finding your mobile growth

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

Spenser Skates

spenser@amplitude.comhttps://amplitude.com

Questions?