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AppFollow Meetup
How to use data to increase
your user retention
Kevin Bravo - Innovation Lead at Phiture
Pg. 2
Quick about me
Kevin Bravo
Growth Consultant & Innovation Lead
Auditing and helping well established companies (>1M MAU) to
understand and improve their users retention through data-driven
CRM activities (emails / push / inapps).
Background in Data Analysis, Tech & Product growth, iOS
Development.
Pg. 3
App Store Optimization | Retention | Growth Consulting
Pg. 4
● Acquisition costs keep increasing
● Competition is fierce
● User expectations are higher than ever
● Very low barrier to uninstalling apps
○ Low retention rates are the norm
● Many users don’t return after first session in the app
● Winning apps grow MAU and MRR through healthy retention
● Losing apps will burn through acquisition budgets with
slower (or negative) growth
The Mobile App Market
is Saturated
Pg. 5
Retention Metrics
Consider core action that users should build a
habit around
(Intent-based app vs social apps)
At SoundCloud: Monthly Active Listeners
(metric defines both frequency and activity)
Other metrics to look at:
MAU, WAU, DAU - generic active user metrics
DayN, WeekN, MonthN Retention
Reactivation Rate
N-day rolling retention
Pg. 6
Everything affects Retention
● Changes to acquisition methods
● Changes to the product
● Changes to the way the product is marketed + positioned
● CRM Activities
● Interactions with Customer Support or a broader user Community
Pg. 7
Assess the current situation
before diving into tactics
● Identify gaps + opportunities
● Develop insight into drivers of
retention
● Inform strategy through data
Pg. 8
Pg. 9
Identify Tech Gaps
Pg. 10
Identify Data Gaps & Tools Discrepancies
Goal: Ensure data is being collected at the right
level of detail
Event Tracking should facilitate:
● Analysis + Investigation
● Impact Measurement + Conversion Tracking
● Targeting capabilities
● Personalization capabilities
● Trigger points for message delivery
Pg. 11
Document your event + attribute taxonomy
It’s not exciting to do, but rewards are:
● Identification of gaps + bad data
● Consistency of event naming across 3rd party tools
● Improved clarity + trust in the data
● Onboarding of new team members faster
Pg. 12
Key levers for influencing Engagement + Retention
Pg. 13
Understanding impact of current CRM efforts
Pg. 14
App Engagement Analysis
● Make sure you know your app inside
and out
● What are the common paths users are
taking?
● What features are most popular?
● What are common usage patterns?
● Are there emergent clusters in user
behaviour?
Pg. 15
Engagement + Retention Data Analysis
A major part of the audit involves active data exploration:
● Building a quantitative picture of the current state of retention
● Identifying useful behavioural segmentation approaches
● Uncovering the actions that are highly correlated with higher
retention
● Understanding the current usage frequency and establishing
a realistic target usage frequency
Pg. 16
Identifying Drivers of Retention
Pg. 17
Natural Usage Frequency
Method available here: https://mobilegrowthstack.com/natural-usage-habits-choosing-your-engagement-metric-a158438962c3
Pg. 18
Segment retention data with different approaches
Pg. 19
Defining user triggers (TCALP Framework)
- Time
- What is the different time of day / week when the user is the most likely to use your
product?
E.g: Uber: It's Saturday night and I want to go out
- Change
- What are the changes in the environment that can affect your user to use your product?
E.g: Uber: City transportation are on strike
- Action
- What actions your users are taking that can tie to another usage of your product?
E.g: Netflix: User just finished watching a show
- Location
- What change of location can impact the usage of your product?
E.g: Headspace: user just arrived home from work
- People
- What information / behavior of other people can affect the usage of your product
E.g: Tinder: There are a lot of people swiping right now in the app for your city
Pg. 20
The outputs of the different analysis should
help you build a strategy for improving
retention
The Retention Strategy may involve
changes to approach in:
● Positioning + User Acquisition
● Product
● CRM / Marketing Automation
Tying it all together...
