Jeff Sauro • February 2, 2011

It is the 25th anniversary of the creation of the most used questionnaire for measuring perceptions of usability.The System Usability Scale (SUS) was released into this world by John Brooke in 1986.

It was originally created as a "quick and dirty" scale for administering after usability tests on systems like VT100 Terminal ("Green-Screen") applications.

SUS is technology independent and has since been tested on hardware, consumer software, websites, cell-phones, IVRs and even the yellow-pages.

It has become an industry standard with references in over 600 publications.

- I think that I would like to use this system frequently.
- I found the system unnecessarily complex.
- I thought the system was easy to use.
- I think that I would need the support of a technical person to be able to use this system.
- I found the various functions in this system were well integrated.
- I thought there was too much inconsistency in this system.
- I would imagine that most people would learn to use this system very quickly.
- I found the system very cumbersome to use.
- I felt very confident using the system.
- I needed to learn a lot of things before I could get going with this system.

The SUS uses the following response format:

- For odd items: subtract one from the user response.
- For even-numbered items: subtract the user responses from 5
- This scales all values from 0 to 4 (with four being the most positive response).
- Add up the converted responses for each user and multiply that total by 2.5. This converts the range of possible values from 0 to 100 instead of from 0 to 40.

Over the years I've used SUS a lot in my own research and during usability evaluations. During this time I've reviewed the existing research on SUS and analyzed data from over 5000 users across 500 different evaluations.

This data shows that SUS is a reliable and valid measure of perceived usability. It performs as well or better than commercial questionnaires and home-grown internal questionnaires.

I've put these findings in a 150 page detailed report which contains valuable insights on background, benchmarks and best practices for anyone using the SUS. Here are a few highlights.

The best way to interpret your score is to convert it to a percentile rank through a process called normalizing. I've created a calculator and guide which takes raw SUS scores and generates percentile ranks and letter-grades (from A+ to F) for eight different application types.

The graph below shows how the percentile ranks associate with SUS scores and letter grades.

This process is similar to "grading on a curve" based on the distribution of all scores. For example, a raw SUS score of a 74 converts to a percentile rank of 70%. A SUS score of 74 has higher perceived usability than 70% of all products tested. It can be interpreted as a grade of a B-.

You'd need to score above an 80.3 to get an A (the top 10% of scores). This is also the point where users are more likely to be recommending the product to a friend. Scoring at the mean score of 68 gets you a C and anything below a 51 is an F (putting you in the bottom 15%).

When communicating SUS scores to stakeholders, and especially those who are unfamiliar with SUS, it's best to convert the original SUS score into a percentile so a 70% really means above average.

Sample size and reliability are unrelated, so SUS can be used on very small sample sizes (as few as two users) and still generate reliable results. However, small sample sizes generate imprecise estimates of the unknown user-population SUS score. You should compute a confidence interval around your sample SUS score to understand the variability in your estimate.

To help you in your next study with SUS or to interpret your existing SUS data I've assembled a comprehensive guide on how to use benchmarks, compare SUS scores and find the right sample size for your study.

3 Days of Hands-On Training on UX Methods, Metrics and Analysis.Learn More

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10 Things to Know about Usability Problems

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What five users can tell you that 5000 cannot

Confidence Interval Calculator for a Completion Rate

Nine misconceptions about statistics and usability

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Customer Analytics for DummiesA guidebook for measuring the customer experience Buy on Amazon | |

Quantifying the User Experience: Practical Statistics for User ResearchThe most comprehensive statistical resource for UX Professionals Buy on Amazon | |

Excel & R Companion to Quantifying the User ExperienceDetailed Steps to Solve over 100 Examples and Exercises in the Excel Calculator and R Buy on Amazon | Download | |

A Practical Guide to the System Usability ScaleBackground, Benchmarks & Best Practices for the most popular usability questionnaire Buy on Amazon | Download | |

A Practical Guide to Measuring Usability72 Answers to the Most Common Questions about Quantifying the Usability of Websites and Software Buy on Amazon | Download |

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