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The Lifecycle of Apps: How to Engage Customers at Every Stage

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App Lifecycle Engagement Josh Todd, CMO


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Agenda •  Mobile Trends •  App Lifecycle •  Predictive App Marketing


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OUR APP-ETITE IS GROWING.


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60.3 MIN. The amount of time the average US mobile consumer spends per day with apps: AMOUNT OF TIME PER DAY THE AVERAGE US MOBILE CONSUMER SPENDS WITH APPS. 00:22 22 MIN. AMOUNT OF TIME PER DAY THE AVERAGE US CONSUMER SPENDS ON THE MOBILE WEB. Nielsen & Comscore, 2014


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Mashable, 2014 48,000 APPS ARE DOWNLOADED FROM THE APPSTORE EVERY 60 SECONDS.


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Nielsen, 2014 41 APPS ARE INSTALLED ON THE AVERAGE US SMARTPHONE.


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25% THE PERCENTAGE OF USERS WHO ONLY OPEN AN APP ONCE. Localytics, 2015


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TOP 7 REASONS WHY PEOPLE UNINSTALL MOBILE APPS* Forced social logins Privacy concerns Intrusive ads Bad UI/UX Freezing Complex registration Annoying notifications 19% 23% 29% *AS A % OF ALL RESPONDENTS. 42% 48% 68% 71% EACH PARTICIPANT MENTIONED THREE REASONS.


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Agenda •  Mobile Trends •  App Lifecycle •  Predictive App Marketing


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The App Lifecycle Acquire Engage & Grow Retain


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Acquire  


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App Store Optimization Gain visibility in app store searches Optimize your app store listing


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Organic Channels – Website Redirect Redirect mobile website traffic to your app


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Organic Channels – Email Encourage email subscribers to download your app 53% of emails are opened on a mobile device. Source: Litmus, 2015


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Organic Channels – Social Media Promote your app on social platforms


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Paid Channels – Mobile Ads Work with a mobile advertising company to place targeted ads in other apps Source: Litmus, 2015


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NOT EVERYONE WHO DOWNLOADS YOUR APP WILL BECOME A USER.


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25% Of users only use an app ONCE. Source: Localytics, 2015


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60% The likelihood that an app user who doesn’t return within 7 days will NEVER COME BACK. Source: Localytics, 2014


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Paid Channels – Attribution Use an app analytics platform that partners with major ad networks to track user acquisition campaigns


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The App Lifecycle Acquire Engage & Grow Retain


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Engage  &  Grow  


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Maximize user value through engagement •  Segmentation •  Channels to the customer •  Push •  In-App •  Remarketing •  Email


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Segment your audience Sports Apparel App (your entire userbase)


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Segment your audience Broadcast: 3% of broadcast push messages are clicked 15% of users converted vs Targeted: 7% of targeted push messages are clicked 54% of users converted


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Segment your audience Imagine an app with 100,000 users


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Segment your audience Broadcast: Targeted: vs vs. 3% of 100,000 users = 3,000 opened messages 15% of 3,000 opened messages = 450 converted users 7% of 100,000 users = 7,000 opened messages 54% of 7,000 opened messages = 3,780 converted users


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Maximize user value through engagement •  Segmentation •  Channels to the customer •  Push •  In-App •  Remarketing •  Email


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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 Users with push enabled have 88% MORE app launches. Source: Localytics, 2014


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Increase Push audience, increase success Industry Averages 52% of app users have push enabled on their phones


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Increase Push audience, increase success Industry Averages 52% of app users have push enabled on their phones 48% of app users don’t have push enabled on their phones


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Increase Push audience, increase success Bad Example - Ask them to opt in immediately after launching the app for the first time (first launch)


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Increase Push audience, increase success Good example - Welcome your users with a sequence of introductory, how-to screens to show value 1 2 3


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Increase Push audience, increase success 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


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In-App Messages – Drive Conversions Move users further along funnels to ultimate in-app action with beautiful, branded, in-app creatives In-app messages presented based on an event have 4X HIGHER conversion rates.


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Remarketing – Reaching Existing Users Show current users ads based on how they’ve previously engaged with your brand Great for reaching the 48% OF USERS who opt out of push notifications Source: Litmus, 2015


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Email – Cross Channel Marketing Treat users with richer, longer form content Source: Copyblogger, 2014


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The App Lifecycle Acquire Engage & Grow Retain


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Retain  


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5 years ago… the world was awash in Big Data


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Data Scientists to the Rescue


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Still not fulfilling the promise of big data But still… 50% of all Data Science Projects Fail


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Apps Create a New Opportunity Users Demand Better Experiences Advances in computing have made machine learning more accessible Apps generating massive amounts of data AND have marketing channels embedded


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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  


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Keys to Successful Predictive App Marketing Define  the  specifics  of  the  objec8ve  -­‐  Churn   Establish  Baseline  and  iden8fy  user  paIerns  of  user   behavior  and  correlated  characteris8cs   Take  ac8on  via  the  app  (via  push,  in-­‐app  msg,  etc.)  


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Predictive Churn Example for a Sports App Define  objec8ve  –  Churn  =  users  who  have  visited  the   app  at  least  twice,  but  not  in  the  last  30  days  


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Predictive Churn Example for a Sports App Auto-­‐segmented  new  users  into  the  at  risk  buckets  and   sent  personalized  push  messages  to  drive  users  back   into  the  app   *Measured  as  %  ac8ve  users  with  no  ac8vity  in  past  30  days.  


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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.  


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Predictive Churn Example for a Sports App *Measured  as  %  ac8ve  users  with  no  ac8vity  in  past  30  days.  


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Predictive Churn Example for a Lifestyle 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.  


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Predictive App Marketing Across the Lifecycle Acquire Engage & Grow Retain 52


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How we got here and where we are going 2009  -­‐  2011   2012   2013   2014   2015   2016   2017   2018   Op5mized   Engagement   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)   Rich  Data   Machine  Learning  Predic8on  &   Op8miza8on   53


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Thank you


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Day of the week


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Day of the week


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Time of day


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Time of day


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Length of your message


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Length of your message


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Finally Shifting us Toward Proactive Marketing Historical   Data   Reactive Machine   Learning   User Engagement Proactive Predic5ons  


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Apps are the Self Contained Unit 62


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Understand your app user’s intent before he or she acts. 63


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Adjust your app marketing accordingly to reduce churn risk and improve conversions. 64


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“ 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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