#
web3
#
gaming
Perpetual trading interfaces often fail at the moment they matter most. Scope: UX strategy · Interaction design · Frontend implementation
While traders are executing positions, the UI continues to compete for attention, increasing cognitive load and decision risk.
This project focused on reducing cognitive load at the moment of trade without altering core mechanics or slowing down experienced users. Instead of removing functionality, the interface was redesigned to give traders control over what they see during active execution.
Based on DeFi trading benchmarks, the redesigned experience is expected to reduce active-session drop-off from roughly 40–55% to 20–30%, increasing trade frequency and contributing an estimated $200k–$500k in retained TVL.
The challenge was to address these problems without changing underlying trading logic, compromising performance, or alienating professional users accustomed to fast, information-rich interfaces.
During live trading, most perpetual interfaces keep all major elements visually active at once. Order books dominate screen space, market switching interrupts focus, and position management requires unnecessary navigation. These issues are most pronounced on mobile, where fragmented flows and limited screen space increase execution friction. Under volatile conditions, this added cognitive load directly increases error risk and reduces trader confidence.
The interface was redesigned around execution intent rather than static layouts. Information density became contextual instead of permanent.
The order book was made collapsible, allowing traders to prioritize price action and surface depth only when needed.
Market switching was moved into a collapsible panel to preserve context and reduce mental resets.
Mobile execution was redesigned as a continuous, scroll-based flow to minimize taps and fragmentation.
Open positions remain persistently accessible through a lightweight dropdown, enabling quick exits or adjustments without leaving the trading context.
Familiar navigation patterns were retained to avoid relearning cost and prevent errors under pressure.
