What Are Game Metrics and Do They Matter? (With Examples)

Updated June 24, 2022

Tracking key performance metrics of a game can be one of the best ways of understanding an average user's experience. Game metrics are one example of these performance indexes that allow developers to analyze how players are interacting with their game. By understanding what data game metrics provide, you can develop a deeper knowledge of how players experience a game. In this article, we discuss what game metrics are, why they're important, examples of commonly used game metrics as well as techniques for measuring them.

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What are game metrics?

Game metrics is a term that refers to raw telemetry data that a database stores and converts into values that allow developers to measure their game's performance. Game metrics provide insight into user engagement, spending patterns and satisfaction. By using game metrics, game developers are able to learn about what users are enjoying with their game as well as what they are struggling with. This information can be used to influence changes in a game's content as well as monetization strategies.

Why are game metrics important?

Game metrics are important because they provide quantitative feedback to developers on how they can improve their game. The data that game metrics provide gives invaluable insight into what type of content is engaging users most and driving profits. Understanding how users are interacting with the various systems within a game allows developers to create content that keeps users logging in and spending money. Without game metrics, developers might struggle to analyze how their game is performing in key demographics.

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15 Examples of game metrics

Game metrics provide analytical insight into a variety of topics, from user engagement to spending habits. Here are 15 of the most commonly used game metrics:

1. Daily active users

Daily active users is a metric that tracks how many individual people log into a game each day. By tracking daily active users, companies can quantify the success of content releases as well as game patches. For example, when daily active users increase dramatically after introducing a balancing update, developers might conclude that many users are reacting positively to the update. Understanding what changes to a game increase the daily active user count can be an effective way of tracking what players want to see in a game.

2. Session length

Session length is a measure of how long a user stays in the game before logging out. Session length can be a useful metric to use when analyzing how users engage with different areas of content. If a user was playing a challenging mode in the game and had a short session length, developers might draw an inference that the content was too hard and was causing frustration. Conversely, if a user is staying logged in for a long time on a difficult piece of content, it could mean that the content is challenging but not frustrating.

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3. Installs

Installs is a metric that represents how many times users install a game over a certain time period. Game designers might track installs over a period of a few months or days, depending on what sort of insight they are trying to gain. For example, if an update release and installs drastically increase over a period of a few days, it may be reasonable to conclude that the update is driving the increase in installs. However, if there is an increase in installs without an update, it may be a result of some publicity that the developers were unaware of.

4. First payment conversion

First payment conversion tracks how long it takes an average user to spend money after installing a game. This metric is particularly useful for games that are free to download but offer in-game purchases. Tracking how long it takes a user to start using the in-game shop can be beneficial when designing paid content.

5. Retention rate

The retention rate of a game refers to how long users continue to play after first installing. Tracking retention rate can be helpful when developers are trying to understand what keeps users playing. If users who are engaging with one type of content are playing longer than users who are engaging with a different type, it could be reasonable to conclude that the first type of content leads to a higher retention rate. This information can be beneficial when designing future updates.

6. Customer satisfaction score

Customer satisfaction score is a way to quantify player satisfaction. Developers can derive customer satisfaction scores analytically from other game metrics, or from direct feedback from players. If users are playing frequently and spending money in the in-game shop, developers might conclude that the game is satisfying and use that information to create a customer satisfaction score. Other games might offer the players an opportunity to leave reviews or rank their satisfaction numerically.

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7. Average revenue per user

The average revenue per user is a metric that tracks the revenue an average user generates for the game company. This metric takes a variety of information into account, such as how many ads a user sees while playing and how much money they spend on the game. Games that are free to play but have in-game advertisements or paid content use this metric. Tracking how many ads an average user clicks on is one of the most common data points used when calculating average revenue per user.

8. Monthly active users

Monthly active users is a measure of how many players log in consistently over the course of a month. Developers analyze this metric alongside daily active users to track retention rates. If players log in for a few days but then stop, it can mean that the content wasn't engaging enough. Conversely, if the average user is logging in almost every day, it can indicate that the game's content is effective in engaging players.

9. Churn rate

The churn rate tracks how many users uninstall a game after they play it. This metric is the opposite of retention, as it tracks players who stop playing. Churn rate metrics typically include a measure of how long a user engages with the game before uninstalling. If users are downloading a game and uninstalling it within a few hours, it can be a sign that a game needs a tutorial or similar system to help users learn how to play. If players are uninstalling a game after a few weeks, it can mean the content becomes repetitive after a while.

10. Concurrent users

Concurrent users measures how many users log into a game at the current time. Measuring concurrent users can provide insight that goes beyond daily user count. If the number of concurrent users is increasing dramatically during one time of the day, it can mean that many users are playing in a specific time zone. Understanding the demographics of a game's player base can provide insight into what marketing tools are effective and what types of content developers should release.

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11. Total playtime

Total playtime is the measure of how many total hours a player spends in a game over a period of time, divided by the number of users. Calculating total playtime provides an average of how long a typical user spends in the game. A developer's analytical software tools may also track total playtime. When looking at individual playtimes, developers can see what players are spending a long amount of time logged in and what players are logging out quickly.

Tracking the types of content that players spend the most time playing can provide inspiration to design future updates that maximize playtime.

12. User acquisition cost

User acquisition cost is the amount of money that a company spends per active user it gains. You can measure this by calculating the marketing budget divided by how many new users a game gains. Tracking user acquisition costs allows companies to measure the effectiveness of their promotional efforts. It can also provide direct feedback on the success of different marketing strategies, such as advertising in other games or working with content creators.

13. Customer lifetime value

This metric tracks how much revenue is an average user generates from the time they download the game to the time they uninstall it. Customer lifetime value is an important metric for developers to track, as it can help them understand how to convert users into profits. In free-to-play games, customer lifetime value comes in two categories, paying players and free-to-play players. The lifetime value of a free-to-play player usually comes from ad revenue, whereas the lifetime value of paying players comes from the in-game shop or paid content.

14. Average transaction value

Games that offer in-game purchases track average transactional value as a metric to show much money people spend on average with each transaction. Understanding how much money the average user spends with each transaction can provide developers with insight into how much people are willing to spend on their game. This metric helps create offers for the in-game shop.

15. Start, fail and complete

Start, fail and complete is a term that refers to three metrics that track how users engage with content. This set of data represents how many users start playing a piece of content, how many cannot complete it and give up, and how many successfully complete it. This metric is typically used to measure how difficult a piece of content is. If many users are engaging with a part of a game but ultimately give up before completing it, that can mean that it's too hard and causing frustration.

Ways to measure game metrics

There are many ways to measure game metrics, either with direct feedback from players or through analytically scrutinizing data. Many game companies have community forums where players are able to discuss the game amongst themselves or join conversations with the game developers. Users who are passionate about a game are often more likely to provide feedback to developers about what they're enjoying in a game. Direct feedback from players can be a great way to gain qualitative insight that isn't always apparent from looking at raw data.

In addition to player feedback, most companies have a system of looking at quantitative data. Data warehouses are a common tool used by game companies. These systems store data and categorize it into groups that represent things like engagement, spending and retention. Developers and data analysts use data warehouses and other computer systems for tracking information about in-game interactions that developers might not be able to clearly observe, such as player communication and conflicts.


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