Making rebates and payouts clear and simple
Industry
Fintech
Tools
Figma, FigJam
Role
Product designer
Overview
This project aimed to improve the Rebates Program experience in our trading platform for both retail and PRO traders. Rebates are a percentage of your trading fees, such as spreads or overnight charges, paid back to you.
Nevertheless, many traders were not using the program to its full potential. Users lacked a clear understanding of rebate calculations, spreads, and swaps, which led to:
Missed potential cashback from their trading activity
A high number of support requests related to the Rebates page
The need for better tools to track rebate progress, especially for swap-related rewards, for both beginners and high-volume traders
Goal
The goal was to create a transparent, motivating, and educational rebate experience that builds trust and helps traders make smarter decisions.
We aimed to:
Simplify the rebate structure and language.
Show earnings by asset type.
Add AI-powered tips to help users reach higher rebate tiers.
Maintain clarity and financial transparency.
Reduce confusion and support requests through improved design and information architecture.
Solution
I redesigned the cashback rewards feature to make it easier for traders to understand how much they could earn and how to increase their rewards. The new design focused on clear layouts, simple language, and visual tools that showed progress by asset type. I added educational tooltips, step-by-step explanations, and AI-powered tips to guide users toward higher reward tiers.
To make sure the changes solved real problems, I tested the designs with traders at different experience levels. Feedback from these sessions helped refine the flow, remove unnecessary elements, and make key information easier to find. We validated the final version with a smaller group of users before launching it to everyone.
The result was a more transparent and engaging experience. Traders could now quickly see their earnings, understand payout timelines, and track progress, which reduced confusion, lowered support requests, and increased interaction with the rewards page.
The process
Information architecture
A hierarchical breakdown of all rebate-related data, based on user questions and business logic. This helped define the structure and navigation of the redesigned rewards section, ensuring that every key user question was addressed in the interface.
First approach
In the first iteration, I focused on simplifying how the rebate amount is displayed and explored ways to improve user retention. I redesigned the rebate view for both retail and PRO clients, including swap rebates for PRO users. To keep users engaged, I proposed an individual daily streak feature and AI-powered insights tailored to their activity, motivating them to trade more strategically. Since one of the main requirements was to clearly communicate payout dates, I used a pre-existing disclaimer component from the company’s design system. I also designed two versions of the visualization: a large half pie chart and a compact pie chart, and left the decision to be validated later during usability testing.
Second approach
In the second iteration, I focused on finalizing the payout experience and making rebate details clearer. I designed two versions of spread and swap explanations and created three variants of rebate cards for clients with three or five assets.
Prototyping and usability testing
I prepared a clickable prototype and tested it with 12 participants, including both retail and PRO clients. The goal was to compare two formats for rebate calculations, test two versions of spread and swap explanations, and check which rebate calculation formula was easier to read. I also tested two ways to show estimated payouts: using an information icon or clickable text, and three ways to indicate interactivity in the tiers section: information icon, clickable box, or arrow.
Usability testing results
During testing, most participants preferred the second format for rebate calculations, finding it simpler, but suggested adding numerical examples for clarity. For estimated payouts, the information icon was favored over clickable text for being more intuitive. For tiers, the arrow indicator was preferred over other options as it clearly signaled interactivity.
Improvements based on feedback
Based on the testing results, I created the final version by removing the pie chart, which overloaded the interface with colors. I also removed the disclaimer and month title to create more space and make the layout cleaner. The progress card now includes estimated payout information, showing all key details at a glance, with more available on click. The information icon was replaced with chevrons, as users recognized this as a clearer signal that the card is clickable.
As users preferred a payout page with visualization, I replaced the plain list with a grouped monthly view, added bar graphs for quick comparisons, and organized detailed payout entries inside expandable sections for each month.
Handoff to developers
For the final stage, I prepared a complete set of components used in the final design, grouped by the screens they belong to. I updated all bottom sheets and rebate cards for every screen, covering both retail and PRO clients. I added every state of the estimated rebates widget with different values, as well as error and empty states for mobile and web. Every screen included detailed annotations describing user flows, interactions, and behavior.
Results
Achieved results:
Reduced support requests by ~25% through clearer information architecture and improved explanations of rebates
Increased engagement with rebate cards and breakdown screens by 30% thanks to redesigned progress visuals and detailed breakdowns
Reduced payout drop-offs by 15% with a simplified layout and grouped monthly views
Lowered user errors by adding tooltips, intuitive icons, and simplified rebate calculation logic
Cut task completion time by ~20% with clearer charts, indicators, and streamlined flows
Helped users better track their progress, showing current trading volume, earned rebates, and next tier target
Added a widget with total cashback, payout date, and asset class breakdown, reducing confusion and improving transparency for both retail and PRO traders.
Implemented redesigned components and layouts for the desktop web app
Delivered a dev-ready package with grouped components, responsive behavior, and annotated screens describing logic, interactions, and edge cases
