Understanding the mobile app metrics and knowing how to track them is essential to navigating the complex and competitive app development and marketing niche. In this article we’ve listed down the 28 most useful mobile app metrics to analyze the performance of your app or marketing campaign. All these metrics are divided into four different categories so that it’s easy for you to find and understand the metrics you are most interested in. So, without any further ado, let’s have a look at the 28 best mobile app metrics.
Table of Contents
App Marketing Acquisition Metrics/Mobile Growth
1. CTR – Click Through Rate
CTR is the percentage of clicks/taps that users make on ad impressions. In my opinion, this is a fundamental metric: it is the first step in the performance funnel, which tells us how interested users are in the campaigns and ads we are working on. CTR is a metric that we must put into context by type of company, by advertising platform and by type of ad format.
2. CR – Conversion Rate
The CR in the app marketing and acquisition metrics section refers to users who, after an ad, end up downloading our app by going through the product page in the app stores. This conversion is important because it is usually where the highest percentage of users are lost. Conversion rates in the page also differ by type of app, brand recognition, channel, etc., but the average for apps is around 30%. This means that 70% of the users we manage to attract with an ad leave before downloading. For certain brands, the CR can be above 50%.
3. CPI – Cost per Installation
Cost per install (CPI) is the result of dividing the investment (in a channel, campaign, ad group, ad) by the installations obtained by each of those groups. A metric that we must add to this is the eCPI, which is the effective cost of each installation and which would be calculated taking into account all the investment in paid marketing among all the installations achieved, regardless of whether they come from paid campaigns, from own channels or from organic traffic.
The cost per installation (CPI and eCPI) depends on each project, its history, its vertical, the channel, the country, etc. Therefore, the CPI metric must always be put into context.
4. CPA – Cost per Action
Cost per action (CPA) is the result of dividing the investment -in EUROS/DOLLARS- (in a channel, a campaign, an ad group, an ad) by the actions obtained by each of these groups. Normally, CPA refers to the cost of acquiring a new buyer. But in applications where the business model is not a purchase, but, for example, a registration, CPA can refer to the cost per registration, which we call CPL (Cost Per Lead).
As with CPI, we must keep a close eye on CPA and eCPA for each operating system, channel, country, etc., as well as their evolution over time.
5. Paid Traffic / Non-Paid Traffic Relationship
The ratio of organic traffic to paid traffic or total traffic is an important metric for every project and also for the business. We must not fall into the trap of depending solely and exclusively on paid marketing campaigns. It is a very simple metric, which in my opinion, establishes one of the health metrics of a project. If we start with a new brand, we are a startup and we have limited marketing resources, it will be more difficult for us to achieve a good balance between organic (non-paid) / paid, but this does not mean that we should not keep it in mind, think and work on actions that help us achieve it.
It is also worth mentioning at this point that if we do not work on correctly labelling traffic sources with attribution tracker (MMP), all traffic coming from actions on our own channels is attributed to organic traffic. Therefore, our recommendation is to always try to measure each marketing action, or where appropriate, the increases in organic traffic, especially for campaigns on large media such as TV or actions with influencers/content creators.
In addition to these 5 metrics that I have mentioned for this section of acquisition metrics, it is important to have control over the total number of downloads, registrations, buyers, subscribers, etc. The total costs and conversion rates for each channel, operating system and country, as well as their weekly, monthly, and annual evolution.
App Usage Metrics in Mobile App Marketing
In this section we are going to look at 5 main metrics in the use of mobile applications. In terms of app marketing + usage metrics, it is true that we can go much deeper and have greater control over everything that the user does in the application and that we are interested in measuring. In this case, by focusing more on marketing and business metrics, we are going to take into account the main ones.
Although it may seem obvious, I would also like to point out that usage metrics on the web and in apps are different and different references must be taken into account. Here we are not talking about page views, but about screens, and we are not talking about cookies but about user identifiers.
We need to measure app usage or behavior metrics through a mobile analytics tool. We have Google Firebase, the most popular and free, but we also have tools that have a cost, but are much more advanced.
1. Sessions per user
The number of sessions per user refers to the average number of times that users interact with our application at different times over the time we want to analyze. It is a very basic but very interesting metric, since depending on the application, it can indicate the use and “engagement” that users have with your app. Here we must also put into context the type of application and the vertical in which it is located. We can imagine that the average sessions per user of an app in the social media vertical is different from a fitness app and a finance app.
