(MBL303) Get Deeper Insights Using Amazon Mobile Analytics | AWS re:Invent 2014

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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.

Transcript of (MBL303) Get Deeper Insights Using Amazon Mobile Analytics | AWS re:Invent 2014

November 12, 2014 | Las Vegas, NV

Andy Kelm, AWS Mobile

Patrik Arnesson & Vedad Babic, Forza Football

Chris Keyser, AWS Partner Program

The King of England sent his best men

ahead to learn context to plan the battle

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

Source: britishbattles.com

militaryhistory.about.com

Amazon Mobile Analytics

Collect, visualize, and understand app usage

Amazon

Mobile

Analytics

Amazon

Mobile

Analytics

Amazon

Mobile

Analytics

Amazon

Mobile

Analytics

Amazon

Mobile

Analytics

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

But, customers tell us they want to dive deeper

Live score VotingPush notifications

+5 000 000downloads

50%Sticky factor

800 000 000push notifications / month

2 500 000 monthly active users

100 000 000 sessions / month

1 600 000 000events / month

FORZA FOOTBALLSINCE 2012

OUR EXPERIENCEPRE AMAZON MOBILE ANALYTICS

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 TOOLFROM THE BEGINNING

GA(Google Analytics)

GA Mobile GA sample data

SCREENING THE MARKETWE TALKED TO ALMOST EVERY ANALYTICS VENDOR IN

THE MARKET

THIS WAS IMPORTANT FOR USWHEN CHOOSING ANALYTICS TOOL

PricingFlexible pricing

(Pay as you use)

Competitive pricing

FeaturesRetention

Custom events

Mobile friendly

DataOwnership

Export functionality

No sampling

AMAZON MOBILE ANALYTICS + REDSHIFT

VISUALIZE DATA THAT MATTERS TO YOU

TWO MONTH RETENTIONFRANCE VS AVERAGE

VISUALIZATIONSBY TABLEAU

GROWTH PER COUNTRYTHE WORLD CUP IS THE MOST INTERESTING FOR THE AMERICANS

World Cup

PENETRATIONUSERS PER CAPITA

Potential

Same penetration in the UK as in Denmark would equal 4 400 000 users

LEVERAGE ON MISSIONTABLEAU VISUALIZATION

The users in the nordic countries are the most interested in voting

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

PUSH NOTIFICATIONS9/10 PEOPLE I HAVE MET SAY THAT THEY REMOVED THE

APP BECAUSE OF TOO MANY NOTIFICATIONS.

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

PUSH NOTIFICATIONSRETENTION PER GROUP 65 DAYS

10-14 notifications retain best

PUSH NOTIFICATIONSRETENTION PER GROUP 148 DAYS

5-9 notifications retain 1.5x better than 10-14 notifications

USER SEGMENTATIONSEGMENT USERS BASED ON USAGE

SEGMENTATION BASED ON ACTIVITYWE WANT TO SEE WHICH GROUP USE EACH FUTURE

Low activity Medium activity High activity

Build features for the medium activity group

APPROACH TO SEGMENTATIONWE WANT TO SEE WHICH GROUP USE EACH FUTURE

Experiment Define criteria User group size

EXPERIMENT

• Sessions?

• Session length?

• Days active?

• Per day?

• Per week?

• Per month?

HOW TO DEFINE ACTIVITY

CRITERIAHOW TO DEFINE CRITERIA

Days active (14 days)

• # days active over 2-week

period

• Gaussian distribution?

• Let’s try it out!

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

MAIN MENU WHY WE DELETED A COMPLETELY NEW FEATURE

MAIN MENU

Low activity group: 12%

Medium activity: 25%

High activity: 35%

FILTER MATCHES

Old design New design

10 GigE

(HPC)

Ingestion

Backup

Restore

JDBC/ODBC

S3 Redshift

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

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

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

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