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Top app monetization
      tactics…


    Pratik Shah | Product Manager
A bit
about
Myself..
What do these entities have in
c   o   m     m     o   n    ?
“The deeper the understanding
                                  “We are an analytics company
 we have about our customers
                                    masquerading as a games
and our products, the better we
                                           company”
   can connect with them.”




 Data. Insights. Actions.
                                    Oakland A’s manager Billy
 Citibank is exploring possible      Beane based his winning
     uses for IBM’s Watson           strategy on rigorous data
   supercomputer in mining        analysis to acquire top baseball
        customer data.                        players.
This is all great…..
How the heck is this relevant for an app developer?
700K iOS & Android apps   60% app developers don’t profit   30% apps used only once


               It’s a tough world out there..
        Only the intelligent app businesses will win!
Agenda: Improve App monetization by focusing on your users



Best practices
‣    Monetization models
‣    Key metrics & ARM cycle

Customer segmentation
‣    Why
‣    How

Use cases
‣    Acquisition
‣    Retention
‣    Monetization
Best
Practices
Monetization: Variety of monetization models




   Consumer                 Advertiser
     pays                     pays
   Paid downloads,               Banner,
  in-app purchases,         interstitial, cross
   merchandizing,            promote, offer
    subscription..                walls..
Embrace the power of Freemium model




The best part? Not limited to gaming apps..
Metric driven? Don’t get lost in vanity metrics…




          Did you catch the funny ones?
Keep it simple: Focus on value maximization during ‘ARM’ cycle

                                      Basics
                                      ‣  App value = Number of users * LTV of each user


  Acquisition             Retention   LTV of each user
                                      ‣  Lifetime value
                                      ‣  LTV = value * engagement


                USERS                 Value levers
                                      ‣  Monetization
                                      ‣  Virality
                                      ‣  Loyalty
 Monetization                         ‣  UGC & Community
                                      ‣  Feedback
                                      ‣  Marketplace (Downloads, Ratings & Comments)


    In order to focus on monetization, it is important to look beyond
                            monetization..
Audience

Track key    ‣  Daily Active Users (DAU) &
                Monthly Active Users (MAU)
             ‣  Demography
metrics in   Acquisition
             ‣  Cost per acquisition (CPA)

the ‘ARM’    ‣  ROI on campaigns (Value - CPA)
             Retention

cycle        ‣  Stickyness (DAU/MAU)
             ‣  Retention rate
             Monetization
             ‣  Conversion rate
             ‣  ARPU & ARPPU
Customer
segmentation
Lets borrow an industry best practice..

 Loyal                                31%

 Newly                     24%
 acquired
                                 ‣    Customer segmentation - a practice
 Dormant             18%              of:
                                      ‣  Dividing a customer base into buckets that are
 Engaged                                 similar in specific ways (spending, engagement
                   16%                   etc.)
                                      ‣  On which they can take targeted actions to
 Socially          16%                   extract the maximum marketing value.
 active
 Advanced    13%                 ‣    Traditionally, retail marketers have
                                      used segmentation as an important
 Whales10%                            technique


                                 ‣    In order to maximize the value
                                      levers, app developers need to adopt
                                      the same sophisticated techniques.
Customer segmentation: How does it work?

                               Basics
                               ‣    Use a rule engine to define user behavior & attributes to
                                    define a segment


                               Dimensions
                               ‣    Purchase history
                               ‣    Time spent
                               ‣    Session length
                               ‣    Advancement
                               ‣    Session frequency
                               ‣    Country, Carrier, Device
                               ‣    ….


                               Examples
                               ‣    S1: IF purchase history > 25 percentile of my app
                               ‣    S2: IF purchase history > $10
                               ‣    S3: IF purchase history > $10 & Time spent < 5 minutes in last
                                    month


    Need to track key metrics with the prism of each segment
Use cases
Lets put it to use in the ‘ARM’ cycle?



              Acquisition                Retention




                            USERS

             Monetization
Acquisition: Leverage organic techniques

                   Basics
                   ‣  Expensive to pay to acquire users unless you
                      have a well oiled positive ROI engine (LTV >
                      CPA)

                   Measurement
                   ‣  Cost per acquisition (CPA)
                   ‣  ROI on campaigns (LTV/CPA)


                   Techniques
                   ‣  Internal cross promote (Keeping users within
                      your app portfolio) is the best but needs to be
                      done properly..
                   ‣  Viral is very cost effective, but also very
                      difficult
                   ‣  Performance networks (display, cross promote)
                      are widely used to acquire further users
Identify pattern:
Highly engaged users from USA are
most likely to give you viral uplift



Segment using rule engine:
IF (time spent > 300 hours) &
(country == USA)