2. Session duration
Session duration tells us how long the user spends in the session. Like the previous metric, we must put this metric into context by app type. We may think that the longer the user is in an app, the better, but that is not always the case. I can think of 3 very specific cases: a delivery app will want the user to have a short session but to convert to order in the shortest time possible.
A news app will want the user to remain in the session for as long as possible consuming content (screens) and, therefore, to be shown the largest number of ads (more business). In games, on the other hand, the duration of the session must be analyzed in greater depth. For example, a user spending a lot of time in a game can be positive, since it can indicate that they like it and are entertained. However, users spending a lot of time on a specific level may not be so good due to the difficulty required to overcome that level, this can cause frustration and not want to return.
3. Behavior flows
Using different tools, we can analyze user behavior in certain processes within the application: onboarding, registration, purchase, trial, etc. This behavioral flow metric is very interesting to analyze in the initial phases of the project to understand how users are understanding our app, how many users we are losing along the way, and how many users complete the action of the process we are analyzing. It also becomes very important in the maturity phases of a project, where any improvement in behavioral flows is a challenge and an achievement to celebrate.
4. Crashes / Bugs
This metric is usually more related to the product or development team, who are the ones who must control the crashes and bugs in the app. We must know what errors exist in the application, the details of each error and be able to solve them. However, those of us on the marketing and business side must be informed of the most serious errors in the app in case we have to stop, for example, acquisition campaigns.
In the ASO section we will see that through App Store Connect and Google Play Console we can control the number of errors: crashes and ANRs that there are in the application daily, by device, operating system, etc. but we will not be able to see the details of said errors. For this reason, it is important that the performance of the product is controlled from a specific tool for this, such as Crashlytics.
Monetization Metrics in App Marketing
This section is probably also the most important for all companies. Although this article includes 8 app monetization metrics, we can discuss many more metrics.
It will depend on whether the application generates business with advertising, with subscriptions or purchases like an ecommerce or other models, even combined or “hybrid”. We should measure monetization metrics with platforms specialized in app and game monetization.
1. ARPU – Average Revenue Per User
ARPU, to put it simply, is the value of the average basket, the average revenue per user. ARPU is calculated by dividing total revenue by the total number of buyers. You need to keep track of 2 ARPU metrics: the one calculated on buyers and the one calculated on total users.
2. Time until the first purchase
We need to know the average time it takes users to make their first purchase and define actions to improve this metric. Here I would like to differentiate between eCommerce shopping apps and those that include in-app purchases, and those that have a subscription business model.
In the latter case, what we are interested in is knowing how long it takes users to start the trial after downloading or registering for the app. On the other hand, for the first group, the time to make the first purchase will depend a lot on the type of product we offer, its value, our brand, and many more factors. What is common to all businesses is having a good strategy defined in prices, discounts, personalized offers, limited offers, etc. This strategy can help reduce the time between downloading/registration and the first purchase.
3. Conversion Rate to Trial
The conversion rate to a trial is calculated by dividing the number of users who start a trial by the total number of downloads of the application. This metric is perhaps one of the most painful when you are not familiar with the wonderful world of subscriptions because the drop can be very heavy: on average only 3.7% of users who download start a trial. For top applications this ratio can reach over 8%.
4. Conversion Rate Trial
The trial to subscriber conversion rate is the percentage calculated by dividing the total number of users who end up subscribing to the app by the number of users who started the trial. In the event that the app does not include a trial, the calculation would be done by dividing the total number of users who subscribe by the total number of downloads.
In this sense, for top apps that offer 1 month of trial we see that 60% of users ended up becoming subscribers, while in smaller apps this percentage is 22%. As a curious fact, we see that for small apps, the % of users who end up being subscribers with 3 days of trial is 19% and for those that offer 1 month of trial it is 22%, so the difference does not seem to be so much in the time offered in the trial, but in other variables.
5. Churn Rate
The Churn Rate is the abandonment rate, the % of users who started a subscription and cancel it in the period we want to analyze. This metric is very important, since it is one of the most important indicators of the health of our business.
For this metric we can take into account two moments of the churn rate: the first moment would be to know how many of the users who start the trial end up cancelling, and the second would be to know how many of the users who end up subscribing renew over time. We are also interested in knowing if the cancellation of the renewal occurs in the first month of subscription, in month 7 or in month 11. This depth of analysis would be worked on with cohort analysis and is essential to understand and improve the profitability of our business.
