Important Metrics in Mobile App Analytics

Analytics had now evolved to adapt a new platform. Mobile app analytics is getting more relevant as the mobile app industry continues to rise. But unlike other business models, apps doesn’t have a single key performance indicator (KPI) that would determine its success. The app industry is dynamic and volatile at the same time. About 22% of downloaded apps only get used once with users uninstalling apps almost instantaneously after installation.

According to a survey conducted by Tapdaq, only 5% of the 90% of developers who have a third party analytics SDK implementation in their apps know how to properly interpret the data they track. This is understandable since most mobile app developers just want to see revenue. But mobile app analytics exists as a means of tracking data pertinent to the performance of the app and user behavior that can drive long-term revenue. It is more than present downloads and revenue. So how can you make the most out of app analytics? Learn the ropes through familiarization of the most important metrics of course.

Important metrics in mobile app analytics can be divided into four main categories: acquisition, engagement, retention and monetization.

Acquisition

The user acquisition stage is what drives your app into motion. You can acquire users either through organic search, paid campaigns, in-app referrals or word-of-mouth. Metrics that you should focus on are:

• Installs

These are easy to track since it is readily provided by all app stores.

• Customer Acquisition Cost (CAC)/ Cost per Install (CPI)

The formula for CAC is total marketing and sales cost/number of new users. This metric is important especially as a benchmark in scaling your user acquisition efforts. CAC is a general metric. To track this metric further, use different channels for user acquisition like referrals and advertisements.

CPI refers to the cost of every app install through advertising. It is one of the common advertising models used especially in game apps. There are platform averages for CPI ($1.43 for iOS, $2.12 for Android for July 2015) but it can vary depending on the type and budget of every ad campaign. It is important to track CPI in the long run. If the cost of your CPI campaign is more than the lifetime value (LTV) of your users, then you won’t be raking much profit unless it is offset by organic installs.

• Demographics

Demographic data is important, especially for localization. It can also give you an idea on regional trends and discrepancies in your target demographic compared to the demographic that is actually using your app.

• Attribution

Attribution is the tracking of the source of installs or other actions done through an ad network. This is to evaluate which ad network performs best in terms of ad views and engagement, cost effectiveness and number of users acquired.

 

Engagement

Downloads are good if you have a paid app without any other monetization model in store. If you have a freemium app, on the other hand, you’ll want more positive user engagement data. In order to evaluate user engagement, you need to track the following metrics.

• Session Length

Session length is the length of time from when a user opens an app until either the said user becomes inactive or the user terminates the app. Google Analytics considers a session over after 30 minutes of inactivity. Other mobile app analytics tools have different parameters for session termination due to inactivity.

Tracking session length is important in finding out if your users spend enough time on the app to make any action that would translate into monetization.

• Session Interval (Recency)

Tracking the frequency of a user’s app session is also important since it can signify interest on the app especially if the session intervals are close to each other and are on a regular basis.

•  Time in App

Time in app is different from session length in a sense that it tracks the total time (regardless of how many sessions it took) a user spent on your app for a certain period of time. This data is useful in ascertaining when, how and why your users interact with your app.

• Screen Flow

The screen flow or screens metric tracks down the user’s navigation from screen to screen. It tells how they interact with each screen and if there are problem areas that can hinder conversion and identify screens with high drop out rates.

 

Retention

Retention metrics are very important, especially after the first month when the app has peaked in the number of users and drop off rate is getting steep. Engagement is useless if there aren’t enough users that can sustain the app’s growth.

• Retention Rate

One of the most popular formula for retention rate is the “rolling retention method”.

Day N = number of retained users on Day+N/number of users who installed the app on Day 0.

• Users (DAU, MAU)

The number of daily and monthly active users can be used to track the “stickiness” of your app. It is closely tied to the engagement and retention metrics. Users can also give you an insight on what to improve. Available data like user behavior that can lead to monetization and usage statistics.

• Churn Rate

The opposite of retention rate, churn rate measures the number of users that stop using your app during a specified time.

•  Cohort Analysis

A cohort is defined as a group of users who share common criteria during a certain period of time. Cohort analysis facilitates the understanding the relationship of behavior within and between different cohorts. This way you can determine the most profitable segment of your app. You can also observe how trends and changes like updates affect user engagement over time.

 

Monetization

• Average Revenue per User (ARPU)

ARPU is basically the revenue that each app user generates. To get the value of ARPU, divide the total revenue on a specific time period by the total number of active users. You can specifically calculate revenue from daily active users using ARPDAU (Average Revenue per Daily Active Users). This metric is vital for game apps. There are no solid benchmarks for ARPU and ARPDAU for each app category and revenue model. As of the second quarter of 2016, the game app subgenre with the highest ARPDAU is “role playing” with $0.66.

• Lifetime Value (LTV)

LTV measures the revenue per user in the entire duration of his/her usage of your app. It is one of the most important revenue metrics. The formula for LTV is: LTV = ARPUxAU/Churn.

 

The app industry may be new but it is just like any industry with standards and best practices. Mobile app analytics has the same framework used by traditional business models. But just like most things, metrics and practices need to change and adapt according to the needs of the new platform. Mobile and web analytics are similar yet very different. That’s why it is important to pay attention what really matters in mobile app analytics. The screen might’ve become smaller, but certainly not the competition.