Do you know how to solve the 3 most important equations in APP operation?

During APP operation , there are a large number of data indicators that need to be tracked and analyzed to determine the overall operation status of the APP. We understand that one of the biggest challenges for independent developers in the process of APP operation is to understand what each data point means and how to improve related product functions and operational ideas based on the information fed back by these data indicators.

In theory, we should not ignore any data we are tracking. This article will focus on what I think are the three most important equations. While explaining their definitions, I will also tell you how I calculated them. Now let’s get started.

1. Retention Rate

Retention rate is the percentage of users who return to the app within a specific time frame after the initial installation. Retention rate is also one of the indicators to measure the "stickiness" of the application. The more valuable your app is to users, the more frequently your app will be used (and the less likely it will be deleted).

It’s now incredibly easy to download and delete apps on both iOS and Android, and many believe that user retention is becoming a bigger challenge as app stores mature. So, how do you calculate your app’s retention rate? Well, there are actually many ways. Here is a relatively simple method.

First, you need to look at the percentage of users who returned to your app on Day + N or any day thereafter, and divide that by the number of users who installed your app on Day 0.

For example:

Let’s say you want to calculate your app’s retention rate on day 7.

If there are 1,000 downloads on day 0 and 260 users open the app on day 7, then the user retention rate is 26%. Keep in mind that after 7 days, if more users continue to open the app from the original 1,000, they are also classified as “retained”.

2. Churn Rate

Churn rate is the exact opposite of retention rate, as it measures the rate at which your app loses users over a specified period of time (usually measured monthly). When calculating your app’s churn rate, try to count the number of users who left your app (the number of people who may have left). (Remember, churn can never be 0% or less).

Let's look at an example:

If your app starts with 1,000 users, then that means 1,000 people are likely to leave the app over the next month, however, at the end of the month, you realize that only 340 users left the app. This means your churn rate is 34%.

3. LTV (Lifetime Value)

LTV is arguably the most important metric of all because it tells you how much you spend to acquire a new customer. In my operational experience , unless you have a consistently high ranking in the app store and make up for the losses from other free download channels , if the CPI (cost per install) exceeds the average user LTV, we will not be able to acquire new users sustainably.

To calculate a user’s LTV, there are a few data points we need to know and understand:

• Revenue: This is a simple metric, which is all the revenue generated by the app, whether it is app advertising, in-app purchases, paid downloads or subscriptions. (Don’t forget to factor in the 30% off on Apple/ Google Play !).
• Active Users: This is the definition used for active users. I personally think this should include users who become inactive after being active for a period of time and users who have not yet purchased premium content in the APP.
• Average Revenue Per User ( ARPU ): Tracking ARPU is easy to do because it is just revenue generation. ARPU focuses on the profit an operator makes from each user over a period of time. Obviously, the more high-end users there are, the higher the ARPU. To calculate, simply divide revenue by the number of active users in a given time period…
• Customer churn: This indicator has been mentioned in the second point, so I won’t explain it in detail here.

At this point, if we have all the data listed above, our equation for calculating LTV is as follows:

As above, let’s use some actual numbers here to make things easier to understand.

example:

If the average revenue per user of the app is $0.40 and the churn rate is 34%, the lifetime value is $1.18. Assuming the average cost per install is over $2 and our app’s actual LTV is $1.18, we can’t sustainably continue buying install ads in this way.

Final Words

As I mentioned above, there are many more important metrics that are crucial for an app. However, I believe these 3 equations can determine how good your app actually performs. Of course, using tools can also simplify things. Tools such as App Annie and Tapdaq can provide ARPU data. In general, these equations are not too difficult to calculate. All we have to do is to continuously improve our work based on the values ​​they provide.

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This article was compiled and published by @Cicada Master (Qinggua Media). Please indicate the author information and source when reprinting!