There is a whole array of valuable user experience (UX) performance indicators that you can use to translate the success and progress of your product experience efforts into tangible metrics.
UX key performance indicators (KPIs) enable care for the human condition to be transformed into an easily understood feedback loop between customers, stakeholders, developers, and designers. With UX KPIs, you can bring new insights into digital experiences through the perspective of the end user together in a set of quantitative data points used to measure, compare and track UX. These KPIs reflect the overall goals of your business, such as revenue growth and retention, taking the invisible and making it tangible.
There’s a famous quote that goes ‘people ignore products that ignore people’. UX key performance indicators are core metrics to study users and measure the success of your empathetic design thinking. They are exactly what helps you to do the opposite of ignoring people.
Performance metrics align with and justify your vision, goals and strategy, by being measurable values that demonstrate how effectively you are achieving key objectives. UX KPIs are a part of a broader user experience strategy encompassing engagement, conversion, adoption and retention. They are the yardstick of the external effectiveness and internal efficacy of your user experience culture.
If you want to succeed in creating value, it makes sense to build KPIs to track user experience.
By designing products and services for optimal human interaction and building systems that support the user journeys, you can create not only a better product match, but also increase engagement and trust. From a business perspective, monitoring your user experience indicators will ensure you achieve these coveted gains with less trial and error AND at less expense.
To track the success of user experience activities, you need to employ user experience specific KPIs. These are part of the UX strategy to balance business goals with usability. That is, reducing risk and replacing assumptions with facts and quantifiable data.
Your metrics should be defined by your objectives. Clear objectives will empower you to select the metric or metrics best suited to charting your progress toward attaining them.
If you’re looking at how to optimise the user experience, start by observing user interaction with your product and identify any bottlenecks or roadblocks. Some of the most common behavioural metrics you might look at to measure UX include time on task, error rates, completion rates, adoption and retention.
To get the full picture, though, you need to capture how the experience of your product feels for users. This means going straight to the source and employing metrics based on user feedback, often referred to as attitudinal KPIs. Garnering user attitudes helps quantify aspects of the UX that can’t be tracked automatically.
Here are a few methods for transforming emotion into something quantifiable:
Considered the “quick and dirty” tool for measuring usability and learnability, the System Usability Scale consists of a 10-item survey in which respondents are directed to answer using a Likert scale of ‘Strongly disagree’ to ‘Strongly agree’.
The SUS is a standardised performance metric of perception.
Used in customer experience programs, the NPS is measured with a single simple question:
Respondents give a rating between 0 (not likely at all) and 10 (extremely likely), and depending on their response, customers fall into one of three categories (promoters, passives, or detractors) to establish a net promoter score.
The NPS is a metric of loyalty.
Data for Customer Satisfaction scores are collected during user interviews or specially developed online surveys. They are used to gain a wider understanding of how users feel using a product or experiencing a service at different touchpoints and stages.
Alternatively known as CX metrics, CSAT gives a numeric indicator of satisfaction.
UX KPIs are vital for ensuring UX design decisions are made and evaluated using fair evidence rather than personal bias and opinion. Attitudinal metrics are where you ‘quantify’ qualitative data.