Pg. 21
Messaging strategies to increase retention
Suggested Channels + Tactics
Frequency: activity notifications (push + email)
Feature exposure: In-App Messages for Adaptive
Onboarding
Session Length: In-App Content Feed
Pg. 22
Multiply impact with a cross-channel approach
Pg. 23
Building a CRM Lifecycle Plan
Case Study: Vody
Vody is a TV show + Movie discovery and tracking app,
soft-launched in South-East Asia.
What we built:
● Adaptive onboarding within the CRM to target users based
on retention analysis (which features tied to better
short-term retention)
● Increased onboarding completion rate by 15%
Case Study: HS
Headspace is a meditation app available worldwide.
What we built:
● Push notifications tailored for each user:
○ Delivery time based on their meditation time
○ Copy based on their onboarding choice (why they
are meditating) & packs they didn't try yet (or didn't
finish)
○ Next push based on interaction with the previous
one
● Increased Activation rate (people who meditated at least
once) by 6%
Case Study: ONX
OnX is a toolbox for hunters in the US.
From our correlation analysis, we defined that the compound
impact of using 4 different features within M1 tied to long-term
retention.
What we built:
● Adaptive onboarding within the CRM to educate users on
our main retention metric (Feature 1)
● Feature-based onboardings for W2-W4 based on previous
behavior (Features 2-4)
Each campaign had variants that were triggered until the
user used and understood the feature (Occurrences of
Feature X > 1)
Pg. 27
To go further: User level scoring
You can focus on improving CRM
frequency based on the user level.
By understanding how users interact with
your messages (push/email/inapps) you
can define an "engagement score" for
each user, and tailor your campaign
frequency (and value prop) for each user,
instead of running bucketed campaigns.
Thanks! - Any Questions?
kevin.bravo@phiture.com
@phituregrowth
mobilegrowthstack.com | phiture.com
Check out the Mobile Growth Nightmares
Podcast! www.mgnpodcast.com
Thanks!
Any Questions?

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Increase App Retention with Data-Driven CRM

  • 1. AppFollow Meetup How to use data to increase your user retention Kevin Bravo - Innovation Lead at Phiture
  • 2. Pg. 2 Quick about me Kevin Bravo Growth Consultant & Innovation Lead Auditing and helping well established companies (>1M MAU) to understand and improve their users retention through data-driven CRM activities (emails / push / inapps). Background in Data Analysis, Tech & Product growth, iOS Development.
  • 3. Pg. 3 App Store Optimization | Retention | Growth Consulting
  • 4. Pg. 4 ● Acquisition costs keep increasing ● Competition is fierce ● User expectations are higher than ever ● Very low barrier to uninstalling apps ○ Low retention rates are the norm ● Many users don’t return after first session in the app ● Winning apps grow MAU and MRR through healthy retention ● Losing apps will burn through acquisition budgets with slower (or negative) growth The Mobile App Market is Saturated
  • 5. Pg. 5 Retention Metrics Consider core action that users should build a habit around (Intent-based app vs social apps) At SoundCloud: Monthly Active Listeners (metric defines both frequency and activity) Other metrics to look at: MAU, WAU, DAU - generic active user metrics DayN, WeekN, MonthN Retention Reactivation Rate N-day rolling retention
  • 6. Pg. 6 Everything affects Retention ● Changes to acquisition methods ● Changes to the product ● Changes to the way the product is marketed + positioned ● CRM Activities ● Interactions with Customer Support or a broader user Community
  • 7. Pg. 7 Assess the current situation before diving into tactics ● Identify gaps + opportunities ● Develop insight into drivers of retention ● Inform strategy through data
  • 10. Pg. 10 Identify Data Gaps & Tools Discrepancies Goal: Ensure data is being collected at the right level of detail Event Tracking should facilitate: ● Analysis + Investigation ● Impact Measurement + Conversion Tracking ● Targeting capabilities ● Personalization capabilities ● Trigger points for message delivery
  • 11. Pg. 11 Document your event + attribute taxonomy It’s not exciting to do, but rewards are: ● Identification of gaps + bad data ● Consistency of event naming across 3rd party tools ● Improved clarity + trust in the data ● Onboarding of new team members faster
  • 12. Pg. 12 Key levers for influencing Engagement + Retention
  • 13. Pg. 13 Understanding impact of current CRM efforts
  • 14. Pg. 14 App Engagement Analysis ● Make sure you know your app inside and out ● What are the common paths users are taking? ● What features are most popular? ● What are common usage patterns? ● Are there emergent clusters in user behaviour?
