When ordering the development of inexpensive applications, you should immediately think about evaluating the effectiveness. For some it is measured by the number of downloads, for others the number of users is important. Some bet on increasing brand awareness. Others care more about conversion and sales through the app.

There are many metrics to evaluate the effectiveness of apps. Which ones? An overview of the metrics prepared by the experts of the company KITAPP will help you understand them.
efficiency metrics

Performance metrics of mobile apps related to users

Attracting users is one of the key tasks mobile app developers and customers have to accomplish. Naturally, when evaluating effectiveness, you should focus on metrics related to users. And there are quite a few of them. Let’s take a look at a few of the main ones.

Number of installations

Many people attach great importance to this metric. Yes, it is useful to know the number of installations. But this metric does not give a complete picture of success. After all, users immediately after installing an application can delete it, or install it “for the checkmark” and not use it. The number of installations is worth considering as a certain baseline needed to calculate other metrics.

Daily Active Users (DAU)

DAU (Daily Active Users) are the users that interact with an application on a daily basis (daily active). Agree, if a person regularly uses a program, spending their time on it, then we can talk about the usefulness, quality of the product, etc. For business applications this metric is usually considered as a measure of success of a software product.

No formulas are required to calculate DAU – this is the number of UNIQUE users per day. The uniqueness is determined by the ID or login. You can get this figure with the help of analytics systems (e.g. Google Analytics or AppMetrica).

Where there is DAU, there is WAU and MAU.

WAU and MAU show the number of active users per week and month, respectively. By manipulating these three metrics, you can extract useful information for your business. For example, by dividing the DAU by the MAU, you can calculate the weekly engagement rate (also called “stickiness” or loyalty). This is an important metric. The higher it is, the higher the engagement and regularity of using the app.

DAU, WAU and MAU are important metrics for attracting partners and investors. They are the first thing many people look at.

PCU and ACU for effective decision making

PCU (Peak Concurrent User) – The highest number of users (“peak”) who are in the application at the same time. Usually peaks are during the same periods of time. ACU (Average Concurrent User) shows the average number of users online.

This information is useful, for example, when managing advertising in the application. With the help of these indicators, it is possible to manage displays with a focus on the highest activity hours.

LTV, CPA and RPU

LTV (lifetime value). The mobile app performance metric shows how much can be earned on the average user for as long as he is a customer. It is calculated by multiplying the average conversion value, the average number of conversions over the time a customer was using the app, and the average number of conversion actions.

The metric is very popular and widespread among mobile app owners. It is advisable to use it in conjunction with another effective metric – CPA. CPA (cost per acquisition or price per user) shows the effectiveness of advertising and user acquisition campaigns.

The greater the difference between LTV and CPA (in favor of LTV), the more effective the app is and the more a business earns per user.

Another popular metric to help solve the problem of how to measure an app’s effectiveness is ARPU (Average Revenue Per User). This is the average revenue per user. It is calculated as the income from the application during a certain period divided by the number of installations (users) for this period. ARPU is also called Current LTV.

IMPORTANT. LTV and ARPU are averaged metrics after all. It’s necessary to take into account that statistically only 0.15% of users generate half of revenue from an application (depending on specificity). And if you just rely on these figures, the data can be far from ideal, it turns out “smeared”. Therefore, if you operate with LTV and ARPU, when analyzing them, pay attention to download and removal rates, the length of user session, traffic and other indicators. That is, the analysis must be comprehensive.

In order to understand what income a paying user brings on average, ARPPU is used. It is calculated by analogy with ARPU: the income from the application for a certain period is divided by the number of paying users.