Competitor pricing,
in real time.
A pricing intelligence surface for e-commerce category managers — elastic rules, alerts, and revenue forecasts on a 5-second refresh.
- HTML · CSS
- Next.js
- Tailwind
- Sector
- Retail · Pricing
- Users
- Category managers, pricing analysts
- Scope
- Product UX · data UX · rules engine UX
- Surface
- Web app
• 01 · Overview
Overview.
Designed a pricing intelligence platform for a mid-market e-commerce retailer with 12,000 SKUs. Role: principal product designer, working with pricing strategy and a small front-end team.
• 02 · Challenge
The challenge.
Category managers were exporting CSVs from three competitor scrapers, joining them in Excel, and updating prices on a 48-hour cycle. Margin loss from stale pricing was estimated at 4-6% per quarter.
• 03 · Process
Process.
Started with a workflow audit and shadowed three category managers across one full pricing cycle. Mapped the rules they were using mentally and made them explicit. Designed an elasticity-aware rules engine they could author themselves without engineering.
- Three full pricing-cycle shadow sessions
- Mental-model mapping of implicit rules
- Self-serve rules-engine UX validated in 5 user tests
• 04 · Solution
Solution.
A two-pane workspace: live competitor grid on the left, elastic rules editor on the right. Rules can be authored in plain language ("if competitor X drops below my price by 5%, alert and propose match"). Revenue forecast updates as you type.
- Two-pane workspace — data + rules in one screen
- Plain-language rules editor with autocomplete
- Live revenue forecast under each proposed rule
- Alerts thread directly into Slack and email
• 05 · Results & metrics
Results.
- 48h → 5minpricing cycle time
- +3.4%gross margin recovered in Q1
- 92%rule changes shipped without engineering
