Reimagine Growth: Analytics and segmentation

Learn the Growth Secrets
of Top Mobile Brands

Find your silver bullet with analytics and
segmentation

You’ll learn about…
Using the Recency,
Frequency, and
Monetary (RFM) analysis
framework to convert
loyal customers into
influencers
Applying cohort
analysis, and intent-
based segmentation to
fuel growth
Leveraging analytics to
understand what your
users are doing on
your app once you’ve
acquired them

Our Speakers
Backed by an engineering degree from IIT Bombay,
Shobhit spent his 20s in three entrepreneurial ventures
and finally took up his first job at the age of 30. Shobhit is
presently responsible for growing Disney+ Hotstar –
India’s largest OTT platform and the future of
entertainment.
https://www.linkedin.com/in/shobhitsinghal1/
SABYASACHI SAHU
Customer Success Manager
Sabyasachi is a senior consultant with 5+ years of
experience that spans multiple functions in product.
At CleverTap, he’s been responsible for helping
clients across India and Europe, from early stage
startups to multi-billion dollar enterprises for driving
growth.
https://www.linkedin.com/in/sabyasachisahu/
SHOBHIT SINGHAL
Associate Director, Product

Growth @ Disney+ Hotstar
Associate Director, Product
SHOBHIT SINGHAL

What does Growth mean at D+ Hotstar
How do we ascertain which Metrics to grow
How do we set up Analytics
How do we build Segmentation frameworks &
Cohorts
How does analytics translate into User
Intelligence
How does insight inform Personalisation
How does personalisation create Growth Loops
Here’s the Line Up

Cohorts
Intelligence
Getting Started

Grow What Exactly?
I want to maximise time spent
- Time spent is a metric that many
consumer internet apps relying on ad-
led revenue care about
I want to maximise revenue
- Revenue could be a metric mature
companies post Product Market Fit
may care about

For Hotstar, Growth = Max User Base
150M MAU
8M Paying Users

Cohorts
Intelligence
Sounds Simple, But...

Keep It Simple
Simple Equations >> Complex Equations
Define a North Star
Extract L1 and L2 metrics from the North Star

Measure of Success = Subscriber Growth
We want users to become paying customers because higher LTV + more loyalty
Subscriptions North Star → L1s
Acquisitions ChurnSubs Growth

Acquisitions = Convert free users + Acquire users via marketing + Organic
➔ Convert free users → Show relevant paid catalogue to free users
➔ Marketing → Optimise each step of the performance marketing funnel
➔ Organic → Easy and frictionless journey to subscribe
Churns = Users who cancel + Non-renewers on non-recurring plans
➔ Users who cancel → build more engagement with Hotstar
➔ Non-renewers on non-recurring → convert both negatives to positives
Subs L2

Measure of Success = Watch Time
As an OTT platform, the amount of time spent by users watching videos is a strong indicator of the health of our platform
Engagement North Star → L1s
Acquisition
No. of Users
Frequency of
visit
Time Spent
per visit
Retention Engagement
Watch Time

No. of Users = MAU = Acquisition
Frequency = Active Days per Week X Active Weeks per Month
Time Spent per Visit = (1/ bounced) X Time spent engaging
Engagement L2

Cohorts
Intelligence
Getting the Basics Right

Early Stage
You probably have 1-2 apps
Talk to peers/leaders about metrics
Talk to industry experts. Work with
Clevertap CS teams (paid plug 😅)
Focus instrumentation on key insights
You support 95% of the platforms you
want to be on; for us that’s 12 apps
Source-of-truth Data Dictionary is
mandatory
Start assigning a risk value to events
and properties. Talk to peers
Eg: Shobhit will lose his job if the
“Watched Video” event breaks
Set up alerts on event volumes and
values
Growth Stage Late Stage
Everything you are doing for data
quality is a year late
Remove dependency on client apps
and release cycles
Automate schema quality; social
development practices
Invest in anomaly detection based on
how many PMs have lost their jobs -
Talk to people :-)
Talk to People

Fear of Branal © (Broken Analytics)
● Fear & Monetary Impact can do what good conscience cannot
● We built the Bifrost Platform to help us manage, govern and our data flow
● We have quality validations, server side enrichment and sampling capability

Cohorts
Intelligence
Making Cohorts Cool Again

Worthy Segments
Hotstar 2018 - Business Insight
MAU
● IPL would drastically move up the
baseline
● Many users would churn out when
IPL was over
● New baseline of active users =
step function growth
● Users would stay back for non-
cricket
Worthy Segment:
Users who first watched cricket && then
watched non-cricket content (C2E)

2020: No IPL, Now What?
Hotstar 2020 - Business Insight
“Avengers: Endgame” Theatre Performance
● There is an equally sized market for
content dubbed in Indian languages
● Launched AE on Hotstar in Nov 2019 in
English, Hindi, Tamil and Telugu
● Offered lower price points for HTT
● Launched Disney+ in Indian languages
Worthy Segments:
1. Users who watch entertainment content in
Indian languages
2. Users paying for higher and lower priced
plans and differences in language consumption
2x tickets sold for AE in
Indic Languages
Indic rev = English rev

