Mobile Apps Unlocked Vegas 2016 Thursday, May 5 Retention Breakout Session — 2:50pm - 3:10pm The blessing and the curse of retention talks is that we could have the exact same title for every session and still have different content materialize, because while certain things hold true across businesses, every individual company is different. Helping to contribute to your knowledge base is iBotta, sharing how they built their messaging strategy and team to support a fully segmented, cross channel approach. Cody Ryan, Senior Manager, User Retention @ Ibotta

1. MAU 2016
Cody Ryan – Senior Manager, User Retention @

2. 1. Why it matters
2. What data you should use
3. Stages of segmentation
4. Results of improved segmentation at Ibotta
5. Key takeaways
6. Q & A

4.  ALL USERS ARE DIFFERENT!
 Users differ and are unique based on:
 Demographics
 In-app behavior
 Needs
 Socio-economics
 Beliefs/perceptions
 Motivations

5. Behavior
Demographic
Acquisition Source
Predictive Modeling
User-level Data
Warehousing
Proper data tracking is the cornerstone
to segmentation
Segmentation
Strategy

6. High Value
Low Use
High Value
Mid Use
High Value
High Use
Mid Value
Low Use
Mid Value
Mid Use
Mid Value
High Use
Low Value
Low Use
Low Value
Mid Use
Low Value
High Use
 …segmentation drives User Acquisition (UA)
 The easiest way to drive increased value and decreased churn, is to get the best possible
users from your User Acquisition efforts
Coordinate with UA efforts
to find these users. Identify
them based on:
• Source
• Demographics
• Look-a-like targeting
• Behavioral
characteristics
Level of Usage
ValueofaUser

8. • Leverage more
data to build
predictive
modeling and
advanced
statistical
analysis
• Smaller, more-
specific segments
help stretch users
to drive behavior
that is
incremental
• User-level
segmentation
• Segment based
on app usage
(opens,
purchases, etc.)
• Bucket users
together into a
manageable
number of
segments
• All users receive
a uniform
experience
• Useful for A/B
testing general
app features
None AdvancedIntermediateBasic
Example: None
Usage + Value
Scoring Buckets
User-Level Usage +
Value Scoring
K-means cluster
analysis / Machine
Learning

9.  Segmentation parameters should be aligned with business objectives
 For example: If ads are what make you money, segmentation should drive more ad revenue
 The goal is to move users up and to the right
No
Segmentation
High Value
Low Use
High Value
High Use
Low Value
Low Use
Low Value
High Use
High Value
Low Use
High Value
Mid Use
High Value
High Use
Mid Value
Low Use
Mid Value
Mid Use
Mid Value
High Use
Low Value
Low Use
Low Value
Mid Use
Low Value
High Use
Level of Usage
ValueofaUser
ValueofaUser
Level of Usage

10.  Use cluster analysis to identify user groups that behave similarly
 Cluster analysis leverages statistics to allow users to group according to pre-
determined behavioral factors (purchase events, app feature usage, etc.)

11. Shrinking
Growing
New
User
Steady
Eddy

12. Paid UA ReferralOrganic UA
Download
Data Collection
 Source
 Time to Register
 Demographics
 Name
 Age
 Gender
 Zip/State
 iOS/Android
Actionable Targeting Data
User Behavior
(Opens, app
events, etc.)
CustomerSupport&Resolution
Data Collection
Engagement Level & Timing
(How long does it take a
user to cycle through funnel)
Data Collection
Frequency & Volume
(Avg 1.2 per week, 2
wk/month)
Data Collection
 Time
 App Events
 Ad Engagement
 Clicks
 Customer
Support contact
 Details for each
engagement or
behavior

13. Source Source
Needs:
1) User Linked Across all
Platforms
2) Dynamic Learning/Updates
3) Data Warehouse
4) Personalization Tools
Actionable Targeting Data
App
Events
Ad
Interaction
Content
Likely to
Churn
Other
Variables
Likely to
be Power
Likely to
Refer
Source
Internal External
Communications
In
App
Email Push Ads URUA
Data (Predictive, Manipulation, etc)
Data, Content &
Communication
Triangle

14.  Risks:
 Users notice differences and get frustrated
 Segmentation is too complex to manage efficiently
 Law of Unintended Consequences
 Limitations:
 Don’t house or collect all of the right data
 Can’t align across internal and external tools
 Don’t have the capabilities in-house to build

15. None Basic +72%
Increase in App
Events
Basic Intermediate +44%
Increase in App
Events

16.  TEST EVERY CHANGE IN SEGMENTATION!
 Improve segmentation incrementally (and know what every improvement is worth)
 Align segmentation with business goals
 Let the data dictate your strategy
 Build back end systems with future segmentation in mind
MAKE SEGMENTATION A CORE COMPETENCY!