Incentivize virality
Segment: Social influencers




Reduce your CPA by as much as 50%
Identify pattern:
Advanced users in your top app
don’t have other apps in your
portfolio


Segment using rule engine:
IF (levels crossed > 25) & (! Using
omegajump)


Smart cross promote
Segment: ‘ripe’ users



Increase ROI by acquiring known users
Retention: Use a variety of techniques at different user stages

                                     Basics
                                     ‣  Difficult.. but certainly most important


                                     Measurement
                                     ‣  Stickyness (DAU/MAU)
                                     ‣  Retention rate (% of returning users across
                                        months)
                                     ‣  Cohort analysis
                                     ‣  Measure how many users return for 2nd time, 3rd
                                        time and so on…

                                     Techniques
                                     ‣  Clean early experience
* Playnomics Q3 2012 report
                                     ‣  Localize content
                                     ‣  Gamification: Rewards, challenges etc…
Identify pattern:
New users are likely to be delighted
to see a tailored message



Segment using rule engine:
IF (App launches < 5) & (country ==
China)



Localized ‘welcome’
Target segment: New Chinese users




Increase retention beyond day 1
Identify pattern:
User engagement can be improved
with a social taunt



Segment using rule engine:
IF (user time spent in last month <
50% of average time spent)



Social ‘taunt’
Target segment: Waning users




Increase engagement by 30%
Monetization: Use tiered pricing


                 Basics
                 ‣    Price goods along the curve based on capacity
                      of each customer

                 Measurement
                 ‣  Conversion rate (% paying)
                 ‣  ARPU & ARPPU
                 ‣  Customer profile split
                      ‣    Whales (10% users, 60% revenue)
                      ‣    Dolphins (30% users, 30% revenue)
                      ‣    Minnows (60% users, 10% revenue)


                 Techniques
                 ‣  Holiday & event specific
                 ‣  Timely offers
Identify pattern:
Hardcore users would pay a lot for
certain features

Segment using rule engine:
IF (user time spent == high) & (app
section == ‘tough’)


Timely unlocks
Target segment: Hardcore users




    Display offers at right time
Identify pattern:
High paying users in developed
economies tend to purchase a lot
during holidays

Segment using rule engine:
IF (user purchase history == high) &
(date == 31st Oct) & (country ==
USA || UK)


Holiday promotion
Target segment: High paying US and
UK users


Add cyclic bursts to your sales
‣    Step 1: Deciding what data will
                  be collected and how it will be
How does a   ‣ 
                  gathered
                  Step 2: Collecting data from
developer    ‣ 
                  various sources
                  Step 3: Developing methods of

do all of         big data analysis for
                  segmentation
             ‣    Step 4: Building in-house
this?             message server - scaled
                  globally!

             ….Could this all be easier?
Thank you   Pratik Shah
            Product Manager, InMobi
            Pratik.shah@inmobi.com

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Top Mobile App Monetization Tactics You Ought to Know

