This document discusses behavioral cohorts and how they can be used to analyze user groups and monitor key metrics over time. It provides examples of common use cases like tracking user milestones, engagement with new features, conversion of new or non-active users. The document also demonstrates how to create different types of cohorts using Amplitude's tools, including inline cohorts with rolling windows and offsets to compare user behavior in different time periods.

1. © 2020 Amplitude Inc. Confidential. All Rights Reserved.
Deep Dive:
Behavioral Cohorts
Daria Eibert
Growth, Success Manager
Amplitude
solutions@amplitude.com

2. Agenda
© 2020 Amplitude Inc. Confidential. All Rights Reserved.
● Types of cohorts
● Industry & Team Specific Use
Cases
● Q&A

3. © 2020 Amplitude Inc. Confidential. All Rights Reserved.
Help product leaders prove they
build better products by
understanding the impact of
product bets on changes in user
experience

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Define an outcome, form
hypotheses about what drives
change, and the measure
impact of product bets to
validate assumptions
Product analytics
lifecycle
Define
Product
Outcomes
Evaluate
Impact of
Releases
Understand
Customer
Journeys

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Analyzing Every User Journey To Identify Milestones Is
Hard
SIGN IN 1ST SEARCH FILTER SEARCHVIEW 1ST TEAM SPACE END SESSION DORMANT USER
WEB HOMEPAGE VIEW 1ST TEAM SPACECREATE ACCOUNT SEARCH
ACTIVATED CUSTOMER
VIEW 1ST CHART
MILESTONE MILESTONE
ACTIVE USERSIGN IN VIEW CHART1ST SEARCH FILTER SEARCH END SESSION
VALUABLE CUSTOMER
1ST SEARCH TWEAK 1ST CHART SAVE 1ST CHART
MILESTONE MILESTONE
SHARE 1ST CHART
MILESTONE
VIEW 1ST CHART
MILESTONE
TWEAK 1ST CHART

6. © 2020 Amplitude Inc. Confidential. All Rights Reserved.
Powered by our proprietary infrastructure
Nova, Historical Count lets teams answer
questions like:
๏ What are my important milestones?
๏ How does user behavior change after achieving a
milestone?
๏ How does this milestone impact my target outcome?
๏ What are the critical milestones I haven’t thought of?
๏ What kinds of users achieve milestones, and why?
MILESTONE ANALYSIS
Track the milestones that convert
new users to high-value customers
INDUSTRY FIRST • TECHNICAL BREAKTHROUGH • PROPRIETARY BACKEND NOVA
Potential Milestones
7th friend
5th show watched
1st transaction
2nd project created
1st song shared
1st delivery

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Deep Dive: Behavioral
Cohorts Notebook

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Behavioral Cohorts
Microscope
Exploratory analysis of specific
user groups:
• comparison with other groups
• using a cohort across other
analysis
• AB testing
In-Line Cohorts
Dynamic user groups to monitor:
• BETA user adoption
• activated user vs non-activated
• KPI’s
Custom Cohort
Dynamic user groups to:
• engage with a target group (Ex.
push-notifications, campaigns)
• monitor a target user behavior
(Ex.New, Non-activated)
• experiment with a specific user
group

9. In-line Rolling
Apply a Rolling Window to increase the size of the interval. Typically, a user would use a Rolling
Window to smooth out seasonality (accomplished by including more data points).

10. In-line Offset
Shift the time period of your cohort back in time using date inline offsets. Define transitions
between cohorts in order to understand where your growth is coming from!

11. Users who read 1 article in a week and then read 2+ articles the subsequent week. This
helps us target users who are finding value in our content and we can target them to
purchase a subscription.
Use Case: Media

12. How are current users (“any active event” in 2 consecutive periods) are engaging with
collaboration features in rolling 28 day periods.
Use Case: Productivity

13. Who are users that created an account last month and have become chart editors this
month? This group represents users that recently realized value in Amplitude, so it’s a
helpful metric for CSMs to watch to understand which accounts are growing healthily or if
trainings had an impact.
Use Cases: Amplitude

14. App: Users who installed the app, but did not make a purchase during the month
after install. This is important to track so that they can run re-engagement
campaigns.
Use Cases: Navigation App

15. Users who made a purchase in each day and also made a purchase at any point in
the prior 3 months. They view this metric as a better proxy for product satisfaction.
Previously, they’d have to use surveys to ask how likely users were to return to
make another purchase.
Use Case: Food delivery

16. “in each” cohort
+rolling by 90 days
1. Let’s create an “in each” in-line cohort for AmpliTunes users that made a purchase in March.
2. Let’s add a rolling 90 day window to increase the interval to include last 90 days (1/1 - 3/31).
So when we look at the 3/31 data point, it actually includes users who did Purchase 1/1 - 3/31 (90 data points
total because of 90 day rolling window).
Users who made a purchase in each day and also made a purchase at any point in the prior 90 days.
March
Purchase
1/1 - 3/31
FebruaryJanuaryDecember
Previous Period

17. “in each” cohort
+rolling by 90 days
+offset by 1 day
Users who made a purchase in each day and also made a purchase at any point in the prior 90 days.
March
Purchase
12/31 - 3/30
FebruaryJanuaryDecember
“Offset” is how you
can make something
happen “prior”
1. Let’s create an “in each” in-line cohort for AmpliTunes users that made a purchase in March.
2. Let’s add a rolling 90 day window to increase the interval to include last 90 days (1/1 - 3/31).
3. Add a 1 day offset to shift the date range into the past by 1 day (now 12/31 - 3/30)
Previous Period

18. “in each” cohort
March
Purchase
3/31
Let’s create an “in each” in-line cohort for AmpliTunes users that made a purchase in March.
If we take a single day, 3/31, users are counted if they made a purchase on that day.
Users who made a purchase in each day and also made a purchase at any point in the prior 90 days.
Current Period

19. “in each” cohort
+rolling by 90 days
+offset by 1 day
Users who made a purchase in each day and also made a purchase at any point in the prior 90 days.
March
Purchase
12/31 - 3/30
FebruaryJanuaryDecember
Purchase
3/31
4. Add the second Purchase event for our “current” period
Previous Period Current Period

20. Previous Period
Definition
Current Period
Definition
A Closer Look

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Resources
● Follow-up
○ Recording
○ Amplitude Demo Notebook with use cases
○ Questions highlight
● Questions?
○ support.amplitude.com
● Webinar idea?
○ solutions@amplitude.com

22. Thank you
© 2020 Amplitude Inc. Confidential. All Rights Reserved.