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App Lifecycle Engagement
JoshTodd, CMO
Agenda
•  Mobile Trends
•  App Lifecycle
•  Predictive App Marketing
OUR APP-ETITE
IS GROWING.
22 MIN.
60.3 MIN.AMOUNT OF TIME PER DAY
THE AVERAGE US MOBILE
CONSUMER SPENDS WITH
APPS.
00:22
The amount of time
the average US
mobile consumer
spends per day with
apps:
AMOUNT OF TIME PER
DAY THE AVERAGE US
CONSUMER SPENDS ON
THE MOBILE WEB.
Nielsen & Comscore, 2014
48,000APPS ARE DOWNLOADED FROM
THE APPSTORE EVERY 60
SECONDS.
Mashable, 2014
Nielsen, 2014
41APPS ARE
INSTALLED ON THE
AVERAGE
US SMARTPHONE.
25%
THE PERCENTAGE
OF USERS WHO
ONLY OPEN AN
APP ONCE.
Localytics,
2015
19%
23%
29%
42%
48%
68%
71%
Forced social logins
Privacy concerns
Intrusive ads
Bad UI/UX
Freezing
Complex registration
Annoying notifications
TOP 7 REASONS WHY PEOPLE
UNINSTALL MOBILE APPS*
*AS A % OF ALL
RESPONDENTS.
EACH
PARTICIPANT
MENTIONED
THREE
REASONS.
Agenda
•  Mobile Trends
•  App Lifecycle
•  Predictive App Marketing
The App Lifecycle
Acquire Engage &
Grow
Retain
Acquire	
  
App Store Optimization
Gain
visibility in
app store
searches
Optimize
your app
store listing
Organic Channels – Website Redirect
Redirect mobile
website traffic to
your app
Organic Channels – Email
Encourage email
subscribers to
download your app
53%
of emails are opened on a
mobile device.
Source: Litmus, 2015
Organic Channels – Social Media
Promote your app on
social platforms
Paid Channels – Mobile Ads
Source: Litmus, 2015
Work with a mobile
advertising company to
place targeted ads in
other apps
NOT EVERYONE
WHO DOWNLOADS YOUR
APP
WILL BECOME
A USER.
Source: Localytics, 2015
Of users only use an
app ONCE.
25%
Source: Localytics, 2014
60%The likelihood that an app user who doesn’t return within 7 days
will NEVER COME BACK.
Paid Channels – Attribution
Use an app analytics platform that partners with major
ad networks to track user acquisition campaigns
The App Lifecycle
Acquire Engage &
Grow
Retain
Engage	
  &	
  Grow	
  
Maximize user value through engagement
•  Segmentation
•  Channels to the customer
•  Push
•  In-App
•  Remarketing
•  Email
(your entire userbase)
Sports Apparel App
Segment your audience
3% of broadcast push
messages are clicked
7% of targeted push
messages are clicked
15% of users converted 54% of users converted
Broadcast: Targeted:
Segment your audience
vs
Imagine an app with 100,000 users
Segment your audience
Broadcast: Targeted:
3% of 100,000 users =
3,000 opened messages
7% of 100,000 users =
7,000 opened messages
15% of 3,000 opened
messages =
450 converted users
54% of 7,000 opened
messages =
3,780 converted users
vs.
Segment your audience
vs
Maximize user value through engagement
•  Segmentation
•  Channels to the customer
•  Push
•  In-App
•  Remarketing
•  Email
Bring them back and keep them engaged with Push
Motivate inactive users to
return to your app with
targeted, carefully timed, and
well-written copy
88% MORE
Users with push enabled have
app launches.
Source: Localytics, 2014
Increase Push audience, increase success
52% of app users have push
enabled on their phones
Industry Averages
Increase Push audience, increase success
52% of app users have push
enabled on their phones
48% of app users don’t have
push enabled on their phones
Industry Averages
Bad Example
- Ask them to opt in
immediately after launching
the app for the first time
Increase Push audience, increase success
(first launch)
- Welcome your users with a
sequence of introductory,
how-to screens to show
value
1 2 32 3
Increase Push audience, increase success
Good example
Good example
- Welcome your users with a
sequence of introductory,
how-to screens to show
value
- THEN, ask them to opt in
with a unique, well-designed
in-app message
Increase Push audience, increase success
In-App Messages – Drive Conversions
Move users further along
funnels to ultimate in-app
action with beautiful, branded,
in-app creatives
4X HIGHER
In-app messages presented based
on an event have
conversion rates.
Remarketing – Reaching Existing Users
Source: Litmus, 2015
Show current users ads based
on how they’ve previously
engaged with your brand
Great for reaching the
who opt out of push notifications
48% OF USERS
Email – Cross Channel Marketing
Treat users with richer, longer
form content
Source: Copyblogger, 2014
The App Lifecycle
Acquire Engage &
Grow
Retain
Retain	
  
