All cases Case 04 — portfolier

Trading Strategy Management

portfolier is a web product where a trader connects a trading account, studies how strategies actually performed and subscribes to the ones worth copying. I designed the MVP — the analytics the decision is made on, the marketplace, copying and subscriptions.

1.5 months from brief to an MVP handed over to development

Data-heavy by nature — equity curves, monthly tables, breakdowns by day, hour and symbol, and a filter panel that drives all of them at once
Analogues taken apart first — Portfeller and, in part, TradingView, to see where a trader expects to find what
Breakpoints generated, not drawn — I ran my own screens through Figma Make so the frontend team could see how each page reflows

Product: portfolier — web app for subscribing to and copying trading strategies (MVP)
Role: UX/UI designer — lead designer on the project
Team: Head of Product — set the tasks and reviewed every screen
Timeline: About one and a half months, MVP handed over to development
Scope: Portfolio analytics, chart and table filtering, adding a trading account, strategy marketplace, smart copying, subscriptions, profile, entry flows
Status: In development — part of the screens is published here

A trader on this product is answering one question: which strategy to copy, and with how much of the deposit. Everything on the screen exists to serve that question, which is why the analytics page is not a dashboard of pretty tiles but a working instrument: the filter panel on the left, the charts in the middle, the breakdown on the right, and every filter changing all three at once.

I took the analogues apart before drawing anything — Portfeller and, in part, TradingView — because in a category this established a trader already knows where things should be, and fighting that costs conversions rather than winning awards. What came out of it is a three-column structure that survives being filled with real numbers: capital growth over months, profit and loss by weekday, by hour and by symbol, and a portfolio share showing how much of the deposit each strategy holds.

Two things in the case are worth naming separately. The product has an AI insights block, and designing it meant designing what a machine is allowed to claim: the best trading day, the optimal window, the symbol that produces most of the drawdown — each as a short, checkable statement rather than a verdict. And the responsive behaviour was not drawn by hand: I fed my own screens to Figma Make and let it generate the breakpoints, so the frontend team could see how a page reflows without me spending days redrawing it.