According to GitLab’s 2024 DevSecOps Survey, 38% of startup downtime incidents could have been more easily prevented by automated tests. The same survey also lists increased automation as the top priority for increasing developer satisfaction and among the most important investment factors for new IT organisations.

The conclusions are clear: software QA automation is no longer just a nice way to increase efficiency – for startups, it’s practically a matter of survival.

To be clear, not every startup is ready for automation, and automation is not a catch-all solution to all your QA needs. However, the modern IT market practically requires startups to move fast and grow even faster. If you’re not careful and don’t set up proper QA frameworks on time, the cost of cutting corners can become staggering in terms of both lost revenue and customer trust.

As a QA tool, automation can be a great way to future-proof projects for scale and streamline production. Better yet, it can increase stability and reliability even if your organization is facing hurdles that are common with startups, such as limited resources and ambitious goals.

In this article, we’ll take a look at how automated testing can benefit startups by providing the stability, efficiency, and speed that are so critical for recently funded projects. We’ll also explain how to properly automate tests into your startup’s QA pipeline, highlighting the cost benefits of doing so.

Why Stability Is Mission-Critical for Startups

Stability is crucial for startups because it’s a direct indication of their ability to secure funding, grow, adapt to changes, and ultimately deliver a quality product. This is especially true for projects that aim for innovation or lofty business goals.

Let’s be frank here – startups face a high risk of failure, and earning the trust of investors, customers, and developers is not easy. That’s why a stable foundation can benefit your project in multiple ways:

  • Reduced customer churn – Every missed bug or slow fix can have devastating consequences for your customer base, which directly affects revenue.
  • Investor confidence – Startups need funding to survive and grow, and investors are more likely to trust companies with a reliable track record. The ability to release quickly while maintaining quality reassures their investments.
  • Talent acquisition – Similarly, developers prefer to work in companies with reliable frameworks and stable environments. As such, stability reduces staff turnover and helps you acquire top talent.
  • Operational efficiency – A stable foundation allows teams to more easily execute tasks, allocate resources, and solve problems on the fly. This is especially important during the early stages of development when optimization is key.
  • Reduced costs – Fixing bugs and issues becomes significantly more expensive post-release. As such, investing in your ability to catch them early is a great way to prevent potential bottlenecks and money sinks.

How Automated Testing Drives Stability

So, stability is important for your startup, which probably isn’t a surprise for anyone working in the IT industry.

But how can test automation increase stability, and why is automation so useful for startups in particular?

Let’s consider some of the main factors:

  1. Earlier Defect Detection
  2. Consistent Release Gates
  3. Faster MTTR (Mean Time to Repair)
  4. Metrics & Feedback Loops

  1. Earlier Defect Detection

Automated tests can be integrated into the CI/CD pipeline, enabling continuous testing and early detection of defects.

Additionally, methods like shift-left automation aim to integrate QA tests as early into the development cycle as possible. This approach allows you to address potential issues and defects before they have a chance to grow into real QA concerns.

Unit and API testing are also often automated as a way to streamline development. Automating such tests is generally more feasible than, say, UI testing, and it can reduce maintenance costs and increase the speed of your development cycle. That’s why more than 54% of API testing these days features some level of automation.

  1. Consistent Release Gates

Release gates act as checkpoints within a development pipeline that ensure code meets pre-defined criteria. As you can imagine, the goal is to prevent issues from “slipping through the cracks.”

Automating these checks can massively improve the efficiency of the entire process by removing the need for manual code checks. Moreover, automating the process ensures consistency and reliability.

Your QA pipeline can be further improved through methods like zero-touch automation. “Zero touch” simply means that repetitive tasks like regression tests can be performed with no human interaction. As you can imagine, this can be highly beneficial for startups with limited headcounts and resources.

  1. Faster MTTR (Mean Time to Repair)

Early bug prevention is not the only benefit of automation. If properly implemented, it can also reduce the time it takes your system or product to recover from failure or outage.

In short, automated checks and gates help developers verify bug fixes immediately. This is most often achieved using Smoke Suites – automated tests designed to verify hotfixes and allow you to immediately launch them without additional issues or unintended consequences.

By automating the verification process, QA automation eliminates the need for manual testing, which can be time-consuming and prone to errors. This, in turn, reduces downtime and prevents revenue loss.

According to IBM, the average cost of unplanned downtime can reach up to $9,000 per minute. The faster you can resolve issues, the less your bottom line will suffer, which is essential for young startups.

  1. Metrics & Feedback Loops

Additionally, automation can help improve stability by providing feedback and allowing your team to proactively address potential issues.

For example, Flaky Test Dashboards are a handy tool that detects and identifies tests with inconsistent results. They track the frequency of flaky tests and their impact on the software and its various builds. They can also help you understand any trends and the underlying issues behind the flakiness.

Another example would be defect trend alerts. These tools provide insight into any patterns and trends with defects within the software, using data to alert your team to potential issues in the code or the development pipeline.

Selecting the Right Automation Stack on a Startup Budget

Implementing automation into your QA stack has clear benefits in both the long and short terms. However, tooling costs are often cited as one of the major downsides of automation. We should also keep in mind that budgeting is a major concern for pretty much every startup out there.

If cost-effectiveness is critical for your organization, there are multiple ways to address the issue of QA automation.

  • Open-source resources (Selenium, Playwright, Cypress) can offer a lot of benefits at minimal cost. However, you should keep in mind that these tools offer varying perks and features and often require experienced testers to properly utilize them.
  • Low-cost cloud runners (GitHub Actions, CircleCI) can be the perfect solution for teams operating on a budget because they balance comprehensive testing with low maintenance costs. They can also offer startup credits and scalable infrastructure that adapts to your needs as they change and evolve.
  • Self-hosted runners are probably not the first thing that comes to mind when you say “budget-friendly.” However, if properly implemented, a custom automation platform can be a cost-effective solution in the right circumstances.