6. RPM – Revenue Per Thousand Impressions
RPM is the revenue generated per thousand ad impressions shown. For apps and games that are ad-supported or include advertising as a mixed revenue model, keeping track of RPM by channel, OS, country, and other variables is critical. RPMs differ greatly between countries, verticals, and formats, with some pretty crazy differences.
We’ve seen projects with RPMs of €0.30 and others with RPMs of €50. It’s absolutely crazy. For ad-only models, this is the key metric (along with the average number of ad impressions per user), as it will help you know the maximum cost per download (CPI) you need to invest.
7. LTV – Lifetime Value
LTV is the value (amount of income) that users will leave us on average throughout their useful life in our app. It is a very important metric that we must take into account in phases of maturity or a certain journey, but not so much at the beginning of a project. Knowing what the LTV of our business is will help us have a clear objective in terms of the cost of acquisition (CPA).
8. ROAS – Return On Ad Spend
ROAS is the return on our advertising investment. Calculating ROAS is measuring the gross income generated by each euro invested in advertising and is essential to know the profitability of our campaigns. ROAS is calculated by dividing gross income by advertising investment and multiplying by 100 to obtain the data as a percentage. ROI (Return On Investment) usually refers to the profitability of the business, taking into account the net income and total costs of the company.
Retention Metrics in App Marketing
In this section, we will discuss 4 main metrics related to app engagement or retention. We can analyze many more, but these are the 4 that we should keep a close eye on. Retention metrics are measured through analytics tools and these 4 that we will discuss now can also be measured through an MMP such as AppsFlyer or Adjust.
1. Active Users: DAU, WAU, MAU
Active users are those who interact with our application and we can divide them into time intervals: days, weeks and months.
- Daily Active Users (DAU): total number of users who had a session with our app on a given day.
- Weekly Active Users (WAU): Total number of users who had a session with our app in a given week.
- Monthly Active Users (MAU): total number of users who had a session with our app in a given month.
A few years ago, the metric “how many downloads do you have” became a thing of the past, replaced by “how many MAUs do you have?”. Downloads themselves are not worth much, especially when you know that uninstall rates are usually very high or retention rates are low, or very low.
Active users are a metric that any analytics tool provides you with and it is important to analyses their growth as well as their dependence on paid marketing. This is not the first time that we have seen in a project that the growth of MAU per month is very similar to the growth of new users acquired in the month.
2. Stickiness
Stickiness (or “Sticky Ratio”) is a very simple metric to calculate. The formula is to divide the daily active users (DAU) by the monthly active users (MAU). This metric gives us very quick information about retention, since it tells us the average number of days that users interact with our app per month.
Like all metrics, we must put it into context by type of app. What is clear is that the higher this figure, the better. Improving this ratio can undoubtedly help us increase our income. In general, the more recurrence users have with our app, the more likely we are to “convert to business.”
3. Retention
Retention is one of the most important app marketing metrics in apps that also reveals the health of our business. A phrase that I have also repeated a lot over the years is: “the challenge is not in attracting users, the challenge is in retaining them.” Having a budget to attract users can be done by many, having good retention data is achieved by few.
Retention is calculated based on the average % of users who return to your app over time. Retention can be calculated using various criteria and will depend on the model of our app to determine which ones are of most interest to us. For example, we can analyze retention on Day 1, Day 7, Day 30, Month 1, Month 2, and Month 3. We can also analyze retention over specific periods, retention by time intervals, or retention on a specific day outside of the standard ones.
We can obtain retention through app analytics tools, but also through MMPs such as AppsFlyer, which allow us to perform retention analysis differentiating between organic and non-organic traffic, by country, by each of the acquisition sources, by campaigns, etc.
4. Cohort analysis
Cohort analysis can be performed for both behavioral and retention analysis. Cohort analysis allows us to group user types by whatever we want: users by acquisition traffic source, users by country, purchasing users, etc. and analyze their behavior pattern on whatever we want to analyze over a period of time.
ASO Metrics in App Marketing
We finish with the last section of app marketing metrics, which is not the least important. Having control over ASO metrics is essential for every project. We must remember that ASO is not a 1-shot that we should work on at the beginning of the project and forget about, far from it. App stores change and the ASO actions that we can and should work on also change.
A phrase that I have repeated a thousand times, without exaggeration, is that we must understand ASO as a process, where the search part is only one part. ASO metrics are measured through the Apple and Google developer consoles and also with specialized ASO tools.
