What Figma learns from your usage
Figma relies on user data to guide product decisions, from fixing performance bottlenecks to blocking spam. The company separates the data it collects into two buckets: functional data needed to operate the service, and analytics data used to improve the product.
Functional data: the minimum to get started
Signing up for Figma only requires an email address, name, and role. That small set of information is enough to start creating files and collaborating. Notably, Figma avoids asking for more sensitive details that other cloud services often require, such as ID verification or payment information. When users do purchase a paid plan, payment processing is handled by Stripe, Figma’s payment infrastructure provider, so Figma itself never touches those details.
Analytics data: three case studies
Analytics data captures how the platform is accessed and which features are used, ignored, or causing trouble. The data science team analyzes this information to inform development priorities. Here are three examples of how that data translates into tangible changes.
Improving the sharing experience
Data analysis revealed that only 20% of users opened the share modal within their first month, and just half of those users actually shared a file. The team hypothesized that simplifying the modal’s UI and moving secondary functions into separate tabs would make sharing easier. An A/B test confirmed this: the change produced a 2% increase in users sending invites and a 2% increase in the number of users invited per file. The team also watched for regressions in uploads to the Figma Community, a metric they thought might be affected, but saw none.
Reducing prototype crashes on iOS
After the iOS app beta was announced at Config 2021, a crash analysis found that prototypes were a primary cause of crashes on the platform, with 25% of prototype-related crashes occurring within the first 10 seconds of loading. The data also confirmed that complex prototypes were more likely to crash. These findings led to changes in incremental frame loading and image sampling, resulting in over a 50% reduction in prototype crash rates on iOS.
Blocking spam bots
Metadata about how the product is used also feeds Figma’s anti-abuse defenses. Bad actors attempt to use Figma to send spam or publish harmful content in the Figma Community. To distinguish real users from bot fleets, Figma collects subtle signals about user interaction patterns. These signals are processed through a secure pipeline that delivers them to both Figma’s backend and anti-fraud partners. The defenses use this context to block automated requests at multiple checkpoints across the product.
These examples show how data informs decisions about usability, performance, and security—all with the goal of keeping Figma useful for its design community.
