What Are the Top 7 KPIs Metrics of a Video Game Testing Service Business?

As the video game industry continues to expand and evolve, the demand for high-quality testing services has never been higher. However, ensuring the effectiveness and efficiency of these services can be a challenge for both service providers and clients. That's where Key Performance Indicators (KPIs) come into play. In the context of artisan marketplaces, understanding industry-specific KPIs is crucial for evaluating the success and impact of video game testing services. In this blog post, we will explore the seven most important KPIs for video game testing services, offering valuable insights for small business owners and artisans looking to optimize their marketplace performance and drive success in the gaming industry.

Bug Detection Rate

Definition

The Bug Detection Rate KPI is a ratio that measures the effectiveness of identifying and addressing bugs or defects during the video game testing process. This KPI is critical to measure as it provides insights into the thoroughness of the testing services provided by ElitePlay TestWorks. In the business context, the Bug Detection Rate directly impacts the quality of the games being tested. A high Bug Detection Rate indicates that the testing process is able to identify and resolve a significant portion of bugs, leading to a higher-quality and more polished end product. On the other hand, a low Bug Detection Rate indicates that there may be a higher chance of bugs slipping through the testing process, potentially leading to negative user experiences and poor game performance. Ultimately, this KPI matters as it directly impacts the reputation of the game developers and their ability to compete in the gaming market.

How To Calculate

The Bug Detection Rate KPI can be calculated by dividing the total number of bugs detected during the testing process by the total number of bugs present in the game. The resulting ratio provides insights into the effectiveness of bug detection.

Example

For example, if a game has a total of 100 bugs and the testing process successfully detects and addresses 85 of them, the Bug Detection Rate would be calculated as (85/100) * 100, resulting in a Bug Detection Rate of 85%.

Benefits and Limitations

The advantage of measuring Bug Detection Rate is that it provides a clear indication of the testing process's effectiveness in identifying and addressing bugs. However, a limitation of this KPI is that it may not account for the severity of the bugs detected, as certain critical bugs may have a greater impact on the game's performance and user experience.

Industry Benchmarks

According to industry benchmarks, an above-average Bug Detection Rate for video game testing services falls within the range of 80% to 90%. Exceptional performance would be considered a Bug Detection Rate of 90% or higher, demonstrating a rigorous and thorough testing process.

Tips and Tricks

• Implement comprehensive test cases to cover all aspects of the game, including gameplay mechanics, graphics, audio, and technical performance.
• Utilize automated testing tools to efficiently identify and address bugs throughout the development and testing phases.
• Regularly review and update testing protocols based on industry best practices and feedback from testing teams.

Test Case Coverage

Definition

Test case coverage is a key performance indicator (KPI) that measures the percentage of test cases executed during the testing process. It is critical to measure because it provides insight into the thoroughness of the testing process and the extent of testing performed. In the business context, test case coverage KPI is essential in ensuring that all critical components of the game are tested, reducing the risk of releasing a faulty product. It impacts business performance by enhancing the overall quality of the game, leading to higher user satisfaction, positive reviews, and increased sales. Therefore, measuring test case coverage is crucial to identify potential areas of improvement in the testing process and ensure that all aspects of the game are thoroughly examined.

How To Calculate

The formula for calculating test case coverage is the number of test cases executed divided by the total number of test cases. The number of test cases executed refers to the actual tests performed during the testing process, while the total number of test cases represents the complete set of test scenarios outlined for the game. By dividing the number of test cases executed by the total number of test cases, businesses can determine the percentage of test case coverage achieved.

Example

For example, if a video game has 100 test cases identified for testing, and 80 of those test cases are executed, the test case coverage can be calculated as follows: Test Case Coverage = (80 / 100) x 100 = 80%. This means that 80% of the test cases have been executed, indicating the extent to which the game has been tested.

Benefits and Limitations

The primary benefit of measuring test case coverage is that it provides visibility into the thoroughness of the testing process, ensuring that critical aspects of the game are thoroughly examined. However, a limitation of this KPI is that it does not necessarily guarantee the detection of all potential issues, as some defects may still go undetected despite comprehensive test case coverage.

Industry Benchmarks

According to industry benchmarks, typical test case coverage for video game testing services falls within the range of 75-85%, reflecting a comprehensive testing approach. Above-average performance levels for test case coverage may exceed 90%, indicating a more thorough and exhaustive testing process. Exceptional performance levels may achieve test case coverage of 95% or higher, demonstrating a meticulous and comprehensive testing effort.

Tips and Tricks

• Utilize test case management tools to organize and track test cases effectively.
• Regularly review and update test case scenarios to align with evolving game features and requirements.
• Implement regression testing to ensure previous test cases remain valid after game updates or modifications.
• Leverage automation testing to increase the efficiency and coverage of test cases.

