Summary: Creating realistic data for prototypes is a chore. Use these prompting tactics with generative AI to enhance content fidelity in usability testing.
Prototype testing is at the core user-centered design. But crafting realistic data for prototypes that you plan to test is time-consuming. Especially when the design itself is still evolving, you’re pressed for time, or you are a one-person UX team . Don’t let the struggle of crunching numbers discourage you. Generative AI can help.
Users Will Scrutinize Your Tables and Charts
Research in data sensemaking by Laura Koesten and colleagues found that when participants were given unfamiliar data, they spent more time looking for outliers and inconsistencies than when they worked with familiar data. If you plan to test a prototype (especially if your user personas critique data frequently), your study participants will scrutinize the prototype’s tables and charts, whether you want them to or not .
This article will discuss practical tactics that any UX professional with access to a general-purpose generative AI tool can use to create higher-quality charts and tables efficiently. To illustrate these tactics, we use a hypothetical example of a sales and marketing-management app targeting ecommerce retailers.