Your best users provide your greatest source for reviews, growth and feedback.
You have an app. You have users. Your analytics say you have some users that use your app a lot, others seem to try it once and then never return. But how do you recognize those best users and encourage them to use your app more often? This is where actionable segmentation comes in.
There are a lot of app analytic tools available for app developers. From Flurry to Google Analytics, you have plenty of tools to show you how often your app is opened, clicked or used, but not many ways to make actionable decisions or actions from that data within your app. For app developers, there really are only a few key metrics that really work for recognizing user behavior and providing easy tools for adding incentives for better engagement. Those metrics are almost the same as retail stores have used for years to segment their customers.
Who knew that my time selling comic books would directly help me with app development?
When I was in retail, we used two metrics to categorize our customers and find incentives to make them our super customers. Because I was in the comic business, ‘super’ was an appropriate term for our best customers.
Our super customers showed up at 2 am to buy the latest Magic the Gathering release. They’d come in every week, remembering our last conversation, helping unbox product on new comic day. They would passionately share their favorite new comic with their friends and relatives and complete strangers in the store, and even tell them to buy it at our store. They purchased from our stores first before going to a secondary source for something we didn’t have or couldn’t get. While the comic business is light years away from app development, the tools we used are highly applicable to today’s app marketing.
In retail, the two key metrics are how often they shopped at the store and how much they spent. To measure that, we needed to know our averages, which just involved a lot of counting. Modern technology makes this so much easier.
Our average customer came into the store every two weeks and spent about $14 each visit. So customers who visited weekly and spent more than $14 were our Super customers. Simple, right?
With these two metrics, we now had four groups of customers, and we could create marketing plans for each group.
Group 1—Here are our super customers. They keep the doors open and the lights on. We would have special events outside of business hours for them, put unique promo items aside for them that we knew they would like, or give them special discounts when available. These customers are special, and we treated them that way.
Group 2 —Visited, more often than average, but spent less than average. These are the customers we saw as often as our Super customers, but they didn’t spend as much. To help get them into Group 1, we gave them coupons that would encourage them to spend more than average to get the discount. Because our average transaction was $14, we would give them a coupon for $10 off any purchase of $40 or more. And we could see them wandering around the store, adding things to their pile and adding it up in their head. But after they’d spend more than $14 several times, we didn’t need to give them the incentive anymore.
Group 3—Visited less often than average, but spent more each trip. Here, we wanted to get these customers to just come in more often so they might get a series of coupons that required each one to be used in sequence—such as one a week—over a period of time to get to the last and best coupon. Or we’d give them a coupon that couldn’t be used on the same day but had to be used within the next 7 days.
Group 4—These were our general every-so-often customers. We wouldn’t try to get them from Group 4 to Group 1 right away. We would make a decision to try to encourage them first into either Group 2 or 3 first, before making the jump to Group 1. Either get them visiting more often or get them to spend more each visit. From there, you then move them into Group 1 using the above tools.
With this in mind, what metrics should an app developer use to find their Super Users?
Let’s start with average opening of the app and average time in the app—two easy to track metrics.
The App User Segmentation chart would look something like this:
Group 1—These are your Super Users that open the app more often than average and spend more time in it than average. These are the users you want to focus on for app reviews, social sharing, promotions, and rewards. Most likely, they’re already sharing your app with their friends, so find more ways to encourage it and reward them.
Group 1—These are your Super Users that open the app more often than average and spend more time in it than average. These are the users you want to focus on for app reviews, social sharing, promotions, and rewards. Most likely, they’re already sharing your app with their friends, so find more ways to encourage it and reward them.
Group 2—These are opening your app more often, but spending less time in it. You should use them to find out why they have shorter app sessions and find ways to get them to stay in the app longer. Depending on your app, this can be anything from free coins at the end of a gameplay, extra targeted content, or anything that keeps them around just a little longer.
Group 3—Here are your infrequent users that like using your app, but just don’t think about it as much. Here, you need to look for ways to bring your app back to the front of their mind—or the center of their home screen. App notifications, push messages or email all work to bring your app back to a user’s attention.
Group 4—These are the bulk of the users that used your app once and deleted it or started to use it and stopped. Here, you want to find incentives to bring them back at least once or twice and see if you can move them into Group 2 or 3. They’re also a good potential source for surveys on why they didn’t use the app more than a couple of times.
How do you get this segmentation in your app and act on it? Most analytic tools don’t provide this. Instead, they focus on usage, but not on how to change engagement.
Enter AppToolkit.io’s super user and Cloud Config.
Using the AppToolkit SDK, you can immediately start getting Super User data and see it live and create actions within the app to target those users. Instead of asking every user to leave you a review, only ask your Super Users. They’re more likely to do it and more likely to leave a positive 5-star review. Working on a new feature and want some helpful feedback? Ask your Super Users to either test it in-app, limiting it to just them or ask them to join a TestFlight build.
Once you can identify and interact with your apps Super Users, you can use them to grow your app faster. They’re more likely to review it, mention it in social media, promote it to their friends, and give you your best feedback.
Within the Super User dashboard, you can drill down to specific user history:
This user has had three sessions since the beginning of April, totaling 61.5 minutes. Right now, this app doesn’t do user registration, either voluntarily or required, but that’s easy enough to add. Once we include any form of user registration, we can then engage with this user within the app using the code on the side of the user dashboard. With the ability to see user devices, iOS, and app versions, you can tie that info into help ticket support or target specific users for updating to your latest version. Outside of that, using email to bring a user back to the app after an extended absence.
AppToolkit.io Super User is free for your first 1000 monthly average users and $0.001 cent per user over that. But finding your Super Users and growth hacking your reviews, downloads, and sales? That’s priceless. I’m sure there are other tools you can use as well. The point is to identify these users and analyze their behavior as quickly as possible to capitalize on the traction your app already has.
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