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Use case

MAP monitoring with an AI agent.

Find every seller of your products, compare their advertised prices with your minimum advertised price, and keep a dated record of each listing.

Updated · datawebot team

Connect your agent

How the check works

  1. List your products and MAP. One row per product: a clear name or model number and the minimum advertised price for each market.
  2. Find who sells each product. Your agent searches online shops and lists every seller's price for the product, with a direct link to each listing.
  3. Read the exact listing when it matters. For Amazon (10 countries) and Walmart US, an extraction Job reads the product page itself: 1 credit per page.
  4. Compare and keep the evidence. Flag offers below MAP, and store each one with the seller, price, link and retrieval time in your own spreadsheet or database.
  5. Repeat on your schedule. Run the same check daily or weekly from cron, GitHub Actions or your agent, and compare runs to see who changed price.

A prompt to start with

For each product in map.csv, find every seller in US shops, list their advertised price with the link, and flag any price below the MAP column. Save the results with today's date.

MAP policy and monitoring guideEcommerce price monitoring guideBuild a price tracker in Python

A few useful answers.

What is MAP monitoring?

Minimum advertised price (MAP) monitoring means checking that resellers do not advertise your products below the price your MAP policy sets. It needs the advertised price, the seller and a dated record of each listing.

Does datawebot send MAP alerts?

No. datawebot returns what each shop shows when your agent asks, with the retrieval time. The comparison with your MAP, the schedule and any alerts run in your own workflow.

Does datawebot decide whether a seller broke my policy?

No. It gives you the advertised price, seller and link as evidence. Whether a listing breaks your policy, and what to do about it, stays with you.

What does a check cost?

Product search and seller offers are free within a daily allowance. Reading a product page with an extraction Job costs 1 credit per page, and every account starts with free trial credits.