Essential Usability Metrics for SaaS

6 min readJun 8, 2022

Ever wonder why Netflix became so popular? Is it only because of the unique shows on the platform? Or why is Salesforce the world’s no 1 CRM tool? Is it only about the functionalities? But in a technically advanced world, there must be many similar platforms or tools that can bring the same functionalities to the plate as these two. Then what’s the differentiating factor? The answer is simple- it’s the user’s happiness and trust. In any business, the customer is the key, and for SaaS, the success of any product depends on the ease of usability. How easily and effectively users can use the software determines the success factor.

A metric is a system or standard of measurement. Usability Metrics are the metrics that help to measure the usability of a service or product. Usability metrics for a SaaS product are the primary method of understanding the customers’ satisfaction. It helps to find the success factor or loopholes in any product and enables the designers and developers to work on the betterment of the product. Moreover, it helps to increase the user experience.

Why is Usability Metric important?

There’re many reasons to use usability metrics. It helps to understand the areas that need improvement. Insights from usability metrics help designers design user-friendly products that allow users to finish their tasks without hassle. Again, product managers can make important decisions about a product based on usability metrics reports.

Furthermore, Usability Testing helps identify the features that might be difficult for the users or confuse them. These test results support the designer and the developer team to create a better, easy-to-use product. Consequently, better selling of a great product enhances the business as well. So, to be precise, there are three crucial parts that usability metrics play.

1. It provides essential insight into a product’s ease of usability, which helps the designers and developers create better systems.

2. SaaS companies can use usability metrics to compare products and quantify a usability problem factor.

3. It makes intra-department communication better. After usability insight comes, the product management, designer and the developer team can work together for better innovation.

Essential Usability Metrics for SaaS:

Usability metrics for SaaS can be divided into three major categories, by the:

● Effectiveness


● Satisfaction

Effectiveness: It’s about the precision and thoroughness with which users achieve their objectives. Success Rate and Number of Errors can measure effectiveness.

Success Rate: It’s a good indicator to measure the effectiveness of an interface. The success rate or completion rate determines how users can finish a specific task in a given time without facing any difficulties.

Success Rate= (No. of successful tasks completion/Total no. of Tasks)*100

Success scores for any product can vary from 0 to 1 in a binary system or 0–100. This score only gives a conclusion of YES or NO, overlooking other specific situations. For example, any partial task success is considered as a failure in this system.

The simplicity of this metric system makes this most popular and easy to understand. Although inclined toward an ideal scenario, any SaaS product should aim for achieving a 100% success rate; according to a study by Jeff Sauro, the average completion rate is 78%. The same survey shows that the success rate is highly dependent on the context of the task evaluation.

Number of Errors: It defines the number of errors users make while finishing a task using a particular product. No.of errors directly indicate the ease of usability of a product. Unintentional actions, slips, mistakes, or omissions can be part of the errors, for example, typing mistakes while entering data. At times, errors occur due to the lack of the users’ knowledge.

Errors can be measured in two ways.

1. Error Rate: Error rate measured by (Total no. of committed errors/Total no of attempts). For example, count the number of attempts if a user tries to click a disabled link or button.

2. Error Occurrence Rate: It is measured by (Total no of errors/ Total no of all possible errors).

Jeff Sauro concluded from an analysis of 719 tasks performed using consumer and business software that the average number of errors per task is 0.7, with 2 out of every 3 users making an error. Only 10% of the practical tasks were completed without error, implying that it is normal for users to make mistakes when performing tasks.

Efficiency: Efficiency determines the ease of usability of a product, i.e., how fast customers can finish their tasks. It is called Task Time.

Task Time= End time of a Task- Start time of the same task

Efficiency again can be calculated in two ways

Time-Based Efficiency: Time-Based Efficiency is calculated by combining the success rate and the measured task time.

N = The total number of tasks

R = The total number of users

nij = The results of task ‘i’ by user ‘j‘. If the user has completed the task, then Nij = 1, if not, then Nij = 0

tij = The time spent by user ‘j’ to complete task ‘i’. If the task is not completed, time is measured until the user quits the task.

Relative Efficiency: The Relative Efficiency is calculated by dividing the success rate by the task time. It is a good indicator of your product’s guidance system that helps users to complete their tasks efficiently.


Measuring satisfaction by metrics varies from company to company and depends on their expectations, goals, and working environment. Satisfaction questionnaires measure satisfaction after using a product.

Task-Level Satisfaction: After attempting a task (regardless of whether they succeed or fail), users are immediately given a questionnaire to assess how difficult that task was. These post-task questionnaires typically consist of up to 5 questions, frequently taking the form of Likert scale ratings.

ASQ: After Scenario Questionnaire — Asks three questions to assess the difficulty level.

NASA-TLX: NASA’s task load index measures the users’ mental effort on a 7point scale.

SMEQ: Subjective Mental Effort Questionnaire- 1 question that asks for rating their subjective mental efforts while completing a task.

UME: Usability Magnitude Estimation- It’s a standard to measure judgments of sensory stimuli.

SEQ: Single Ease Question- 1 question that asks users about their faced difficulties while using the product.

Test-Level Satisfaction: In usability tests, test level satisfaction measures the users’ overall ease of use. They are questionnaires distributed to users only after the test session has concluded.

SUS: System Usability Scale-10 item scale used to assess the overall usability.

SUPR-Q: Standardized User Experience Percentile Rank Questionnaire — Questions with a scoreboard spanned from 1–5 collect user experience on a large scale.

CSU: Computer System Usability Questionnaire (19 questions).

QUIS: Questionnaire For User Interaction Satisfaction- A 24 sets of questions applicable for managers to assess the system and find the areas for improvement.

SUMI: Software Usability Measurement Inventory (50 questions)- Helps measure computer software usability.

The choice of questionnaire depends on the allocated budget for user satisfaction measurement and the importance & impact of the users’ satisfaction on the overall project.

Sauro suggests using SUS to measure user satisfaction with software, hardware, and mobile devices and the SUPR-Q to measure test level satisfaction with websites. SUS is also preferred because it has been shown to produce very accurate results. Furthermore, it includes a simple scale that is easy to administer to participants, making it ideal for use with small sample sizes.

Wrapping Up

Usability metrics are not the most enjoyable aspect of a UX researcher’s job. There’s a lot more to it than just adding up the numbers. You must first recruit many users, create tasks, organize testing, observe and collect data, and then apply the formulas to obtain results.

Organizations willing to go the extra mile will be rewarded with a transparent, data-driven system of UX evaluation.

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