  • 1. Top app monetization tactics… Pratik Shah | Product Manager
  • 3. What do these entities have in c o m m o n ?
  • 4. “The deeper the understanding “We are an analytics company we have about our customers masquerading as a games and our products, the better we company” can connect with them.” Data. Insights. Actions. Oakland A’s manager Billy Citibank is exploring possible Beane based his winning uses for IBM’s Watson strategy on rigorous data supercomputer in mining analysis to acquire top baseball customer data. players.
  • 5. This is all great….. How the heck is this relevant for an app developer?
  • 6. 700K iOS & Android apps 60% app developers don’t profit 30% apps used only once It’s a tough world out there.. Only the intelligent app businesses will win!
  • 7. Agenda: Improve App monetization by focusing on your users Best practices ‣  Monetization models ‣  Key metrics & ARM cycle Customer segmentation ‣  Why ‣  How Use cases ‣  Acquisition ‣  Retention ‣  Monetization
  • 9. Monetization: Variety of monetization models Consumer Advertiser pays pays Paid downloads, Banner, in-app purchases, interstitial, cross merchandizing, promote, offer subscription.. walls..
  • 10. Embrace the power of Freemium model The best part? Not limited to gaming apps..
  • 11. Metric driven? Don’t get lost in vanity metrics… Did you catch the funny ones?
  • 12. Keep it simple: Focus on value maximization during ‘ARM’ cycle Basics ‣  App value = Number of users * LTV of each user Acquisition Retention LTV of each user ‣  Lifetime value ‣  LTV = value * engagement USERS Value levers ‣  Monetization ‣  Virality ‣  Loyalty Monetization ‣  UGC & Community ‣  Feedback ‣  Marketplace (Downloads, Ratings & Comments) In order to focus on monetization, it is important to look beyond monetization..
  • 13. Audience Track key ‣  Daily Active Users (DAU) & Monthly Active Users (MAU) ‣  Demography metrics in Acquisition ‣  Cost per acquisition (CPA) the ‘ARM’ ‣  ROI on campaigns (Value - CPA) Retention cycle ‣  Stickyness (DAU/MAU) ‣  Retention rate Monetization ‣  Conversion rate ‣  ARPU & ARPPU
  • 15. Lets borrow an industry best practice.. Loyal 31% Newly 24% acquired ‣  Customer segmentation - a practice Dormant 18% of: ‣  Dividing a customer base into buckets that are Engaged similar in specific ways (spending, engagement 16% etc.) ‣  On which they can take targeted actions to Socially 16% extract the maximum marketing value. active Advanced 13% ‣  Traditionally, retail marketers have used segmentation as an important Whales10% technique ‣  In order to maximize the value levers, app developers need to adopt the same sophisticated techniques.
  • 16. Customer segmentation: How does it work? Basics ‣  Use a rule engine to define user behavior & attributes to define a segment Dimensions ‣  Purchase history ‣  Time spent ‣  Session length ‣  Advancement ‣  Session frequency ‣  Country, Carrier, Device ‣  …. Examples ‣  S1: IF purchase history > 25 percentile of my app ‣  S2: IF purchase history > $10 ‣  S3: IF purchase history > $10 & Time spent < 5 minutes in last month Need to track key metrics with the prism of each segment
  • 18. Lets put it to use in the ‘ARM’ cycle? Acquisition Retention USERS Monetization
  • 19. Acquisition: Leverage organic techniques Basics ‣  Expensive to pay to acquire users unless you have a well oiled positive ROI engine (LTV > CPA) Measurement ‣  Cost per acquisition (CPA) ‣  ROI on campaigns (LTV/CPA) Techniques ‣  Internal cross promote (Keeping users within your app portfolio) is the best but needs to be done properly.. ‣  Viral is very cost effective, but also very difficult ‣  Performance networks (display, cross promote) are widely used to acquire further users
  • 20. Identify pattern: Highly engaged users from USA are most likely to give you viral uplift Segment using rule engine: IF (time spent > 300 hours) & (country == USA) Incentivize virality Segment: Social influencers Reduce your CPA by as much as 50%
  • 21. Identify pattern: Advanced users in your top app don’t have other apps in your portfolio Segment using rule engine: IF (levels crossed > 25) & (! Using omegajump) Smart cross promote Segment: ‘ripe’ users Increase ROI by acquiring known users
  • 22. Retention: Use a variety of techniques at different user stages Basics ‣  Difficult.. but certainly most important Measurement ‣  Stickyness (DAU/MAU) ‣  Retention rate (% of returning users across months) ‣  Cohort analysis ‣  Measure how many users return for 2nd time, 3rd time and so on… Techniques ‣  Clean early experience * Playnomics Q3 2012 report ‣  Localize content ‣  Gamification: Rewards, challenges etc…
  • 23. Identify pattern: New users are likely to be delighted to see a tailored message Segment using rule engine: IF (App launches < 5) & (country == China) Localized ‘welcome’ Target segment: New Chinese users Increase retention beyond day 1
  • 24. Identify pattern: User engagement can be improved with a social taunt Segment using rule engine: IF (user time spent in last month < 50% of average time spent) Social ‘taunt’ Target segment: Waning users Increase engagement by 30%
  • 25. Monetization: Use tiered pricing Basics ‣  Price goods along the curve based on capacity of each customer Measurement ‣  Conversion rate (% paying) ‣  ARPU & ARPPU ‣  Customer profile split ‣  Whales (10% users, 60% revenue) ‣  Dolphins (30% users, 30% revenue) ‣  Minnows (60% users, 10% revenue) Techniques ‣  Holiday & event specific ‣  Timely offers
  • 26. Identify pattern: Hardcore users would pay a lot for certain features Segment using rule engine: IF (user time spent == high) & (app section == ‘tough’) Timely unlocks Target segment: Hardcore users Display offers at right time
  • 27. Identify pattern: High paying users in developed economies tend to purchase a lot during holidays Segment using rule engine: IF (user purchase history == high) & (date == 31st Oct) & (country == USA || UK) Holiday promotion Target segment: High paying US and UK users Add cyclic bursts to your sales
  • 28. ‣  Step 1: Deciding what data will be collected and how it will be How does a ‣  gathered Step 2: Collecting data from developer ‣  various sources Step 3: Developing methods of do all of big data analysis for segmentation ‣  Step 4: Building in-house this? message server - scaled globally! ….Could this all be easier?
  • 29. Thank you Pratik Shah Product Manager, InMobi Pratik.shah@inmobi.com