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The Most Important Test Automation Metrics To Accelerate and Improve Outcomes

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Team Copado
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Test automation metrics are what let you quantify the results of your program. However, a lot of people have trouble creating them because they have no idea how to define value in the testing process. Of course, there are big picture questions, like does this speed our release cycles or save us money? But if you want to see how automation affects your organization, your testing metrics have to capture value at more granular levels. 


When costs go down or release cycles shorten, there can be many contributing reasons—and not all of them will be repeatable. Maybe your server costs dropped or your coders were working on a system addition they felt comfortable with. To get an accurate idea of how test automation affects your bottom line, you have to look at all the little components that come together to speed releases.

Big Picture Questions to Answer

Before you consider the kinds of methods to evaluate in your test automation, you have to take a look at the bigger picture. Specifically, it would help if you outlined the kinds of questions you're trying to answer regarding: 

  • How quickly can we go to market? Accelerating releases is a fundamental goal, especially in the face of digital transformation. Comparing pre-automation release cycles with current ones can give you an idea of how automation affects timelines. 
  • Are we improving software quality? Quality is subjective. Something an engineer or developer sees as brilliant may not be as enthusiastically accepted by end-users. To get the users’ perspective, you’ll have to solicit bug reports, surveys, and other feedback.
  • What are our automation costs and how do they evolve? It's expected that costs will increase during the initial automation project. The payoff is that long-term costs should drop. 
  • What is the automation value for this project? A key part of automation is being able to compare the expense of the automation project compared to the savings it creates. After all, if automation isn't providing ROI, what's its purpose? 
  • How do we use automation to manage skill demand? Can you complete software updates with junior coders or are more experienced staff members required? Understanding the roles a project requires helps organizations create a workflow where expensive experts work on difficult problems while automation handles simple, repeatable tasks. 

Assigning a numerical value to each of these means you can connect them to the smaller metrics that make them possible. You won't just have the results. You'll understand the specific path you took to get there. 

Must-Have Test Automation Metrics

Once you understand your big-picture goals, you can use test automation metrics to track your progress toward them. Six that you should consider reviewing regularly are:


Automatable test opportunities

Testing time

Pass rates

Automatable opportunities measure how many of your tests could be automated. This metric tells you if automating the program is worth further investment. The more tests you have eligible for automation, the larger the effect automation will have on big-picture goals.

This metric accounts for the total run time of tests. The goal of adoption is to accelerate the testing process. If automated tests take too long to run, they require review. This number can also be compared directly to the release cycle to see the impact testing automation has on timelines.

The overall pass rate of the automation test is a key indicator of stability. If pass rates are low, the program may be ineffective and require review. Failures will require validation. If they can't be validated, then the issue is with the test automation itself.

Script failures

Defects found

Defect distribution

Your script is essential when you're running automation. After all, if it's ineffective, the test won't work. A high number of script failures means that it's likely your team needs some remedial training on creating appropriate programs for software testing.

Defects found must be monitored to ensure they're resolved before release. This metric should also include open and close rates, which compare the total defects found before and after the software ships.

Defects are rarely evenly distributed throughout your whole development lifecycle. Defect distribution tells you where most of the errors are occurring so you can fix the most damaging problems first. It also lets you measure how effectively your software test automation resolves high-impact issues.


These smaller-scale test automation metrics will directly impact your big-picture goals. For example, reducing testing time can jumpstart your speed to market. Smaller metrics give you insights into the low-level issues you can fix to maximize your automation project's ROI.


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