User Satisfaction Score

Definition

User Satisfaction Score (USS) is a key performance indicator that measures the overall satisfaction level of the end users with the video game. This KPI is crucial for a video game testing service as it reflects the success of the testing in ensuring that the game meets the expectations and preferences of the target audience. The USS provides valuable insights into the user experience, identify areas for improvement, and helps in understanding how the game will be received in the market. For a video game testing service, monitoring the USS is imperative for delivering high-quality games that meet user expectations and drive business success.

How To Calculate

The User Satisfaction Score can be calculated by taking the average of user feedback and ratings received during testing. This includes feedback on gameplay experience, graphics, audio, controls, and overall enjoyment of the game. The scores obtained from user surveys, beta testing, and focus groups are typically used to calculate the USS. By averaging these scores, a comprehensive understanding of user satisfaction can be derived.

Example

For example, if a video game testing service collects feedback from 100 users during testing, and the sum of their satisfaction scores amounts to 850, the User Satisfaction Score would be calculated as follows: USS = 850 / 100 = 8.5. This indicates that, on average, the users have rated the game with a satisfaction score of 8.5 out of 10.

Benefits and Limitations

Measuring and monitoring the User Satisfaction Score allows the video game testing service to understand how well the game resonates with the target audience. A high USS indicates that the game is meeting user expectations, leading to better user retention, positive reviews, and increased sales. However, it's important to note that the USS only provides a general understanding of user satisfaction and may not capture the specific areas that need improvement in the game.

Industry Benchmarks

In the US gaming industry, the typical benchmark for User Satisfaction Score is around 8.0, indicating a high level of satisfaction among users. An above-average performance level would be a USS of 8.5, while an exceptional performance level would be a USS of 9.0 or above.

Tips and Tricks

• Regularly collect user feedback throughout the game testing process to ensure a representative sample of opinions.
• Utilize analytics tools to gain deeper insights into specific areas of the game that impact user satisfaction.
• Implement user feedback into iterative game testing to continuously improve the user experience.
• Compare the USS with industry benchmarks to gauge the game's performance against competitors.

Time to First Bug Report

Definition

Time to First Bug Report is a key performance indicator (KPI) that measures the speed at which bugs or issues are identified and reported during the video game testing process. This ratio is critical to measure as it provides insights into the efficiency and accuracy of the testing service. In the business context, a quick and early identification of bugs is crucial for developers to address issues promptly, improve game quality, and ensure a smooth user experience. The KPI is important to measure as it directly impacts the overall quality of the game and customer satisfaction. The more efficiently bugs are identified and reported, the better the business performance will be in terms of customer retention, positive reviews, and game sales.

How To Calculate

The formula for calculating Time to First Bug Report KPI is the time elapsed between the start of the testing process and the submission of the first bug report. This time is then compared against the set standards or industry benchmarks to evaluate the efficiency of bug identification and reporting. The faster the bugs are reported, the lower the time to first bug report is, indicating a more efficient testing process.

Example

For example, if the testing process for a game started on January 1st, and the first bug report was submitted on January 5th, the Time to First Bug Report would be 5 days. This indicates that it took 5 days from the start of testing to identify and report the first bug in the game.

Benefits and Limitations

The benefit of measuring the Time to First Bug Report KPI is that it enables developers to identify and address issues promptly, leading to improved game quality and customer satisfaction. However, a potential limitation is that a very low time to first bug report may also indicate a lack of thorough testing, potentially leading to overlooked issues.

Industry Benchmarks

According to industry benchmarks, the typical Time to First Bug Report for video game testing services in the US is around 7-10 days. Above-average performance would be considered 5-7 days, while exceptional performance would be less than 5 days.

Tips and Tricks

• Implement automated testing tools to quickly identify and report bugs.
• Encourage testers to thoroughly explore the game to uncover potential issues early on.
• Establish clear and efficient bug reporting processes to streamline the submission of bug reports.

Defect Removal Efficiency

Definition

Defect Removal Efficiency (DRE) is a key performance indicator that measures the effectiveness of the testing process in identifying and eliminating defects in a video game. It is critical to measure DRE as it provides important insights into the overall quality of the game and the efficiency of the testing service. High DRE indicates a robust testing process, resulting in fewer defects slipping through to the final release, which can significantly impact the overall user experience and the reputation of the game.

How To Calculate

The formula for calculating DRE is: (Total defects found before release / (Total defects found before release + Total defects found after release)) x 100.

Example

For example, if a video game testing service identifies a total of 100 defects before the game's release and 10 defects are found after the release, the DRE would be calculated as: (100 / (100 + 10)) x 100 = 90%. This means that 90% of the defects were removed before the game was released to the market.

Benefits and Limitations

The benefits of measuring DRE include the ability to assess the effectiveness of the testing process, identify areas for improvement, and ensure a higher quality product for the end consumer. However, one limitation of DRE is that it only measures the quantity of defects found, not necessarily the severity or impact of those defects on the user experience.

