Overview

Workers care deeply about understanding how much they can expect to earn each month, yet compensation was difficult to track across programs, rules, and thresholds. This uncertainty made it harder for users to plan, stay motivated, and make informed decisions about how to allocate effort.

Role & Ownership

I led research planning and execution end‑to‑end, clarifying user needs early in the project and guiding iterative design decisions by synthesizing qualitative and evaluative findings for cross‑functional partners across Design, Product, Business, and Engineering.

Research Strategy

The research focused on understanding how users mentally model compensation, where confusion or mistrust emerged, and what information users needed to feel confident taking action. The work emphasized interpretability, clarity, and decision support over surface‑level usability alone.

Methods

• One‑on‑one interviews to surface existing tracking behaviors, expectations, and sources of uncertainty

• Concept testing to evaluate whether proposed designs supported understanding and strategic decision‑making

• Usability testing to ensure key information was discoverable and actionable across multiple compensation programs

Synthesis & Key Insights

Research revealed that many workers relied on fragmented or high‑level summaries provided by multiple sources, limiting their ability to understand how compensation was calculated or how close they were to meaningful thresholds. Designs that clearly explained earning structures and highlighted progress toward key milestones were perceived as significantly more valuable, as they helped users verify they were not leaving money on the table. 

Rather than seeking exhaustive breakdowns, users wanted clarity around what actions mattered most and how close they were to the next payout opportunity, enabling more confident planning and prioritization.

Impact

Research directly informed design decisions that prioritized transparency and progress visibility, transforming compensation tracking from a passive reference into an active decision‑making tool. The resulting experience improved users’ confidence in projected earnings and supported more deliberate, goal‑oriented behavior around maximizing compensation.