5yearsago…
theworldwasawashinBigData
Data Scientists to the Rescue
Still not fulfilling the promise of big data
But still… 50% of all
Data Science
Projects Fail
Apps Create a New Opportunity
Apps generating massive
amounts of data AND
have marketing channels
embedded
Advances in computing have
made machine learning more
accessible
Users Demand Better
Experiences
Pillars of Predictive App Marketing
Predic5ve	
  Segmenta5on	
  
•  The	
  dynamic	
  grouping	
  of	
  users	
  into	
  segments	
  which	
  will	
  behave	
  in	
  similar	
  ways	
  
Marke5ng	
  Auto-­‐Op5miza5on	
  
•  The	
  automa8c	
  tes8ng	
  and	
  op8miza8on	
  of	
  a	
  marke8ng	
  strategy	
  across	
  mul8ple	
  channels	
  
	
  
Na5ve	
  Personaliza5on	
  
•  The	
  1:1	
  matching	
  of	
  users	
  to	
  content,	
  products,	
  with	
  which	
  they	
  	
  have	
  the	
  greatest	
  affinity	
  
Keys to Successful Predictive App Marketing
Define	
  the	
  specifics	
  of	
  the	
  objec8ve	
  -­‐	
  Churn	
  
Take	
  ac8on	
  via	
  the	
  app	
  (via	
  push,	
  in-­‐app	
  msg,	
  etc.)	
  
Establish	
  Baseline	
  and	
  iden8fy	
  user	
  paIerns	
  of	
  user	
  
behavior	
  and	
  correlated	
  characteris8cs	
  
Define	
  objec8ve	
  –	
  Churn	
  =	
  users	
  who	
  have	
  visited	
  the	
  
app	
  at	
  least	
  twice,	
  but	
  not	
  in	
  the	
  last	
  30	
  days	
  
Predictive Churn Example for a Sports App
*Measured	
  as	
  %	
  ac8ve	
  users	
  with	
  no	
  ac8vity	
  in	
  past	
  30	
  days.	
  
Auto-­‐segmented	
  new	
  users	
  into	
  the	
  at	
  risk	
  buckets	
  and	
  
sent	
  personalized	
  push	
  messages	
  to	
  drive	
  users	
  back	
  
into	
  the	
  app	
  
Predictive Churn Example for a Sports App
Control Group Experimental Group
Users! 190,930! 189,900!
Returned! 115,243! 120,112!
Churn %*! 39.3%! 36.8%!
Improvement — 6.6%
Users Rescued — 4,928
*Measured	
  as	
  %	
  ac8ve	
  users	
  with	
  no	
  ac8vity	
  in	
  past	
  30	
  days.	
  
Predictive Churn Example for a Sports App
*Measured	
  as	
  %	
  ac8ve	
  users	
  with	
  no	
  ac8vity	
  in	
  past	
  30	
  days.	
  
Predictive Churn Example for a Sports App
Control Group Experimental Group
Users! 3,383,031! 381,723!
Returned! 565,930! 102,500!
Churn %*! 83.3%! 73.1%!
Improvement — 14%
Users Rescued — 38,644
*Measured	
  as	
  %	
  ac8ve	
  users	
  with	
  no	
  ac8vity	
  in	
  past	
  30	
  days.	
  
Predictive Churn Example for a Lifestyle App
52
Predictive App Marketing Across the Lifecycle
Acquire Engage &
Grow
Retain
53
How we got here and where we are going
2012	
   2013	
   2014	
   2015	
   2016	
   2017	
  
Personalized	
  Content	
  &	
  UI	
  	
  
Deep	
  Automa8on	
  &	
  Lifecycle	
  Management	
  
Personalized	
  Messaging	
  (Push,	
  In-­‐app,	
  Email,	
  Remarke8ng)	
  	
  
Behavioral	
  Analy8cs	
  (Mobile,	
  Web,	
  3rd	
  Party,	
  Cross-­‐app)	
  	
  
User	
  Insights	
  (Profiles,	
  Segments,	
  User	
  Acquisi8on)	
  
Machine	
  Learning	
  Predic8on	
  &	
  
Op8miza8on	
  
2009	
  -­‐	
  2011	
   2018	
  
Op5mized	
  
Engagement	
  
Rich	
  Data	
  
Thank you
Day of the week
Day of the week
Time of day
Time of day
Length of your message
Length of your message
Reactive
Proactive
User
Engagement
Historical	
  