Week 0 Week 1 Week 2 Week 3
98% 88% 81% 77%
97% 91% 83% 79%
98% 87% 88% 80%
97% 90% 85% 84%
Returning % →
Acquisition
Apr W4
Apr W3
Apr W2
Apr W1
Closer Look at Retention

What Can We do With Segments?
Re-activation
Facebook / DBM
Spend some money
for win-back
Analytics
BI Tools
Understand
conversion metrics
for each segment
Notifications
Clevertap
Push / nudge users
likely to perform
desirable actions
We built a platform to allow user segmentation and refreshing cohorts at scale. We deploy
connectors to send “lists” of users for various applications:

Cohorts
Intelligence
Get Smart, Quickly

Let’s Focus on More Subs
We wanted to identify which users can convert into paying customers
Massive free user base
● We created paid value propositions
out of our content catalogue
● Latest movies, Specials
● Disney+ :-)
Worthy Segments:
1. Users who sample, click on paid content
2. Users who watch on more than 1 device
Overall Entertainment
Value Proposition for
Indian Households
Multiple Hooks to
Subscribe

Some Parameters Stood Out
Device Cost
Metro Cities
Watched Cricket
&& Entertainment
WiFi vs 4G
Streaming Quality
Age
Number of Devices

Birthing a Model - Propensity to Pay
Predicted
Scores
DAU
Subs
Acquisitions
< 0.1 9% 0.5%
< 0.2 9% 0.3%
< 0.3 9% 0.5%
< 0.4 9% 1%
< 0.5 9% 1%
< 0.6 9% 2%
< 0.7 9% 3%
< 0.8 9% 5.5%
< 0.9 10% 12%
>0.9 20% 75%
● Break the variables down further
Example: what are the fundamental metrics that
influence device cost? Dig deeper
● Remember Branal:
Which metrics have high coverage and high accuracy
● Test early and frequently
● Most Customer Intelligence platforms help get started
quickly - Clevertap, Amplitude, Mixpanel

Cohorts
Intelligence
Pursuing the Holy Grail

Key Elements of Personalisation
Recommendation
Best guess, Increases
Future Gratification
Best of Hotstar for You - Masthead
Top Picks For You
You May Also Like based on X
Watch Next
3
Realisation
Deterministic, Enables
Faster Gratification
Continue Watching
Watch List
Shows / Tournament You Watched
Recent Search History
2
Customisation
User Selects, Invests
before Gratification
Preferences during Onboarding
Profiles
Content Rating (Kids safe)
1

Cohorts
Intelligence
Closing The Loop

Closing The Loop
App Learns More
About the User’s
Preferences
User Watches Content
OR
Does Not Engage
OR
Browse/Search
Shown Content to Watch
Based on Everything We
Know About the User
User Comes to App
CORE LOOP

THANK YOU
LinkedIn: linkedin.com/in/shobhitsinghal1 || singhal.shobhit@gmail.com

CleverTap
Segmentation and Analytics
Customer Success Manager
SABYASACHI SAHU

Segmentation
● Real Time Segmentation:
○ Segmenting users who start
watching the Wimbledon
● Behavioral segmentation:
○ Segmenting freemium users
and understanding their intent
to purchase subscription
● Interest Based segmentation:
○ Segmenting users based on
the genre they watched, so
that the latest releases can be
sent out to them

Intent based Segmentation
● Micro-Segmentation of the users
based on their Intent

RFM
Auto-Segmentation Tool
● Defining the power users so that
the new feature can be shared
with them
● Defining the users who are
about to churn
● Defining the loyalists and
sharing the content

Cohorts
● See the number of freemium users
returning after the premier
release/ sports season and
purchasing

Trends
● Trend:
○ Understanding the average
charged
● Trend Comparison:
○ Comparing the
video/product watch trend of
the premium vs freemium
users
○ Seeing the purchase trends
of user from different
regions

Funnels
● Funnel:
○ Understanding the drop off for
the new users after watching
free content
○ Understanding the median
time
● Funnel comparison:
○ Comparing users to different
regions and seeing where is
the maximum conversion

Pivots and Flows
● Flows:
○ Checking how freemium users
navigated once they first come to the
app
● Pivots:
○ Seeing the video consumption trend
during the day in different regions or
different segments

Real Impact
● Seeing average conversions for
subscription
● Measuring the primary KPIs as
compared to the control groups
○ Revenue per user
○ Stickiness of the App
○ Recency of the user

Thank You!
marketing@clevertap.com

Reimagine Growth: Analytics and segmentation

Recomendados

Recomendados

Mais conteúdo relacionado

Mais de CleverTap

Mais de CleverTap (20)

Último

Último (20)

Reimagine Growth: Analytics and segmentation