Clarity
Help designers define meaningful, well-structured events without requiring specialist knowledge.
FIGMA PLUGIN / AI & ANALYTICS
Analyzing
Figma plugin.
An AI-powered plugin that helps UX designers turn design context into consistent, editable analytics event plans—inside Figma.
MY ROLE
UX Design Lead & Builder
TIMELINE
Three months
PROJECT STAGE
Early-stage tool / initial usage feedback
IMPACT & OUTCOMES
~2 hours
Saved per analytics plan
Designer estimate compared with manual planning
5 hours / week
Design time freed up for other priorities
Early feedback from a small group of designers; time savings were estimated, not measured in a timed study. Weekly design time freed up is my estimate; usage data was one factor in the prioritization decision.
01 / THE PROBLEM
Design the experience.
Define what to measure.
Analytics setup is a point of friction between design, product, and engineering. Designers are expected to make data-informed decisions, but defining the tracking plan often happens too late.
Across large product organizations, event names and structures can be inconsistent. Teams depend on specialist analytics partners, and designers may lack confidence in deciding what to measure.
THE DESIGN OPPORTUNITY
Give designers guidance at the moment of design, so measurement becomes part of the workflow.
I designed and built an AI-powered Figma plugin to help designers generate analytics event plans from their design context without needing deep analytics expertise.
02 / DESIGN GOALS
Make analytics
part of design.
The plugin brings analytics planning into the tools designers already use. Shared standards guide the output, while designers retain the ability to review and edit the plan.
Consistency
Use shared naming conventions and logical event structures across features and teams.
Integration
Make tracking plans part of the design process, rather than an additional task after design or implementation.
Partnership
Support analytics experts with guided, standards-aligned output that designers can share with their partners.
My toolkit included Figma, ChatGPT, internal analytics standards, Markdown, and Cursor.
03 / HOW IT WORKS
From screen context
to a tracking plan.
Capture the design context.
The plugin reads the screen to gather context for the experience being designed.
Define goals and events.
AI helps define the goals that events roll up to, with guidance for event names, required and optional properties, state transitions, and success and failure signals.
Review, edit, and share.
The plugin generates a structured tracking plan that is fully editable in Figma. Designers can review it, make changes, and share it with product and engineering.
04 / OUTCOMES
Using tracking plans to inform design priorities.
Less time preparing a plan
Designers using the plugin estimated that it saved about two hours per analytics plan compared with putting plans together manually. This was feedback from a small group, rather than a formal timed study.
Usage evidence informed where we spent design time
I used the plugin to create a tracking plan for the billing area I supported as its dedicated designer. The resulting tracking showed that almost no traffic reached specific billing information.
Low usage was one factor in shifting our priorities. We continued supporting billing, but moved away from assigning a dedicated designer to it and put design effort into other areas. I estimate that this freed up five hours of design time per week for other priorities.
05 / WHAT I LEARNED
Checking usage and reviewing what we measure.
Look at usage before committing design time
The billing findings helped me see that we should understand how much people actually use an area before deciding how much design time to put into it.
Treat generated events as a starting point
The plugin helped designers find a direction for their analytics plans. They still needed to review the suggested events and check that those events matched what they actually wanted to measure.
THE TAKEAWAY