1. Traffic: Impressions, Visits and Downloads
When we talk about traffic, we are referring to these 3 metrics: impressions, visits, and downloads. Impressions are the number of times that the result of my app appears in the app stores. Even though we include impressions in the traffic section, if we don’t get a visit or a download, we won’t have much traffic. Visits refer to the number of users who visit our app’s page to get all the information and access the download. Downloads are the users who end up downloading our application.
As I will discuss in the next conversion metric, it is not necessary for users to go to the app listing from a search result to download the app. However, for all users who arrive from a campaign or action, it is necessary. These 3 data come from the developer consoles and we can obtain them by traffic source (search, browsing and others), as well as by country and device.
2. Conversion Rate to Download
The download conversion rate (CR or CVR) is calculated by dividing the downloads achieved by the users who have visited our application’s listing. We obtain this data through the developer consoles, which provide us with CR data by country and traffic source.
It is worth noting that in Apple’s console, App Store Connect, the CR can be higher than 100% because there are users who download the app from the search results without going through the listing. However, in Google’s console, Google Play Console, we can calculate the CR on users who have previously visited the app’s listing and CR on the total. In addition, Google shows CR references from other apps in the same category and country, which is very interesting for comparing ourselves with other apps.
3. Uninstallations
Through the developer consoles (App Store Connect and Google Play Console) we can find out the number of uninstallations we have by country. In my opinion, this is a metric that should be monitored, but we shouldn’t go crazy with it. It’s better not to worry about the number of uninstallations and focus on how to have a better product so that users don’t leave, or don’t leave too quickly. To put your mind at ease, depending on the type of app we have and the number of years we’ve been on the market, having high uninstallation ratios is the most common. We’ve seen apps with millions of new downloads every month and even more millions of uninstallations…
It is worth mentioning that, although this is a metric that we control from the ASO teams, it is not a metric that we can influence with ASO actions. The fact that a user uninstalls an app depends largely on the quality of the traffic (paid performance team) and the product (and the product team, of course).
4. Keyword Rankings
Keyword positions should be monitored with specialized ASO tools, such as App Radar or AppTweak, among others. It is important to have well-defined keywords that we are going to work on in our listing and to have them monitored. We can also spy on the competition and find out which apps are positioned best for the keywords we have established.
5. Visibility in Navigation (Browse)
When we talk about visibility in navigation, we are referring primarily to positions in Top Charts, Featured (Features) and Similar/Related Apps. As we know, each application/game has at least one category and in each country, we have lists of rankings for each category and for each app store. Although the positions in Top Charts were a very relevant metric years ago, today it is becoming less and less important due to how app stores are organized.
Users do not browse so much by rankings but rather by featured content, trends, similar content or personalized content offered to them. In this sense, and through specific tools, we can monitor highlights in stores and similar applications that positively affect browsing traffic.
6. Average rating, ratings and comments
The average rating, reviews and comments of an app say a lot about an app and affect everything (including business) much more than it may seem. We have worked on a marketing plan, on a good execution of campaigns, on having all the business metrics under control, etc. but if our users do not rate us well in their great majority, we will have a problem that affects beyond the image we have in the stores. It affects costs and the business.
In this regard, I would like to give 3 recommendations:
- Have an average rating above 4.1* and if it is a financial or transactional app, better above 4.4*. Trust in these apps is key.
- Having a volume of reviews in line with the number of downloads we have, knowing that the vast majority of users do not rate. To do this we must establish a strategy to request the review from the right users at the right time.
- Keeping track of the comments received, giving personalized responses to users, solving problems, listening to what they tell us and, above all, making sure that negative comments do not sneak into the visible part of the product sheet. This also affects the conversion to download.
7. Errors/crashes, ANRs, Blockages
From the developer consoles we can (and should) know the number of errors and crashes that our application is suffering, but not the details. As we have seen previously in the metric on crashes, this should be a metric that is controlled from the point of view of use and for the product and development teams.
It should be noted that this metric affects the visibility of the apps in the application stores and that, therefore, it should be controlled by the marketing team. The developer consoles offer us certain valuable data such as errors by version to know if after an update this data is good or not.
Conclusions
As you can see, this article on mobile app marketing metrics has covered a lot and we could go into much more depth. There is no single tool for everything, sorry but no, so we must spend time analyzing, comparing and having at least these metrics covered in these 5 areas: acquisition, use, business, retention and ASO.