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Guide

Price intelligence for ecommerce that starts with your catalog

Real price intelligence connects your own products to comparable competitor offers, then shows why each price is fresh and trustworthy enough to act on. Comptrace finds and matches those offers automatically, so you skip manual competitor URL lists.

Imported prices and matched competitor rows stay private to your workspace.

Make your catalog the operating layer

Price intelligence for ecommerce should help operators decide which products need attention today, not hand them another disconnected dashboard. It starts with the catalog fields your team already trusts, then turns automated market checks into a focused queue of exceptions. Comptrace imports from a single product URL, Google Merchant Center, a CSV or feed, or a guided setup, and uses identifiers like GTIN, MPN, and brand to anchor every comparison.

  • Import from a product URL, Google Merchant Center, CSV, or guided setup to start fast.
  • Use catalog ownership, status, and commercial priority to decide what gets checked first.
  • Let AI match comparable competitor offers and discover sources without manual URL lists.
  • Keep imported prices, catalog fields, and competitor rows private to your workspace.

Prioritize the products that deserve action

A pricing screen should answer whether a product is drifting, exposed, protected by margin, or simply moving with the market. The useful output is a short list of decisions, not a wall of scraped numbers. Comptrace normalizes every competitor offer into price rank, average gap, and trend, then attaches a scraped-at timestamp so you know whether the evidence is current.

  • Use price rank to see whether your offer is cheapest, mid-market, or expensive.
  • Read average gap to focus on products with the widest competitive spread.
  • Watch trend to tell broad market shifts from a single merchant changing.
  • Trust scraped-at timestamps to separate fresh evidence from stale crawls.

Keep commercial decisions explainable

Pricing teams need to explain why a change was considered and which evidence supported it. Comptrace keeps that trace available, with the matched product, source URL, merchant, currency, and timestamp behind every signal. Coverage depends on category, country, and catalog quality, so gaps appear as exceptions with status states rather than being hidden. Your team decides the next action in its existing pricing workflow.

Keep reading

Related guides and setup paths

Move between practical guides for matching, scraping, freshness, and pricing decisions.

Price insights

Turn competitor price insights into decisions with price rank, average gap, trend, and freshness signals so you act only on products that need attention.

Scrape competitor prices

Learn how to scrape competitor prices the right way: AI product matching, Google-discovered offers, timestamped evidence, price rank, gap, and trend signals.

Pricing policy

Build an ecommerce pricing policy that turns matched competitor price evidence, freshness, and margin rules into controlled, auditable price changes.

Scraping freshness

See how scraped-at timestamps, queue and retry states, and stale-price gates keep competitor price data fresh and trustworthy before you act on it.

Google Shopping price monitoring

Turn Google Shopping listings into traceable competitor price evidence: AI-matched offers, scraped-at timestamps, price rank, average gap, and trend.

AI product matching

See how AI product matching pairs your catalog with comparable competitor prices using GTIN, MPN, brand, images, and Google Shopping evidence.

Monitoring vs repricing

Price monitoring vs repricing: monitoring gathers competitor price evidence; repricing decides. See how rank, gap, and trend connect the two safely.

Competitor price monitoring

Competitor price monitoring is the ongoing tracking of rivals' prices for comparable products. Learn how it works, what it tracks, and why it matters.

Resources

Practical competitor price monitoring guides: AI product matching, Google Shopping discovery, scraped-at evidence, price gaps, and pricing-policy actions.

Prices stay private

Your workspace is logically isolated. No catalog field, imported price, or scraped result ever feeds into another account.

Matching is explainable

AI uses product text, identifiers, imagery, retailer pages, and Google-discovered data to decide whether offers are comparable.

Metrics are action-oriented

Price rank, average gap, trend direction, and scraped-at timestamps tell teams what changed and whether the data is fresh.

See how your prices compare

Run a free competitor price check in minutes, then create a workspace to track it continuously.

Check competitor prices