finding your mobile growth
TRANSCRIPT
Finding your mobile growthSpenser SkatesCEO and Co-founder, Amplitude Analytics
Finding your mobile growth
1.The Three Levels of Analytics2.Understanding behavioral cohorts3.An example of using analytics to drive
product decisions
Few key things to cover:
Level 3: What drives growth
Level 2: Where are my problems
Level 1: Counters
Behavior-Based CohortingData Science
Companies at this level:Facebook, Amazon, Netflix, Zynga
FunnelsRetention
SegmentationEvents
DAU, MAU, Revenue
The Three Levels of Analytics
Level 3: What drives growth
Level 2: Where are my problems
Level 1: Counters
Behavior-Based CohortingData Science
Companies at this level:Facebook, Amazon, Netflix, Zynga
FunnelsRetention
SegmentationEvents
DAU, MAU, Revenue
The Three Levels of Analytics
Level 3: What drives growth
Level 2: Where are my problems
Level 1: Counters
Behavior-Based CohortingData Science
Companies at this level:Facebook, Amazon, Netflix, Zynga
FunnelsRetention
SegmentationEvents
DAU, MAU, Revenue
Most companies are here.
The Three Levels of Analytics
Completing 50% of Profile
Adding 7 Friends
What Drives Long Term Retention?
Posting on a wall
Optimized experience around adding and discovering friends.
Level 3: What drives growth
Level 2: Where are my problems
Level 1: Counters
Behavioral CohortingData Science
Companies at this level:Facebook, Amazon, Netflix, Zynga
FunnelsRetention
SegmentationEvents
DAU, MAU, Revenue
Most companies are here.
The Three Levels of Analytics
What is a behavioral cohort?Behavioral cohorting allows you to group your users based on specific actions
that they have or have not taken in your app or website.
This helps you identify user actions or product features in your app that drive growth.
How to use behavioral cohorting to make product decisions
Come up with a hypothesis on
what user actions lead to long term
retention
Apply cohorts to retention reports and
search for insights
Test the hypothesis by
creating cohorts based on
specific user actions
Step 1 Step 3Step 2
Let’s walk through an example.
Step 1: Come up with a hypothesis
Example: Social music app
Key user actions on the 1st day:• Joining a community• Completing user profileCome up with a
hypothesis on what user actions lead to long term
retention
Step 2: Create cohorts to test your hypothesisCohort: Users who joined at least 1 community on the 1st day of use
Step 3: Apply cohorts to retention reports
Takeaway: Users who join at least 1 community on the 1st day of app use have significantly increased retention in the first 30 days.
Now we can repeat this process for our other candidate behavior:Completing the user profile on the 1st day
Cohort: Users who completed their profile on the 1st day of use
Takeaway: Users who complete their profile on the 1st day of app use have significantly increased retention over the first 30 days compared to users who do not complete their profile on the 1st day.
Cohort: Users who completed their profile on the 1st day of use
Both joining a community and completing a profile on the first day correlate with improved
retention.
Let’s compare the 2 pairs of cohorts on the same graph.
Now what?
Takeaway: Joining a community has a greater effect on retention than completing a profile.
Product Decision: Encourage users to join a community during onboarding experience.
• Unlike traditional acquisition date cohorts, behavioral cohorts group users by specific actions they take in your product
• Behavioral cohorting allows you to discover ‘a-ha’ moments: actions that can maximize long-term retention, just like Facebook’s “7 friends in 10 days.”
• There are 3 steps to behavioral cohort analysis:• Come up with a hypothesis of actions that promote
retention• Create cohorts to test that hypothesis• Apply the cohorts to retention or engagement
reports
Summing Up
