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Description

Coming up is a presentation from our App Masters Connect event in Santa Monica where Scott Ritchie, Head of Business Development at Pyze, will share why your addressable market is a lot smaller than you think, the customer value growth checklist and what moves the needle for your app business.

Scott Ritchie is the Head of Business Development at Pyze.

Show Notes

Pyze’s Development Business Head, Scott Ritchie talked about Mobile app engagement and retention:

Mobile apps need to have content that’s tailored to the user’s preference. Most app developers, however, are more focused on acquisition of new users. They are obsessed in getting all of their addressable market.

For example, an addressable market of 100 million users is enough incentive for app developers to spend a lot in acquisition. Unfortunately, the majority of that acquisition will quit using the app at various points in time. In reality, the addressable market is lot smaller for many app developers.

App developers are also aware that they can’t continue spending for acquisition indefinitely. This is also the reason why they keep on creating newer versions and the cycle starts again.

Mobile App Consumer Growth Cycle (6:56)

There are 4 growth cycles:

  1. Acquisition – subject that app developers talked about 90% of the time.
  2. Onboarding – activation, first purchases, first shares
  3. Engagement –  sustained usage of conversions, personalizing experiences, loyalty referrals, attrition, risk reengagement
  4. Retention – Not much focus on this side.

Acquisition Versus Engagement

In acquisition, it’s natural to lose a user you pay for. But with engagement, you analyze how you can retained the user.

Machine Learning

App developers can use Machine learning to cover the engagement and retention pieces without suffering from product development and creativity.

To make use of machine learning, you will need the following checklist:

  • Instrumentation of your architecture
  • Usage analytics
  • Attribution
  • Segmentation
  • Present personalization of content
  • gameplay
  • Engagement triggers
  • Retargeting triggers
  • Campaigns

What moves the needle for your business: (8:34)

There’s no point focusing all your efforts on new features if you lose your old users. Instead build the features base on your users’ behaviors and preferences. Look at the big picture, where do you want the game to head? This will require a detailed analysis of your users’ behaviors.

Events Vs. Attributes

One gaming company has 50 attributes per event. They have a very detailed definition of their users engaged with the event. The developer also uses the attribution data to drive product development and product direction with its current user base. It’s in real-team basis so they can add another event and attribute to a segment, cohort of users that they are engaged with.

Collect Your User’s Identity and Traits (10:25)

Traits are very important. If they log in you’ll be able to trace traits from web, to mobile to web so you can get that all bundled in as well. It’s also very important to engage your users

CRM data is better since you can the personalize user data. This technique is necessary to know the exact person using the app vs simple usage behavior

If you can marry the usage behavior to an ID, you have an exact idea on how it’s done, particularly if you have machine learning. When you have that ID of that particular person regardless of where his behavior changes in the events, the machine can update the data. It would identify what he’s doing and you can start triggering automated campaigns to that person through machines   

Whatever it is, keep them involved in the app, the game, whatever events that you’re creating within your ecosystem

Conclusion:

Today, machine learning has the ability to capture data today with one just line. It will built segment of users that will tell you if you’re going to retain or lose a user. You can combine these users across devices, like android and iPhone. Even with different apps, you can combine that data, cross it, to identify those segments. Machine learning can drive engagement by showing each user their preferred content.