Luxury Watch Market Pricing Intelligence Engine
Budget: ₹75,000 – ₹150,000 INR
We are building an internal Pricing Intelligence & Automation Engine for the secondary luxury watch market.
Objective
Automate competitive price monitoring, sourcing intake, and rule-based pricing decisions to enable faster, data-driven buy and list pricing.
Core Components
1. Marketplace Data Aggregation Layer
Scrape/ingest listings from marketplaces (e.g., Chrono24, eBay).
Normalize by reference number, condition, year, region, seller rating.
Remove outliers and low-quality listings.
Store historical pricing for trend analysis.
2. Pricing Intelligence Engine
Calculate market floor, median, and liquidity indicators per SKU.
Track price deltas vs internal target cost and margin thresholds.
Apply business rules (min margin %, velocity tier, inventory age).
Recommend optimal buy price and listing price.
3. Messaging Listing Parser
Parse inbound dealer listings (e.g., WhatsApp).
Extract structured fields (ref #, condition, set status, price, currency).
Standardize shorthand pricing formats.
Auto-push clean data into sourcing dashboard.
4. Internal Dashboard
SKU search & filtering.
Real-time market comparison.
Margin simulation.
Alerts for pricing opportunities (Slack/email).
Expected Outcome
Reduce manual comp checking by 80%+
Improve pricing accuracy and margin control
Faster quoting turnaround for sourcing team
Centralized, structured pricing intelligence database
Objective
Automate competitive price monitoring, sourcing intake, and rule-based pricing decisions to enable faster, data-driven buy and list pricing.
Core Components
1. Marketplace Data Aggregation Layer
Scrape/ingest listings from marketplaces (e.g., Chrono24, eBay).
Normalize by reference number, condition, year, region, seller rating.
Remove outliers and low-quality listings.
Store historical pricing for trend analysis.
2. Pricing Intelligence Engine
Calculate market floor, median, and liquidity indicators per SKU.
Track price deltas vs internal target cost and margin thresholds.
Apply business rules (min margin %, velocity tier, inventory age).
Recommend optimal buy price and listing price.
3. Messaging Listing Parser
Parse inbound dealer listings (e.g., WhatsApp).
Extract structured fields (ref #, condition, set status, price, currency).
Standardize shorthand pricing formats.
Auto-push clean data into sourcing dashboard.
4. Internal Dashboard
SKU search & filtering.
Real-time market comparison.
Margin simulation.
Alerts for pricing opportunities (Slack/email).
Expected Outcome
Reduce manual comp checking by 80%+
Improve pricing accuracy and margin control
Faster quoting turnaround for sourcing team
Centralized, structured pricing intelligence database