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
doesnt 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 dont 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 theyve 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 anity
Keys to Successful Predictive App Marketing Dene the specics 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
Dene 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 (Proles, 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 users 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 couldnt have
been more wrong. Apps have become the dominant way we interact with
information and the world. Raj Aggarwal CEO, Localytics