
Average Model
50
0
0 10 20 30 40 50 60 70
jour étudié
Time ..…….
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28. ..…….
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29. What’s your take on this?
• These results are based exclusively on our Apps study
• The algorithm can’t be proved, as the rankings are relative to other applications
sales
• To extend the reach of this presentation, we will wait your contribution:
Try the algorithm on your application
Challenge our case study
Bring constructive feedback on iPhone Apps marketing
On twitter: #appstudy
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30. Study written by:
Marie-Caroline Lanfranchi @mariecaroline
Baptiste Benezet @Ba_B
Romain Perrier @RomPerrier
Acknowledgements:
Yves, Martin, Clément L., Virginie, Patrick, Estelle, Pierre-Yves,
Cyril, Matthieu, Sabrina, Stéphane, Ouriel and La Cantine
Contacts
Project - Baptiste Benezet
baptiste.benezet@fabernovel.com
Press - Sabrina Distinguin
Sabrina.distinguin@fabernovel.com
17, rue du faubourg du Temple 75010 Paris
Tél. : +33 1 42 72 20 04
Fax. : +33 1 42 72 20 03
www.fabernovel.com
..…….
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31. Our Apps are available
on the iPhone App Store
http://getap.ps/RATPpremium/appstudy
http://getap.ps/RATPlite/appstudy
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