Data	
  
Machine	
  
Learning	
  
Predic5ons	
  
FinallyShiftingusTowardProactiveMarketing
62
AppsaretheSelfContainedUnit
63
Understand your
app user’s intent
before he or she acts.
64
Adjust your app
marketing
accordingly to reduce
churn risk and improve
conversions.
“In 2008, everyone thought apps were a fad.
They couldn’t have been more wrong. Apps
have become the dominant way we interact
with information – and the world.
Raj Aggarwal
CEO, Localytics

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App Lifecycle Engagement

  • 2. Agenda •  Mobile Trends •  App Lifecycle •  Predictive App Marketing
  • 4. 22 MIN. 60.3 MIN.AMOUNT OF TIME PER DAY THE AVERAGE US MOBILE CONSUMER SPENDS WITH APPS. 00:22 The amount of time the average US mobile consumer spends per day with apps: AMOUNT OF TIME PER DAY THE AVERAGE US CONSUMER SPENDS ON THE MOBILE WEB. Nielsen & Comscore, 2014
  • 5. 48,000APPS ARE DOWNLOADED FROM THE APPSTORE EVERY 60 SECONDS. Mashable, 2014
  • 6. Nielsen, 2014 41APPS ARE INSTALLED ON THE AVERAGE US SMARTPHONE.
  • 7. 25% THE PERCENTAGE OF USERS WHO ONLY OPEN AN APP ONCE. Localytics, 2015
  • 8. 19% 23% 29% 42% 48% 68% 71% Forced social logins Privacy concerns Intrusive ads Bad UI/UX Freezing Complex registration Annoying notifications TOP 7 REASONS WHY PEOPLE UNINSTALL MOBILE APPS* *AS A % OF ALL RESPONDENTS. EACH PARTICIPANT MENTIONED THREE REASONS.
  • 9. Agenda •  Mobile Trends •  App Lifecycle •  Predictive App Marketing
  • 10.
  • 11. The App Lifecycle Acquire Engage & Grow Retain
  • 13. App Store Optimization Gain visibility in app store searches Optimize your app store listing
  • 14. Organic Channels – Website Redirect Redirect mobile website traffic to your app
  • 15. Organic Channels – Email Encourage email subscribers to download your app 53% of emails are opened on a mobile device. Source: Litmus, 2015
  • 16. Organic Channels – Social Media Promote your app on social platforms
  • 17. Paid Channels – Mobile Ads Source: Litmus, 2015 Work with a mobile advertising company to place targeted ads in other apps
  • 18. NOT EVERYONE WHO DOWNLOADS YOUR APP WILL BECOME A USER.
  • 19. Source: Localytics, 2015 Of users only use an app ONCE. 25%
  • 20. Source: Localytics, 2014 60%The likelihood that an app user who doesn’t return within 7 days will NEVER COME BACK.
  • 21. Paid Channels – Attribution Use an app analytics platform that partners with major ad networks to track user acquisition campaigns
  • 22. The App Lifecycle Acquire Engage & Grow Retain
  • 24. Maximize user value through engagement •  Segmentation •  Channels to the customer •  Push •  In-App •  Remarketing •  Email
  • 25. (your entire userbase) Sports Apparel App Segment your audience
  • 26. 3% of broadcast push messages are clicked 7% of targeted push messages are clicked 15% of users converted 54% of users converted Broadcast: Targeted: Segment your audience vs
  • 27. Imagine an app with 100,000 users Segment your audience
  • 28. Broadcast: Targeted: 3% of 100,000 users = 3,000 opened messages 7% of 100,000 users = 7,000 opened messages 15% of 3,000 opened messages = 450 converted users 54% of 7,000 opened messages = 3,780 converted users vs. Segment your audience vs
  • 29. Maximize user value through engagement •  Segmentation •  Channels to the customer •  Push •  In-App •  Remarketing •  Email
  • 30. Bring them back and keep them engaged with Push Motivate inactive users to return to your app with targeted, carefully timed, and well-written copy 88% MORE Users with push enabled have app launches. Source: Localytics, 2014
  • 31. Increase Push audience, increase success 52% of app users have push enabled on their phones Industry Averages
  • 32. Increase Push audience, increase success 52% of app users have push enabled on their phones 48% of app users don’t have push enabled on their phones Industry Averages
  • 33. Bad Example - Ask them to opt in immediately after launching the app for the first time Increase Push audience, increase success (first launch)
  • 34. - Welcome your users with a sequence of introductory, how-to screens to show value 1 2 32 3 Increase Push audience, increase success Good example
