Marketplace e-commerce · Pricing
Repricing without manual price control: a contract-guaranteed pilot
Competitor prices tracked per SKU on the marketplace, a price computed inside an agreed corridor, applied only after confirmation. Pilot: 10 SKUs, setup within 14 days.
- Status
- Pilot
- Timeline
- 3–4 weeks (estimate; 2 weeks in git)
- Stack
- TypeScript
- NestJS
- React
- PostgreSQL
- Redis / BullMQ
- Puppeteer / Chromium
The task
A home-appliance maker sells on a large marketplace as a third-party seller. Platform promotions and undercutting inside the same product card push the shelf price below target, and checking every offer per SKU by hand is not feasible. The client needed a system that holds the target price or takes the best competitor price within an agreed corridor, never applies it without confirmation, and logs every decision.
What we built
- We built a service that walks the SKU product cards on a schedule and collects every seller's offer. Collection is gentle: a standard browser, no evasion of platform limits. Stale data is excluded.
- Pricing follows the two contractual scenarios. The result never leaves the corridor; every decision is stored with its inputs for audit. Deterministic rules, no LLM involved.
- No price is applied without confirmation: a decision goes to the external execution service and counts as applied only after an explicit reply. Pricing and execution statuses are shown separately.
- Contract terms are enforced in code: a 10-SKU cap, two scenarios, setup and pilot deadlines. All 8 acceptance criteria are enforced in code; most are also checked by contract tests.
- Production is provisioned: isolated containers, daily backups, preflight checks, rollback, alerts. Launch follows receipt of the client's input data.
Outcome
- 10 SKUs · 2 scenarios
- pilot scope; the SKU cap and both scenarios are enforced in code and verified by contract tests — the cap cannot be exceeded
- up to 14 days
- contractual setup window from client inputs to launch, then a 1-month pilot; the service tracks the dates and closes access when the period ends
- 8 of 8
- technical acceptance criteria enforced in code; most are also verified by contract tests and a migration smoke test
- 5 services · 4 networks
- hardened production stack: read-only containers, pinned images, reverse proxy without Docker access
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- panels on one project and wall panels on another matched the manual specs line by line, size groups included; area within 0.001 m²
- 2–15 h → 10–30 s
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Marketplace e-commerce · Sales analytics
In productionOne profit per SKU across three marketplaces, reconciled to 0.00%
Five seller accounts on WB, Ozon and Yandex Market merged into one SKU-level P&L: 0.00% variance vs the client's manual benchmark, forecast 2.7× more accurate than naive.
- 0.00%
- variance vs the client's manual benchmark across units, revenue, COGS, profit and margin for a control SKU over a month; threshold was 1%
- 2.7×
- more accurate than naive: weekly WAPE on SKUs driving 80% of revenue, 29.6% vs 81.4%. The 25% goal is open: history covers 66.9% of SKUs
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