Measuring the user experience and the impact of effort on business outcomes

How do you know when a user experience isn’t hitting the mark? Do you wait for it to show up in qualitative feedback? Do you have a long list of different metrics that you have to keep track of that could potentially signal a problem? And how do you know if your good or bad experience is impacting other areas of the business? These are common problems for product managers and the data scientists and analysts who support them. To solve them, I propose creating an aggregate metric that represents the effort or friction experienced by your users - a User Effort Index. This can be achieved through data exploration, statistical analysis, and machine learning - but should also be informed by your product knowledge. Once created, you can use a User Effort Index to improve the user experience through EDA, A/B testing, automation, cohort analysis, and more. My talk will go through the steps of creating a User Effort Index and suggestions on how to use the metric to improve the user experience.