Marek Ziółkowski
Chief Solutions Officer
Ross Krawczyk
Reviewed by a tech expert

33 critical software metrics every SaaS company should measure

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As digital platforms continue to evolve and grow, it's becoming increasingly important for IT professionals and CTOs to effectively monitor their product’s health and performance. This effort is key in ensuring high user satisfaction and smooth operation of the platform, allowing for the early detection and swift rectification of underlying issues. The most practical way to achieve these goals? By measuring specific technical KPIs – and there is a good reason: what gets measured gets managed.

In this article, we will explore the 33 critical metrics for SaaS that you should consider monitoring if you want to manage your growing digital platform effectively. Naturally, there is no need to use all of them – select and monitor the KPIs that align with your business goals and platform objectives.

Availability KPIs

First up, let's start with a vital cornerstone of any digital platform: availability. The uptime of a service or website can make or break the business. Users expect services to be available 24/7, so maintaining high system availability should be paramount for any CTO. By measuring aspects such as uptime, time to repair, and system failures, you can ensure that the platform remains accessible and speedy, thereby meeting user expectations and fostering trust. This is especially important for any service or business competing for the users’ dollars.

Let's have a closer look at these essential availability metrics and their importance in maintaining a high-performing digital platform.

  1. Availability. Expressed as a percentage of uptime in a given period of time. For instance, a digital platform’s 99.9% availability means it was up and running 99.9% of the time.
  2. Mean time to repair (MTTR). This is the average time taken to fix a breakdown and restore the system to its fully functional state. A lower MTTR indicates higher system reliability.
  3. Mean time between failures (MTBF). This represents the average time elapsed between system or component failures. The longer the MTBF, the more reliable the system.
  4. Number of failures. This one refers to the total number of system breakdowns during a specified period. It measure can help identify recurring issues needing proactive attention.

Bugs KPIs

Bugs can manifest in various forms and have far-reaching implications on user experience, system integrity, and overall performance. Let’s delve into the key bug-related metrics that are indispensable for maintaining a healthy, reliable, and efficient digital platform.

  1. Number of bugs in software. A direct count of known software bugs. Lower bug counts indicate superior software quality.
  2. Number of wrong responses from internal components. A measure of internal system errors. This could include microservices returning incorrect data or failing altogether.
  3. Crash-free user experience. The percentage of daily active users that had a crash-free experience. This is a direct reflection of your software's stability from the user's perspective.

By closely monitoring these metrics, you can gain insights into potential software issues, ensure stability, and foster a positive user experience.

Server-side response time KPis

The server-side response time refers to the duration taken by the server to respond to a user's request, significantly influencing the overall performance and speed of your digital platform. High response times on the server side can be an indication of underlying issues that might negatively impact the user experience. In this section, we will discuss two primary server-side response metrics – website response time and microservices response time. These metrics will give you crucial insights into your platform's performance from a server-side perspective.

  1. Website response time. The time taken for your server to respond to a request from a user's browser. Lower is better.
  2. Microservices response time. The time it takes for internal components like microservices to respond to requests. Longer response times can indicate problems within your system's architecture.

User-side response time KPis

In the world of digital platforms, user experience is king. A key component of this experience is the system's responsiveness to user actions. Delayed response times can lead to user frustration, poor user engagement, and, ultimately, a decline in platform use. In this section, we will look at KPIs related to the user-side response time. These metrics will help you gauge how effectively your system handles user interactions, with a focus on how quickly and efficiently it responds to user actions and requests.

  1. Website load time. The time it takes for a user's browser to fully load your website. High load times can negatively affect user experience and bounce rates.
  2. User actions response time. How long it takes for the system to respond to user actions. This impacts the user's perception of system speed and efficiency. Lower is better.

Agility KPIs

Speed, adaptability, and responsiveness are increasingly important in today's digital landscape. Metrics such as time to market, lead time, and cycle time are helpful in identifying project bottlenecks, streamlining workflows, and enhancing your team's agility. This ability to swiftly respond to market demands or internal needs is critical to staying competitive and ensuring high user satisfaction in the rapidly evolving digital world.

  1. Time to market (TTM). The total time from the conception of a product or feature until it is ready for sale or use. A shorter time to market can offer competitive advantages.
  2. Lead time (for bug or change request). The time from the detection or request of a change (including bug fixes) until its implementation.
  3. Cycle time. The total time from the start to the finish of your process, as defined by you and your team.

Quality assurance KPIs

This area focuses on preventing defects in your system and ensuring that your product or service meets defined standards of quality. The metrics in this section, including unit test coverage, automated test coverage, and defects distribution, provide valuable insights into the quality of your software and the efficiency of your testing procedures. High-quality software not only enriches user experience but also reduces the costs and efforts associated with bug fixes and system downtime. So, let's explore these essential quality assurance KPIs that can help you improve software quality and foster user satisfaction.

  1. Unit tests coverage. The percentage of your code covered by unit tests. High coverage can indicate a lower chance of bugs in production.
  2. Automated test coverage. The proportion of code tested by automated testing tools. High coverage can reduce the risk of regression errors in future releases.
  3. Defects distribution. The dispersion of defects in different modules of the software. This can help identify problem areas needing more robust testing.