  • 15. Pg. 15 Engagement + Retention Data Analysis A major part of the audit involves active data exploration: ● Building a quantitative picture of the current state of retention ● Identifying useful behavioural segmentation approaches ● Uncovering the actions that are highly correlated with higher retention ● Understanding the current usage frequency and establishing a realistic target usage frequency
  • 17. Pg. 17 Natural Usage Frequency Method available here: https://mobilegrowthstack.com/natural-usage-habits-choosing-your-engagement-metric-a158438962c3
  • 18. Pg. 18 Segment retention data with different approaches
  • 19. Pg. 19 Defining user triggers (TCALP Framework) - Time - What is the different time of day / week when the user is the most likely to use your product? E.g: Uber: It's Saturday night and I want to go out - Change - What are the changes in the environment that can affect your user to use your product? E.g: Uber: City transportation are on strike - Action - What actions your users are taking that can tie to another usage of your product? E.g: Netflix: User just finished watching a show - Location - What change of location can impact the usage of your product? E.g: Headspace: user just arrived home from work - People - What information / behavior of other people can affect the usage of your product E.g: Tinder: There are a lot of people swiping right now in the app for your city
  • 20. Pg. 20 The outputs of the different analysis should help you build a strategy for improving retention The Retention Strategy may involve changes to approach in: ● Positioning + User Acquisition ● Product ● CRM / Marketing Automation Tying it all together...
  • 21. Pg. 21 Messaging strategies to increase retention Suggested Channels + Tactics Frequency: activity notifications (push + email) Feature exposure: In-App Messages for Adaptive Onboarding Session Length: In-App Content Feed
  • 22. Pg. 22 Multiply impact with a cross-channel approach
  • 23. Pg. 23 Building a CRM Lifecycle Plan
  • 24. Case Study: Vody Vody is a TV show + Movie discovery and tracking app, soft-launched in South-East Asia. What we built: ● Adaptive onboarding within the CRM to target users based on retention analysis (which features tied to better short-term retention) ● Increased onboarding completion rate by 15%
  • 25. Case Study: HS Headspace is a meditation app available worldwide. What we built: ● Push notifications tailored for each user: ○ Delivery time based on their meditation time ○ Copy based on their onboarding choice (why they are meditating) & packs they didn't try yet (or didn't finish) ○ Next push based on interaction with the previous one ● Increased Activation rate (people who meditated at least once) by 6%
  • 26. Case Study: ONX OnX is a toolbox for hunters in the US. From our correlation analysis, we defined that the compound impact of using 4 different features within M1 tied to long-term retention. What we built: ● Adaptive onboarding within the CRM to educate users on our main retention metric (Feature 1) ● Feature-based onboardings for W2-W4 based on previous behavior (Features 2-4) Each campaign had variants that were triggered until the user used and understood the feature (Occurrences of Feature X > 1)
  • 27. Pg. 27 To go further: User level scoring You can focus on improving CRM frequency based on the user level. By understanding how users interact with your messages (push/email/inapps) you can define an "engagement score" for each user, and tailor your campaign frequency (and value prop) for each user, instead of running bucketed campaigns.
  • 28. Thanks! - Any Questions? kevin.bravo@phiture.com @phituregrowth mobilegrowthstack.com | phiture.com Check out the Mobile Growth Nightmares Podcast! www.mgnpodcast.com Thanks! Any Questions?