Performance indicators of games: paying conversion

What is conversion, how to calculate it and how it affects income, says Vera Karpova, analyst at devtodev.

Quite often, when discussing a particular project, we use the term “conversion”. When analyzing a product, this indicator is given a lot of attention, and any developer tries to maximize this metric.


Conversion is the percentage of users who have committed any targeted action. Such an action can be pressing the “Register” button on the landing page, going through an advertising link, or, for example, making a payment.

Just the last case we will consider in more detail, since it is he who is most important for the project. And most of all, saying “conversion” have in mind “conversion to payment”.

Before you derive the formula for conversion, I would like to note an important feature of its calculation. It consists in the fact that this indicator is calculated for a cohort, that is, for a group of users who installed the application in a certain period.

So, conversion to payment is the percentage of users who made a purchase from those who installed the application.

Conversion to Payment = Paying Users / New Users

Conversion directly affects your income. So increasing this figure, you increase the number of users who make payments, which leads to an increase in income.

Income = New users * Conversion * ARPPU

However, if the increase in conversion occurs due to a decrease in the average receipt of the user (or the price of the product), the result may turn out to be negative.

Therefore, experimenting with the conversion, it is worthwhile to monitor other financial indicators.

This is a very important point, which should pay attention! Especially when carrying out actions in the product, when the prices for goods are reduced. Far from always reducing prices leads to a decrease in income, but it is still necessary to control this.

In addition to shares and discounts on conversion may affect: product design and its individual elements. The texts of headlines and marketing offers, the simplicity and clarity of the interface, timely purchases, competent CTA-elements, the presence of positive feedback on the product and much more.

All this is quite individual for each project, and what multiplies the conversion in one product can not affect the conversion in another. But you still have to experiment to find what works for you.

Conversion analysis can be done even deeper if you use some additional approaches.

Conversion Rate Optimization

Separation of payment types

Conversion should be considered not for all payments, but separately for the first and repeated ones, which will give more understanding about the behavior of users in the product. In this case, the conversion to a second payment is the percentage of users who have made more than one payment for the analyzed period.

And re-payments can be divided into the 2nd, 3rd, N-th and count a conversion for each separately.

It is important to ensure that users, after making the first payment, do not stop there, but continue to make subsequent payments, since it is often the repeated payments that bring the most revenue.

Tracking time before the first payment is made

It’s pretty important to understand at what point users are starting to pay – immediately on the first day or after some time after installation, when they will better understand the project.

Knowing this, you can find patterns in the behavior of users, influence it and plan various marketing activities, increasing the likelihood of payment.

In addition, if the application has levels or stages, then it is worth considering the time of the first (or any other) payment in the context of these stages. This breakdown can be relevant for gaming applications where there are levels, as well as educational products or fitness applications, where the user’s progress can be divided into separate stages.

Using cohort analysis to study the metrics by days

Conversion is calculated for cohorts, and this feature can be used to track its changes over time for a certain group of users, and compare different cohorts among themselves.

Again, such an analysis is very relevant in the conduct of experiments – it is possible to estimate how the changes affected the conversion of cohorts formed before and after these changes.

There is one more metric, similar to the conversion, but, nevertheless, having a different meaning is the share of paying (paying share). But do not be confused.

Paying share = Paying users / Active users

This indicator differs from the conversion by the denominator, which is calculated from the entire active audience and is not tied to the date of installation, nor does it require cohort analysis.

In addition to the fact that the conversion affects the income of the application, it also shows the interest of users. Therefore, it will be superfluous to study their behavior and needs in order to make them relevant proposals, develop and improve the product. And remember that keeping track of how all these changes affect the percentage of paying users, you need to remember to check other equally important financial metrics.

Articles in this series:

  1. Performance Indicators: ARPU
  2. Performance Indicators: ARPPU
  3. Performance Indicators: Cumulative ARPU
  4. Games performance indicators: paying users
  5. Performance indicators of games: paying conversion
  6. Performance Indicators: ROI

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