Choosing the right mobile analytics solution can help you understand user behavior, engage users, and maximize user lifetime value. After this session, you will understand how you can learn more about your users and their behavior quickly across platforms with just one line of code using Amazon Mobile Analytics.

1. November 12, 2014 | Las Vegas, NV
Andy Kelm, AWS Mobile
PatrikArnesson& VedadBabic, ForzaFootball
Chris Keyser, AWS Partner Program

3. The King of England sent his best men ahead to learn context to plan the battle

4. Tactics used:
Segmented army into three divisions
Chose higher elevation around flat land
Waited for the enemy to buy time to rest and prepare
Built a system of ditches and pits to bring down the enemy cavalry

5. Source: britishbattles.com
militaryhistory.about.com

7. Amazon Mobile Analytics
Collect, visualize, and understand app usage

8. Amazon Mobile Analytics

9. Amazon Mobile Analytics

10. Amazon Mobile Analytics

11. Amazon Mobile Analytics

12. Amazon Mobile Analytics

13. Amazon Cognito Amazon Mobile Analytics Amazon SNS Mobile Push
Kinesis DynamoDB S3 SQS SES
AWS Global Infrastructure (11 Regions, 51 Edge Locations)
Core Services
Mobile Optimized
Connectors
Mobile Optimized
Services
Your Mobile App, Game or Device App
AWS Mobile SDK
Compute Storage Networking Analytics Databases
Integrated SDK

15. But, customers tell us they want to dive deeper

19. Live score
Voting
Push notifications

20. +5 000 000
downloads
50%
Sticky factor
800 000 000
push notifications / month
2 500 000
monthly active users
100 000 000
sessions / month
1 600 000 000
events / month
FORZA FOOTBALL
SINCE 2012

21. OUR EXPERIENCE
PRE AMAZON MOBILE ANALYTICS

22. 0
440,000
880,000
1,320,000
1,760,000
2,200,000
February 2012
October 2012
April 2013
November 2013
CHOOSE THE RIGHT TOOL
FROM THE BEGINNING
GA
(Google Analytics)
GA Mobile
GA sample data

23. SCREENING THE MARKET
WE TALKED TO ALMOST EVERY ANALYTICS VENDOR IN THE MARKET

24. THIS WAS IMPORTANT FOR US
WHEN CHOOSING ANALYTICS TOOL
Pricing
Flexible pricing
(Pay as you use)
Competitive pricing
Features
Retention
Custom events
Mobile friendly
Data
Ownership
Export functionality
No sampling

25. AMAZON MOBILE ANALYTICS + REDSHIFT
VISUALIZE DATA THAT MATTERS TO YOU

26. TWO MONTH RETENTION
FRANCE VS AVERAGE

27. VISUALIZATIONS
BY TABLEAU

28. GROWTH PER COUNTRY
THE WORLD CUP IS THE MOST INTERESTING FOR THE AMERICANS
World Cup

29. PENETRATION
USERS PER CAPITA
Potential
Same penetration in the UK as in Denmark would equal 4 400 000 users

30. LEVERAGE ON MISSION
TABLEAU VISUALIZATION
The users in the nordic countries are the most interested in voting

31. HOW AND WHY DO USERS USE OUR APP?
DATA GUIDE DESIGN DECISIONS

32. PUSH NOTIFICATIONS
9/10 PEOPLE I HAVE MET SAY THAT THEY REMOVED THE APP BECAUSE OF TOO MANY NOTIFICATIONS.

33. NOTIFICATIONS
>30% set notifications for more than 11 teams.
We wanted to see if the amount of notifications could affect the retention.
0-4 notifications
5-9 notifications
10-14 notifications

34. PUSH NOTIFICATIONS
RETENTION PER GROUP 65 DAYS
10-14 notifications retain best

35. PUSH NOTIFICATIONS
RETENTION PER GROUP 148 DAYS
5-9 notifications retain 1.5x better than 10-14 notifications

36. USER SEGMENTATION
SEGMENT USERS BASED ON USAGE

37. SEGMENTATION BASED ON ACTIVITY
WE WANT TO SEE WHICH GROUP USE EACH FUTURE
Low activity
Medium activity
High activity
Build features for the medium activity group

38. APPROACH TO SEGMENTATION
WE WANT TO SEE WHICH GROUP USE EACH FUTURE
Experiment
Define criteria
User group size

39. EXPERIMENT
•Sessions?
•Session length?
•Days active?
•Per day?
•Per week?
•Per month?
HOW TO DEFINE ACTIVITY

40. CRITERIA
HOW TO DEFINE CRITERIA
Days active (14 days)
•# days active over 2-weekperiod
•Gaussian distribution?
•Let’s try it out!

41. USER GROUP SIZE
•Averaged over 16 time periods
•~60% in medium activity
•Result
•Low activity: 1-4 days
•Medium Activity: 5-12
•High activity: 13-14
HOW TO DEFINE SIZE

42. MAIN MENU
WHY WE DELETED A COMPLETELY NEW FEATURE

43. MAIN MENU
Low activity group: 12%
Medium activity: 25%
High activity: 35%
FILTER MATCHES

44. Old design
New design

47. 10 GigE
(HPC)
Ingestion
Backup
Restore
JDBC/ODBC

48. S3
Redshift

49. 172.16.0.0/20
Public Subnet 172.16.0.0/22
172.16.0.0/20 Local
0.0.0.0/0 IGW
Amazon
Mobile
Analytics
EC2

50. event_timestamp
arrival_timestamp
application_key
account_id
app_title
event_type
unique_id
model
make
platform
platform_version
locale
app_package_name
app_version_name
sdk_name
sdk_version
a_level
a_promo_code
m_score
m_quantity

51. Activity Monitor (custom application)
Amazon SNS
Cross-platform Mobile Push
event_timestamp
arrival_timestamp
application_key
account_id
app_title
event_type
unique_id
model
make
platform
platform_version
locale
app_package_name
app_version_name
sdk_name
sdk_version
a_level
a_promo_code
m_score
m_quantity
a_endpoint_arn

54. http://bit.ly/awsevalshttp://aws.amazon.com
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