  • 35. Good example - Welcome your users with a sequence of introductory, how-to screens to show value - THEN, ask them to opt in with a unique, well-designed in-app message Increase Push audience, increase success
  • 36. In-App Messages – Drive Conversions Move users further along funnels to ultimate in-app action with beautiful, branded, in-app creatives 4X HIGHER In-app messages presented based on an event have conversion rates.
  • 37. Remarketing – Reaching Existing Users Source: Litmus, 2015 Show current users ads based on how they’ve previously engaged with your brand Great for reaching the who opt out of push notifications 48% OF USERS
  • 38. Email – Cross Channel Marketing Treat users with richer, longer form content Source: Copyblogger, 2014
  • 39. The App Lifecycle Acquire Engage & Grow Retain
  • 42. Data Scientists to the Rescue
  • 43. Still not fulfilling the promise of big data But still… 50% of all Data Science Projects Fail
  • 44. Apps Create a New Opportunity Apps generating massive amounts of data AND have marketing channels embedded Advances in computing have made machine learning more accessible Users Demand Better Experiences
  • 45. Pillars of Predictive App Marketing Predic5ve  Segmenta5on   •  The  dynamic  grouping  of  users  into  segments  which  will  behave  in  similar  ways   Marke5ng  Auto-­‐Op5miza5on   •  The  automa8c  tes8ng  and  op8miza8on  of  a  marke8ng  strategy  across  mul8ple  channels     Na5ve  Personaliza5on   •  The  1:1  matching  of  users  to  content,  products,  with  which  they    have  the  greatest  affinity  
  • 46. Keys to Successful Predictive App Marketing Define  the  specifics  of  the  objec8ve  -­‐  Churn   Take  ac8on  via  the  app  (via  push,  in-­‐app  msg,  etc.)   Establish  Baseline  and  iden8fy  user  paIerns  of  user   behavior  and  correlated  characteris8cs  
  • 47. Define  objec8ve  –  Churn  =  users  who  have  visited  the   app  at  least  twice,  but  not  in  the  last  30  days   Predictive Churn Example for a Sports App
  • 48. *Measured  as  %  ac8ve  users  with  no  ac8vity  in  past  30  days.   Auto-­‐segmented  new  users  into  the  at  risk  buckets  and   sent  personalized  push  messages  to  drive  users  back   into  the  app   Predictive Churn Example for a Sports App
  • 49. Control Group Experimental Group Users! 190,930! 189,900! Returned! 115,243! 120,112! Churn %*! 39.3%! 36.8%! Improvement — 6.6% Users Rescued — 4,928 *Measured  as  %  ac8ve  users  with  no  ac8vity  in  past  30  days.   Predictive Churn Example for a Sports App
  • 50. *Measured  as  %  ac8ve  users  with  no  ac8vity  in  past  30  days.   Predictive Churn Example for a Sports App
  • 51. Control Group Experimental Group Users! 3,383,031! 381,723! Returned! 565,930! 102,500! Churn %*! 83.3%! 73.1%! Improvement — 14% Users Rescued — 38,644 *Measured  as  %  ac8ve  users  with  no  ac8vity  in  past  30  days.   Predictive Churn Example for a Lifestyle App
  • 52. 52 Predictive App Marketing Across the Lifecycle Acquire Engage & Grow Retain
  • 53. 53 How we got here and where we are going 2012   2013   2014   2015   2016   2017   Personalized  Content  &  UI     Deep  Automa8on  &  Lifecycle  Management   Personalized  Messaging  (Push,  In-­‐app,  Email,  Remarke8ng)     Behavioral  Analy8cs  (Mobile,  Web,  3rd  Party,  Cross-­‐app)     User  Insights  (Profiles,  Segments,  User  Acquisi8on)   Machine  Learning  Predic8on  &   Op8miza8on   2009  -­‐  2011   2018   Op5mized   Engagement   Rich  Data  
  • 55. Day of the week
  • 56. Day of the week
  • 59. Length of your message
  • 60. Length of your message
  • 61. Reactive Proactive User Engagement Historical   Data   Machine   Learning   Predic5ons   FinallyShiftingusTowardProactiveMarketing
  • 63. 63 Understand your app user’s intent before he or she acts.
  • 64. 64 Adjust your app marketing accordingly to reduce churn risk and improve conversions.
  • 65. “In 2008, everyone thought apps were a fad. They couldn’t have been more wrong. Apps have become the dominant way we interact with information – and the world. Raj Aggarwal CEO, Localytics