Market price engine template

The problem

Monitoring a marketplace for pricing anomalies and genuine seller trust is impossible to do manually. Bait prices, troll listings, and untrusted sellers distort the market, making it hard to price items accurately or safely.

How it works

1. Fetch Listings: rotates through pet catalog searches, fetching up to 400 listings per run.
2. Normalize: uses regex to extract canonical item names, drops junk, and handles price conversions.
3. Seller Profiling: fetches profile data with a 6-hour cache and TOTP authentication.
4. Market Analysis: aggregates listings by item and tier, filtering junk and troll titles.
5. Trust Gate: rejects sellers with low feedback, too few reviews, or new accounts.
6. Statistical Trimming: uses median-based filtering to remove low-bait and high-troll outliers.
7. Price Calculation: applies dynamic markups based on market value and validates against historical anchors.

Read the full story in the case study, or see the system on the Projects page.

What you get

• The n8n workflow file, importable as JSON.
• The PostgreSQL schema for listings, sellers, and price history.
• The JavaScript normalization logic and the seller trust scoring rules.
• A written setup guide for the Gameflip API connection and TOTP authentication.
• A redacted sample of a run output showing pricing per item tier.

Requirements

• A running n8n instance (cloud or self-hosted).
• A PostgreSQL database.
• A Gameflip account with API access enabled.
• TOTP secret configured for authenticated profile fetches.
• Node.js for the JavaScript normalization step.

Redacted samples