Read this great article by Kerry Rodden. She writes that when designing for the web, you can analyze usage data for your product and compare different interfaces in A/B tests. This is sometimes called “data-driven design”, but I prefer to think of it as data-informed design — the designer is still driving, not the data.

There are acouple of useful methods to help choose and define appropriate metrics that reflect:

• The quality of user experience (the HEART framework)
• The goals of your product or project (the Goals-Signals-Metrics process)

UX metrics, as defined by Google product teams, suggested they tended to fall into five categories (HEART): 

• Happiness: measures of user attitudes, often collected via survey. For example: satisfaction, perceived ease of use, and net-promoter score.
• Engagement: level of user involvement, typically measured via behavioral proxies such as frequency, intensity, or depth of interaction over some time period. Examples might include the number of visits per user per week or the number of photos uploaded per user per day.
• Adoption: new users of a product or feature. For example: the number of accounts created in the last seven days or the percentage of Gmail users who use labels.
• Retention: the rate at which existing users are returning. For example: how many of the active users from a given time period are still present in some later time period? You may be more interested in failure to retain, commonly known as “churn.”
• Task success: this includes traditional behavioral metrics of user experience, such as efficiency (e.g. time to complete a task), effectiveness (e.g. percent of tasks completed), and error rate. This category is most applicable to areas of your product that are very task-focused, such as search or an upload flow.

Find out more and see the Goals-Signals-Metrics process at the original article here.