A look at some of the tools and methods the UX Team employs to gather, analyze, and present user feedback.
Gathering and Analyzing Data
Thousands of students, faculty, staff, and researchers around the world use NYU Libraries’ website daily. Web analytics and electronic surveys enable us to gather significant qualitative and quantitative user data and feedback, including:
- the number of times the website and/or specific pages are used per day
- the type of device (desktop, tablet, mobile) and internet browsers being used to interact with our site
- user locations (country and city)
- the average amount of time a user spends on the site per session
- bounce rate (the percentage of sessions where users only use one page within the site and then leave.)
This data allowed us to identify behaviors among our user audiences and reflect that information in the new design. For example, we were able to see that a significant percentage of our users access the Libraries website on smartphones, and employ a responsive site design strategy (scaling an interface based on screen size) for the new site.
Crazy Egg, a “heat mapping” software tool, provides screenshots highlighting most visited areas of a page. By adding this tool to many of the pages on our current website, we have been able to understand the areas on each page our users are most interested in accessing. For example, when we added a “Reserve” button on our Study Spaces page, all but a small percentage of traffic (see screenshot below) migrated directly to that button upon accessing the page.
Web-based survey software (such as Qualtrics and Google Forms ) are effective for gathering quantitative and qualitative feedback. NYU Libraries uses surveys for a number of services and initiatives. For this project we were able to cull information from existing surveys-as well as create new ones to gather information.
Interpreting and Presenting Feedback Data
Mining data from the Ask-A-Librarian chat software allowed us to identify user behavior and create clusters of user types, which we then translated into personas, which are composite archetypes:
Because NYU Libraries has such a large population with diverse audiences, it can be challenging to effectively communicate about–and empathize with specific user group–when they are represented as data. Personas serve as stand-ins for segments of a website’s targeted audience who share similar behavior patterns. In the UX department we use personas to create journey maps, communicate user needs to stakeholders, and to serve as touchstones. Learn more about how personas were created for NYU Libraries.
User Stories/User Flows
To ensure the design and Information Architecture (IA) were rooted in user needs and behaviors, we created user stories and user flows for our personas, around typical site interactions. This process helped validate our decisions, as well allowed us to uncover unaddressed functionality issues.
Card sorting was used to gather feedback and evaluate content groupings. Participants were given topics and categories from the existing website, such as “Research Consultation,” “Contact Us,”and “Study Spaces,” and asked to sort the terms into logical groups. The results helped us to understand our users’ mental models and their perceptions of our library services. Results informed the information architecture and navigational elements of the new site.
Formal in-person usability testing is the most clinical of our methods and provides rich qualitative data. It involves creating a set of tasks designed to gain information about user behavior and reaction relating to specific functionality, content, or design of a website. Users are asked to think aloud and share their observations as they work through tasks. For these tests a moderator helps facilitate the testing process, while observers take notes (either in the room or remotely).
User testing has been ongoing throughout the redesign process. User testing reports from the past several years helped inform our preliminary IA and design ideas. These designs are then validated and iterated upon with additional user testing across audience types. More information about usability testing and our work can be found on our NYU staff wiki.