We should stress that there is no such thing as one-size-fits-all when it comes to software QA automation.

Selecting the right stack comes down to properly defining your needs, requirements, and priorities. You should be careful not to over-engineer the pipeline and be prepared to adapt your stack as your needs evolve.

KPIs to Track Stability Gains

The benefits of QA automation can be easily identified and tracked using several important metrics. In fact, these metrics should be tracked because they allow you to further improve your stack and adapt it based on evolving requirements.

There are several Key Performance Indicators (KPIs) that can be used to monitor the stability of your product and/or development cycle:

  • Escaped Defect Rate (DER) – The proportion of defects found by end-users compared to the total number of defects identified throughout the development cycle. A low DER rate indicates an effective testing process. Broadly speaking, the goal of QA automation is to increase the speed of production without decreasing DER, which is why this metric is so important.
  • Deployment Frequency - Keeps track of how often code changes are deployed to a production environment. It is often used as an indicator of how efficiently new features, bug fixes, and updates are delivered. As you might have guessed, automation aims to increase deployment frequency without adversely affecting product quality.
  • Change Failure Rate (CFR) – Tracks the percentage of code changes that lead to failures, bugs, errors, or the need for rollbacks and fixes. This metric essentially compares the number of failed changes to the number of total changes, indicating the stability of the entire delivery pipeline. Most teams aim for a CFR rate below 15%, but the exact goals vary from case to case.
  • Mean Time to Repair (MTTR) – Measures the average time it takes to fix a bug or resolve a QA incident. It’s one of the most important metrics when it comes to stability, as it serves as a strong indication of how quickly a team is able to identify and address an issue. MTTR directly impacts downtime and minimizes disruption, which reduces expenses and builds customer trust.

Importantly, you should take care to set proper baselines before tracking any of these metrics. This means that you should calculate these KPIs before implementing automation. This will allow you to easily track the effect of automation on your QA pipeline, offering valuable insight into ROI and overall efficiency.

Case Study Sidebar

If you’re looking for a more concrete example of the effects of automation on QA efficiency, look no further than one of our TechTailors case studies.

Specifically, this story relates to a US-based client who was looking to improve the testing phase and accelerate their release schedule. We approached the task by introducing automated testing with increased regression coverage. We also added a TMT (test management tool) to improve organization and upkeep of all relevant test cases.

Within one year of implementation, the total number of regression bugs found post-release was less than half of what it was before automation. Conversely, the number of bugs fixed pre-release skyrocketed more than five times what it was.

According to industry studies, the cost of fixing bugs increases 30 to 100 times after release. As such, the simple bit of automation in our case study decreases the overall cost of regression bug-fixing by a factor of up to 750. That’s a lot of bang for your buck – and all it took was a bit of strategic automation.

You can read more about the case study here, complete with important metrics and graphs that showcase a clear, rapid improvement in QA efficiency and build stability.

Common Pitfalls & How to Avoid Them

This article largely outlines the advantages and perks of testing automation on software stability. However, we should reiterate an important point: automation is not a miracle cure for streamlining QA pipelines. You should carefully consider when, how, and why you want to automate tests, as well as the costs and benefits of doing so for your specific project.

With that in mind, let’s consider some common pitfalls that startups may run into while automating QA and how to avoid them:

  • Early over-automation – The most common mistake startups tend to make in terms of QA automation is zealously trying to automate as much as possible, as early as possible. However, software tends to change a lot during the early stages of development, sometimes down to its very basic features. Automating test cases too early may lead to having to come back and re-create those tests, which can significantly drive up costs. Remember – compared to manual testing, automation often comes with high initial costs but lower upkeep. You don’t want to pay those initial costs more times than absolutely necessary.
  • Ignoring test maintenance - Automated tests require ongoing maintenance and updates to keep pace with evolving application features and changes. Failing to properly maintain your tests can lead to unreliable results, which defeats the whole purpose of automating. Similarly, you should consider upkeep costs when calculating the ROI of automation QA.
  • No ownership – The reality of working in startup companies is that employees tend to wear many hats, often due to budgetary constraints. This, in turn, often results in QA with no clear ownership or responsibility. Ownership can be handled in many different ways – from dedicated QA teams to “shift-left” methods. Just make sure that any QA automation has a clear purpose, goal, and methodology.
  • False sense of security – One of the goals of automation is to allow teams the space to allocate resources to other areas. However, we caution anyone against taking an overly hands-off approach. Not only do automated tests require constant updates and maintenance, but they also need to be regularly re-evaluated so they don’t fail to cover critical scenarios. Moreover, automated tests should be manually validated whenever possible to prevent defects from slipping into production.

Conclusion

A proper QA framework is essential for maintaining your software or app’s stability. Automating parts of that framework can yield excellent results in terms of ROI, provided this automation is properly implemented.

Specifically, automation often results in earlier defect detection as well as lower MTTR times. Many industry studies highlight the massive costs of post-release bug fixing as well as the devastating financial effects of unintended downtime. As such, a more reliable QA framework is an excellent way to prevent future costs.

Moreover, stability is important for building trust with investors, developers, and users alike. This trust is especially important for startups because they require investments to survive and grow.

As such, QA automation can be a highly cost-effective way for startups to improve key metrics like Escaped Defect Rates and MTTR, all of which are known for preventing revenue loss.

If you’re looking to find out whether QA automation is the right move for your startup, click here to schedule a stability audit with TechTailors. Our team of experts can help you find the most efficient and reliable QA solution for your startup.