Measuring mobile app effectiveness

4 types of mobile app metrics that must be reported

A mobile app's raison d'être, just like any other product, is to generate more money for its creator than it costs to build. Use mobile app analytics to evaluate effectiveness of your mobile app marketing methods and to ensure ad spending leads to installations, and installations lead to app use and in-app purchasing. To review your approach to measuring app effectiveness, here are 4 types of measure we recommend.

1 Tracking the number of installs

One of the key metrics regardless of the app business model is the number of daily installs and their sources. Do your installs come from mobile ads or from app store directly? What is the split between paid and free sources of users and how does it change over time? Tracking paid and free installs are the basic metrics every mobile marketer should track from day one.

Answering these questions is important because an objective of a mobile marketer is to find marketing channels that generate paying users at the lowest possible cost. If all users come from mobile ads, the cost per install (CPI) becomes very expensive. The average current rate is $2, and even $2,5 for iOS apps. So every free install will reduce overall cost of user acquisition and improve effectiveness of your marketing efforts.

Finding your way to the top of the app stores, the source of free users, is the surest way of keeping your CPI down. Initially, this may require a hefty outlay, but once visible in the top of the charts the free, organic downloads should start coming in and mitigating those costs. Hence it is also important to keep track of your app rank in the app store and how it changes over time.

To get to the top of the app store you might need to buy cheaper installs, so-called incentivised installs that are counted towards getting your app to the top ranks but not effective in bringing paying users.

Knowing the number of incentivised, non-incentivised and organic installs is therefore also important, because of the difference in CPI and expected user lifetime value.

2 Virality metric

Another source of free users are your existing users. Look at virality factor to evaluate how many new users your existing users bring into the app by tracking sharing links.

Your app's virality metric is a complicated figure. It's  worked out by, amongst other things, counting the number of users that came from a viral channel, calculating the average number of users generated by your existing user over his lifetime of using your app.

Broadly speaking, the virality metric indicates how much you can lower your expected cost per install (CPI) by.

If your CPI is $2, but you acquire a new user through a current user telling them about your app, rather than any effort you put into marketing, then that $2 you spent to get that original user has, in fact, bought you two users. Therefore your CPI has now dropped to $1.

3 How expensive is your user acquisition cost?

Keeping track of your installations and where they are coming from is vital in working out, which of your advertising channels are performing, and which are just sucking down your money.

Using an independent tracker to monitor this, such as Adjust.com or Google Mobile App Analytics, is a better idea than relying on information supplied directly by your ad networks.

Your cohort analyses metric is determined dividing the total revenue generated from a particular group of users, or cohort, by the number of users in that cohort. A cohort is a segment of users defined by traffic source, country and device. Working out which channel is bringing you the most users is the purpose of cohort analysis. By finding the most effective cohorts from your many ad sources you can target your users better to increase their LTV and ARPU.

4 Long-term value - The end game is user LTV

Calculating the user lifetime value and seeing that it exceeds the cost per install is what the business of a mobile app is about. So unless your app is a cost center for a brand marketing, keeping track of app revenue per user is essential to manage an app as a business.

User lifetime value (LTV) is a measurement of revenue brought in by a user during their time of using the app. This number is then used to help work out the return on investment the app will generate.

The cost per install, or cost of user acquisition, takes into account the money spent on marketing and divides it by the amount of installations over a period of time. This is used in conjunction with the LTV to calculate return on investment.

Average revenue per user is calculated by taking the total revenue per user and dividing it by the LTV.

• Retention metrics

Your app's user retention metric is measured by counting the users that return on a daily basis, then dividing by the total users in the group monitored.

Tracking your user retention can be a tricky business. While most mobile analytics platforms track the number of app sessions to give an idea of retention, their idea of a session is an app being opened. Google Mobile App Analytics however counts openings occurring within thirty minutes of each other as one session which is a better approach.

Churn rate is the opposite. This is your percentage of users that do not re-open your app.

And from there...

Many app developers create their own metrics to analyse, depending on what factors are important to them or their app such as user experience, improving monetisation or increasing retention rate.

For example, a bank may publish an app and track events that signify cost savings, because the user did not use other, more expensive customer care channels such as telephone banking or a visit to a local branch.

For this reason, analytics services often offer the facility to set up a way to measure distinct variables not covered by the standard, ready-packaged metrics.

For instance, Google Mobile App Analytics allows developers to segregate paying users from non-paying users and thus monitor them separately.

If your app marketing requires tracking custom metrics, you should review the degree of customization offered by the analytics services and discuss your needs with your app developer.