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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

Generated analytics goals and event table in Figma, including event names, properties, code snippets, and descriptions
An editable analytics plan connects measurement goals with detailed event definitions.
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.

Clarity

Help designers define meaningful, well-structured events without requiring specialist knowledge.

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.

01

Capture the design context.

The plugin reads the screen to gather context for the experience being designed.

02

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.

03

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.

Plugin analyzing a Figma frame and extracting text, components, navigation elements, and context
Step 1: Read the Figma frame to establish design context.
AI-generated goal, proposed key result, and metrics with controls to confirm or refine the suggestion
Step 2: Review and refine the proposed goal and measurement signals. The displayed target is a generated suggestion, rather than an achieved result.
Editable Figma tracking plan with structured events and their properties
Step 3: Review the structured tracking plan and share it with product and engineering.
04 / VALIDATION & EARLY IMPACT

Less friction.
More confidence.

Initial usage feedback pointed to faster tracking-plan creation, more consistent events, and greater confidence discussing analytics.

  • Designers reported time savings when creating tracking plans.
  • Shared event structures helped improve consistency across features and teams.
  • Designers felt more confident discussing analytics.
  • Feedback indicated better collaboration with analytics and engineering partners.

One Webex designer described moving from a day of work to minutes. In my own use and a small group of other designers, the plugin saved an average of about two hours per analytics plan. Adoption was limited; this is an early result rather than a team-wide outcome.

THE TAKEAWAY

Designing the experience includes
designing how to learn from it.

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