An Introduction to Mobile Analytics

When I made my first iphone app, it completely bombed. The design was shitty. Sales sucked. It presented zero value proposition for users. I hoped to at least recoup my investment in time and money, but I had no idea what to do to improve the situation.

Should I pay a professional copywriter to improve the app description? Should I revamp the design? Did I just need to add a few extra features?

Two painful years of trial and error later, I’ve come to realize that the key to finding these answers lies in numbers. Mobile App Entrepreneurs should track key metrics to understand the actions that influence their business. There are literally zillions of numbers you can track, but Dave McClure from 500 startups recommends the pirate acronym “AARRR” to represent the numbers you need to be tracking, which I think this is a great framework. The acronym stands for Acquisition, Activation, Referral, Retention, Revenue.

This post will attempt to elaborate on the key metrics that all Mobile App Entrepreneurs should be thinking about.


Traffic – If you’re not used to tracking metrics, the easiest metric to get started is to look at total traffic. Within the app store, app downloads are your traffic measure. Use a free service such as App Annie to track specific app downloads over time. Review this constantly to see if downloads are decreasing, understand why, and think about what you can do to fix this. Maybe that spike in downloads came from writing a press release, getting reviewed on an app review site, or even getting on Apple’s featured app list.

Rankings – visibility is key within the app store based on how users are currently discovering apps. The startup, Chomp, used to publish a monthly report on AppStore keyterms before they were acquired by Apple. But even without them, it is fairly intuitive to just think like a new user. How does you find a good app? You browse the top lists overall and the top lists in a specific category. There are lot of tools that can help track rank, but I like to use a website called AppFigures to track AppStore ranking. (Note: this is a paid tool, but I consider it worthwhile because mobile traffic acquisition is so heavily influenced by rankings right now). Without running a fancy regression analysis and purely going off anecdotal evidence that anyone can find using a google search, you’ll see that there is a high correlation between app store ranking and the number of downloads you get.

If you’re an Eric Ries fan, you might realize that traffic and rank are mostly what he terms “vanity metrics,” which are numbers that make you feel good, but don’t actually tell you much about your business. A more advanced measure of your acquisition numbers is to look at daily active users (DAU) and monthly active users (MAU). An active user might be defined differently depending on your analytics software, but in general an “active” user is someone who has opened your app at least once within the previous 3 days. This is a more accurate measure to track who is actively engaged in using your product because it discounts the fluff users who just download the app out of curiosity and never use it again.


“Activation” is a bit of a nebulous term and will change depending on your business. For example, you might consider a user active if they have a registered account. However for the purposes of this discussion, we’ll consider “activated” users to be paying users. If you have a freemium version of your app and are using in-app purchases, you should think about the conversion rate of users from free to paid. This also applies to your business if you have a “lite” version of an app that is driving traffic towards a premium version.

What methods are you using to drive these users toward activation. Perhaps you’re running house ads to tell users to upgrade to paid, or maybe using a push notification to re-engage. Tracking conversion rate across all of your activation features will tell you how effective each method is and guide where you need to improve.

As a followup to the acquisition metrics outlined above, consider tracking Daily Active Paying Users (DAPU) and Monthly Active Paying Users (MAPU). You can use a free analytics tool such as Flurry to track these numbers. Ideally as you better understand your users and make product improvements and refine messaging, your active paying users will increase over time.


As with all good things in life – free is best. In order to be a sustainable business, you’re going to need to lower your cost of acquiring new users by as much as possible. One such way is the referral. A very common referral technique is to integrate a feature into your app such as a facebook and twitter share function. Music apps such as Spotify and Songza do a great job of this by allowing users to share their favorite music, which in turn shows up on newsfeeds and motivates friends to download and try the app – all at no cost to the app developer.

From an analytics perspective, you can track all the channels where new users get referred to your app by using a service like Mobile App Tracking, then use these numbers to drive improvements in messaging and features.


Retention refers to the percentage of users that download and use your app over a period of time. It’s a measure of how sticky your product is because the more engaging your app is, the longer people will want to use it, and the higher your retention rate. Even if you are terrible at monetizing a product, really high retention numbers generally indicate that a product has value and it’s only a matter of time before you as the business owner can figure out how to exchange this value for money. Facebook and Twitter are two famous examples of products that had ridiculously high retention rates and leveraged these metrics to raise a bunch of money, then figured out monetization afterwards.

Retention works a bit funny on mobile because the average user lifecycle is so much shorter on mobile products that analog mediums, such as web. For example a study by research firm, Localytics, revealed that 70% of web users will visit a given news site at least twice a month, while only 29% of mobile users will launch a given news app at least twice a month. While you want to look at the retention of users across the entire lifespan of your product, I tend to focus on these five in the short term:

  • 1 day retention
  • 2 day retention
  • 3 day retention
  • 7 day retention
  • 30 day retention

Flurry is my go-to resource for looking at retention. You can always make these calculations yourself if you know how to do a cohort analysis, but why bother because Flurry does all of the calculations for you and formats them into a nice looking graph.


How are you monetizing your app: advertising, paid, or through in-app purchases? You can track totals and individual sources of revenue with App Annie. However, as a warning, total revenue is another type of vanity metric because it’s easily influenced by factors other than your product. Instead, consider the average revenue per user (ARPU) and the average revenue per paying user (ARPPU) as a better indicator to determine if a product is lagging.

If you’ve made a mobile game, which is a category with a particularly high upper bound for in-app purchases, you will also want to run lifetime value calculations to figure out what your customers are worth. This will influence how much money you can affordably budget for marketing to acquire new users.

Lastly if you’ve already come this far, consider segmenting your users into groups. Most of the revenue is any given business is driven by a small group of core users. The verbage that describes these customer segments will vary from company to company, but it typically looks something like this: (Note – the numbers below are completely made up. Where you draw the separating lines will depend on analogs or insight you have about your own product and users)

  • Freeloaders – people that will never pay for anything
  • Minnows – paying users that will generate between a range of something like $0 – $5
  • Dolphins – paying users that generate a bit more, for example between $5 – $20
  • Whales – the users that spend a lot of time and money in your product and make up the bulk of your businesses revenue. In my arbitrarily made-up example these guys will be paying $20+ in their lifetimes.

The importance of segmenting revenue among user groups is the realization that not all users are created equal. You want to think about how you can attract more paying users by: promoting your freeloaders to paying users, promoting your minnows to dolphins, dolphins to whales, and just getting more whales in general. For example, a direct result of this type of analysis is that many games now target advertising at freeloaders to extract some form of value from this segment.


If you’re new to this, don’t stress – you don’t need to start tracking every meticulous detail immediately. However long term, I think analytics are essential for any app business because at the end of the day, all of these measures will help improve your product (either through new product features or improved messaging) so that you can deliver increased value that customers are willing to pay more for.

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