Support Data for UX

Consult with Customer Support to identify issues affecting users

UX professionals should view colleagues who regularly interact with customers, such as those in customer success or customer support, as a valuable resource for obtaining insights into the difficulties users encounter while using a product. To gather data and challenge assumptions, approach these coworkers as if they were gods. For instance, at an application development platform where customers repeatedly requested a feature that was already available, the UX team discovered that the current name failed to connect with users because it did not provide context about the feature's purpose. When debating a new name, the team consulted a customer support representative to learn what users called the functionality. They discovered that users had a specific term for the feature that was not reflected in the product name or documentation, so the team simply adopted the existing term instead of inventing a new name. Checking in with customer support became a regular part of the team's process for defining taxonomy, especially when renaming or improving the text of an existing feature.

To obtain insights into where customers experience the most friction, start a relationship with customer support. This is an excellent opportunity to gain access to their customer-centric knowledge. A brief email or Slack message can often suffice. When reaching out, make it clear that you want to make their jobs easier by reducing customer friction and that you share the goal of providing customers with a better experience. Have a specific question in mind when requesting information, such as "How many calls do you receive regarding feature X?" or "Where do users typically encounter the most confusion when performing X?" You can also seek permission to review support tickets or gather data from your company's online product community or social media presence. Once you have a list of issues that repeatedly prompt users to seek help, group them by feature and analyze the data for patterns. #CustomerSupportInsights