Use analytics and other user data to focus and prioritize your content design system efforts
Want to use analytics and other user data to improve your content design system and make it more data-driven? ✨
A while back I wrote about how you can use questions you receive about content guidelines to help with the often overwhelming decision of where to focus your efforts as you and your team use your limited time and resources to build out content design system materials. Here’s Part 2, with tips for leveraging analytics and other types of user data that you may already have access to in order to help prioritize which sections, components, and templates to build or expand.
📝 Create a help log: maintain a spreadsheet (ideally without names or identifying information) that you can use to log content guidelines queries. When someone asks a question, you can note the date, category (like “Error messages”), and a short note about the query. Over time this will reveal the types of content guidelines your colleagues are engaging with but finding unclear or incomplete. You can use this data to help make decisions on areas to expand or clarify. If you amass a large log, you can also use it to build the case for more resources to help build out the content design system, especially if you include the role of the person asking the question (“UX designer,” “product manager,” “dev,” “UX researcher,” etc).
💬 Leverage bot analytics: if your team has built a GenAI-based bot to give your design partners an easier way to consult your style guide, look into whether there’s a way to responsibly and securely obtain anonymized, aggregated data on the types of queries it receives (for example, a list of the top entries that users are asking questions about, or a list of the top questions about casing).
📊 Use Figma terminology plugin analytics: if your team uses a Figma plugin to store your controlled terminology list, look into whether it offers analytics on which terminology entries are most popular. This may give you insights into related terms you should prioritize adding. It’s also possible that some of these entries are consulted frequently because they contain terms that are discussed often by product teams, and it might be worth flagging these entries for possible content research.
📈 Built-in tool analytics: if you use a tool like zeroheight to house your content design system, check the analytics to see which entries get the most traffic. Even if the tool you use doesn’t have an analytics feature, if your design system uses one that does, ask if they would be willing to give you data on which design component documentation entries get the most traffic. This will give you an idea of which component entries your design partners consult the most. It could reveal some good places to start if you’re unsure which components to start creating content guidelines for and want to make sure that what you build will be of interest to UX designers.
👍👎 Thumbs up/thumbs down: even if you don’t have access to content design system analytics, look into whether the tool you use to house your system has an option to add a thumbs up/thumbs down feature. Encourage your design partners to use it to indicate entries they found helpful or unhelpful. You’ll get valuable insights into entries that should be improved, and the very fact that someone found and visited an entry (even if you only know that through a 👎) is useful data.
👀 Personal observation: if you use Figma to house your content design system, make a mental note of where your colleagues are when you see them in your files. If they’re often viewing and/or interacting with a specific entry or template, that strongly suggests that they find it relevant to their product design work. It might also give you ideas on what to expand and related topics to add.