Industry Benchmarks

According to industry benchmarks, the average DRE for video game testing services in the US typically ranges from 80% to 90%, with exceptional performance levels reaching above 95%.

Tips and Tricks

• Implement comprehensive and rigorous testing procedures to catch defects early in the development process.
• Continuously monitor and track the DRE to identify patterns and trends in defect removal.
• Invest in training and development of testers to improve their ability to identify and resolve defects effectively.

Average Time to Fix

Definition

The Average Time to Fix KPI measures the average amount of time it takes for the testing team to identify and resolve bugs and issues in a video game. This ratio is critical to measure because it provides insights into the efficiency of the testing process and the ability of the team to address issues promptly. In the business context, this KPI is crucial as it directly impacts the quality of the game and the overall user experience. It also reflects the testing team's effectiveness in ensuring a bug-free gaming experience, which is essential for positive reviews, player retention, and ultimately, the success of the game in the market.

How To Calculate

The formula for calculating the Average Time to Fix KPI is the total time spent on fixing bugs divided by the number of bugs fixed. This provides an average time it takes to resolve individual issues, giving valuable insight into the efficiency of the testing process. The total time spent on fixing bugs includes the time of identifying the issue, investigating the cause, implementing a fix, and verifying its resolution. By dividing this total time by the number of bugs fixed, the KPI offers a clear picture of the average time to address and resolve issues.

Example

For example, if a testing team spends a total of 100 hours fixing 50 bugs, the Average Time to Fix KPI would be calculated as follows: Average Time to Fix = 100 hours / 50 bugs = 2 hours per bug. This means that, on average, it takes the team 2 hours to identify, troubleshoot, and resolve individual bugs in the game.

Benefits and Limitations

The advantages of measuring the Average Time to Fix KPI include the ability to identify efficiency bottlenecks in the testing process, enabling teams to streamline their bug-fixing workflows and improve overall productivity. However, it's important to note that this KPI may not account for the complexity of individual bugs and could overlook the quality of the fixes. Some issues may inherently take longer to address, and the KPI alone may not provide a full picture of the testing team's performance.

Industry Benchmarks

According to industry benchmarks, the average time to fix bugs in the video game testing industry is around 2-3 hours per bug for small to medium-sized studios and independent developers. However, exceptional performance levels can achieve an average time to fix of 1 hour per bug or less, demonstrating highly efficient and effective testing processes.

Tips and Tricks

• Implement automated testing tools to identify and resolve bugs more efficiently.
• Encourage effective communication and collaboration within the testing team to expedite bug-fixing workflows.
• Analyze common types of bugs to develop proactive strategies for prevention rather than just reaction.

Post-Release Defect Discovery Rate

Definition

The Post-Release Defect Discovery Rate KPI measures the percentage of defects or bugs discovered after a video game has been released to the market. This ratio is critical to measure as it provides valuable insights into the effectiveness of the video game testing service. A high post-release defect discovery rate indicates that the testing process was not thorough enough, leading to a higher number of issues being discovered by users after the game's release. In the business context, this KPI is crucial as it directly impacts the reputation of the game developer and the success of the game in the market.

How To Calculate

The formula to calculate the Post-Release Defect Discovery Rate is the number of defects discovered after release divided by the total number of defects discovered. Each component of the formula represents the number of defects identified after the game has been launched and the overall number of defects found during testing and after release, respectively. The resulting percentage provides a clear indication of the ratio of post-release defects to total defects, reflecting the effectiveness of the testing process.

Example

For example, if a game initially had 100 defects identified during testing, and after release, an additional 20 defects were discovered by users, the Post-Release Defect Discovery Rate would be calculated as (20 / 120) x 100 = 16.67%. This demonstrates that 16.67% of the identified defects were discovered after the game's release, indicating the effectiveness of the testing process.

Benefits and Limitations

The advantage of measuring the Post-Release Defect Discovery Rate is that it provides critical insights into the quality of the testing process and the potential impact on the game's reputation and success. However, a limitation is that this KPI does not measure the severity of the defects discovered post-release, which could vary in impact on the user experience.

Industry Benchmarks

Based on industry benchmarks within the US context, the typical Post-Release Defect Discovery Rate for video games ranges from 10% to 15%, indicating that an effective testing service should aim to keep post-release defects within this range. Above-average performance would be in the range of 5% to 10%, while exceptional performance would be under 5% post-release defect discovery rate.

Tips and Tricks

• Implement comprehensive testing strategies to identify and address potential defects before the game's release.
• Collect and analyze user feedback post-release to continually improve the game and reduce the post-release defect discovery rate.
• Engage professional testers with a deep understanding of the gaming community to ensure thorough testing and minimize post-release defects.