User usage KPIs

As we venture further into our list of essential SaaS metrics, we enter the domain of user behavior and engagement. These metrics, under the umbrella of “User Usage”, provide a valuable window into how your users interact with your platform. By understanding user behavior, you can identify strengths and weaknesses in your platform, make data-driven decisions to enhance user experience, and ultimately drive user retention and growth. Let's delve into the specific user usage metrics that you should be monitoring for your digital platform.

  1. Number of logins. The total number of user logins over a certain period. An increase in this number indicates growing user engagement.
  2. Active users (daily/monthly). The count of users who have interacted with the platform within a specified time frame.
  3. Number of photos added. This metric provides insights about user engagement and platform usage and is particularly important for platforms that rely on user-generated content.
  4. Number of offers viewed. A great way to track user engagement with promotional materials or product offerings on e-commerce platforms.
  5. Shopping cart abandonment rate. The percentage of users who add products to their shopping cart but do not complete the purchase. This could indicate problems in the checkout process that need to be addressed.

Resource utilization KPIs

As we move into the section on Resource Utilization, it's important to underline that the efficient use of resources is a cornerstone of a high-performing digital platform. It ensures that your system is equipped to handle the demands placed on it without over-investment in costly resources. Whether it's your computing power, storage, or software services, understanding and managing the utilization of these resources will have a direct impact on both system performance and your bottom line. The metrics we cover in this section will help you assess the workload on your system and provide insights to optimize costs and improve system scalability.

  1. Number of users per CPU core. This one measures your system’s efficiency and can help identify the need for more computational resources. Low numbers are bad and call for system upgrades.
  2. SaaS and PaaS per user. This metric relates to the cost and usage of Software as a Service (SaaS) and Platform as a Service (PaaS) per user. It can assist in predicting costs as your user base grows.
  3. Average cost of bare-metal unit (purchase and maintenance). This refers to your physical servers' total cost, including purchase and maintenance costs. It's a key consideration in budgeting and cost management for your IT infrastructure.

Cybersecurity KPIs

Data breaches and cyber threats are an ever-present risk for SaaS platforms, making security a paramount concern. Security breaches can lead to significant financial loss, damage your brand's reputation, and erode customer trust. The following KPIs provide insights into the robustness of your security measures, helping identify vulnerabilities, thwart potential attacks, and maintain the trust of your users. The following metrics focus on areas such as authentication failures, anomaly detection, system updates, and patch application times.

  1. Number of failed authentications. This can help identify possible malicious activities, as many failed authentication attempts may suggest a brute-force attack on user accounts.
  2. Number of anomalies detected. Anomalies might point to security threats. Early detection can help prevent potential breaches.
  3. Up-to-date systems ratio (security patches, minor updates). Keeping systems updated with the latest patches is crucial for security. This metric shows the proportion of your systems that are up-to-date.
  4. Average time for applying patches. This KPI measures the average time your team takes to apply security patches. Faster times can minimize the window of vulnerability.

Disaster recovery KPIs

Robust disaster recovery measures are paramount to ensure the continuity and integrity of your platform. The following two SaaS metrics are integral to understanding how well-prepared your platform is to handle catastrophic events. They can help you assess the readiness of your recovery procedures, the efficiency of restoring services, and the coverage of your recovery plan. By keeping an eye on these KPIs, you can improve response times, minimize data loss, and ultimately ensure the survival and recovery of your platform, even under the most adverse circumstances.

  1. Recovery plan coverage. This evaluates the percentage of systems, applications, and data covered under a disaster recovery plan. A high coverage ratio is crucial to minimize loss in the event of a disaster.
  2. Mean time to recovery (MTTR). The average time it takes to restore a system after a disaster or outage. A shorter MTTR is indicative of a more resilient and efficient recovery process.

Technical debt KPIs

As your digital platform grows, it's natural to accumulate some technical debt – the term refers to the implied cost of additional rework caused by choosing the quick and easy solution now instead of using a better approach that would take longer. Much like financial debt, if not managed properly, technical debt can snowball over time, leading to costly and time-consuming fixes in the future.

In this section, we will discuss key SaaS metrics related to technical debt, giving you the tools to quantify, track, and manage it effectively. Understanding and addressing technical debt is crucial to ensure the scalability and long-term success of your platform.

  1. Cost to fix issues found during static analysis. These costs can include complexity, duplications, and violations. Keeping track of these costs can help you assess the economic impact of your technical debt.
  2. Cost of reimbursing each of the debts (based on estimations). This metric relates to the estimated cost of repaying technical debts, such as refactoring code or fixing software design issues. Keeping this low over time suggests a well-maintained codebase.

How RST Software helps SaaS companies build excellent digital platforms

Monitoring these 33 key metrics will help you build a comprehensive understanding of the state of your digital platform, enabling quick response to issues, optimal resource allocation, improved decision-making, and, ultimately, higher user satisfaction.

If you're looking for some addition help with SaaS development, simply drop us a line at hi@rst.software, and we'll take it from there.

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