Multi-Retailer MAP & Price-Violation Monitor

Monitor a brand's products across multiple retailers, match each SKU across their disparate catalogs, and detect MAP (Minimum Advertised Price) violations and unauthorized resellers - from logged-out public product pages.

Single-retailer price scrapers are a commodity (priced to the floor). The value here is the layer enterprise MAP tools gate behind quote-based pricing: "here are my SKUs - flag everywhere they're advertised below MAP, and by whom." That means two things this actor owns end to end:

1. Cross-retailer SKU matching + normalization - one product collapsed across retailers by UPC / MPN / fuzzy name, with one normalized price/seller schema.
2. MAP violation detection - advertised price below the floor, graded by severity, cross-referenced against your authorized-seller list.

Responsible use (read this). Retailer Terms of Service treat scraping as a gray area, so this actor is deliberately conservative: logged-out public product pages only, polite rate limits, capped result counts, no account creation, no login, no CAPTCHA bypass. A blocked retailer fails soft with a documented record - we never fabricate a price. Use within each retailer's terms and your own legal counsel's guidance. You are responsible for how you use the output.

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Modes

Mode	What it returns	Charges
price_scan	Normalized public price rows per product across retailers (the flat listings).	listing_record
cross_retailer_match	Each product collapsed into one cross-retailer view: which retailers carry it, price spread (min/median/max), lowest offer.	listing_record + sku_match
map_monitor (flagship)	Everything above + MAP-violation detection with graded severity, seller identity, and unauthorized-seller flags, plus a violation summary.	+ map_violation_flag per violation
seller_audit	Offers grouped by seller, with unauthorized third-party resellers flagged and a below-MAP cross-reference.	listing_record + map_violation_flag

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Retailer coverage (honest labelling)

Retailer	Code	Access	Anti-bot	Coverage
Target	target	RedSky public web JSON	moderate	full
Best Buy	bestbuy	search HTML	high (Akamai)	full
Newegg	newegg	search HTML	moderate	full
Walmart	walmart	__NEXT_DATA__ JSON (browser tier)	high (PerimeterX)	full
The Home Depot	homedepot	GraphQL via browser	high	catalog*
Lowe's	lowes	SPA state blob	high	catalog*
Costco	costco	search HTML	high	catalog*
B&H Photo	bhphoto	search HTML	moderate	catalog*
Wayfair	wayfair	SPA	high	catalog*
Macy's	macys	SPA	high	catalog*
Micro Center	microcenter	product grid HTML	low	catalog*

* catalog = registered with the correct public surface, access method, anti-bot tier and proxy, and wired into the escalation pipeline, but a retailer-specific parser is pending. These emit a documented retailer_pending note rather than fabricated data. Upgrading one to full is a single parser - the orchestrator, matcher, violation engine, and monitor layers are retailer-agnostic. The live access_notes record in every run reports the full matrix and which tier each fetch used.

Anti-bot escalation

On a block, the fetch ladder escalates instead of giving up:

httpx (datacenter)  ->  curl_cffi Chrome-TLS impersonation (residential)
                    ->  patchright stealth browser (residential)  ->  fail-soft

use_browser_fallback (default on) enables the curl_cffi + browser tiers; Walmart and the WAF-fronted retailers need them. The optional CAPTCHA solver is off by default and never invoked by the shipped recipes - a CAPTCHA wall fails soft. Set browser_cdp_url to point the browser tier at a warm anti-detect browser for the toughest managed-challenge retailers.

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Input

{
  "mode": "map_monitor",
  "products": [
    {
      "label": "Sony WH-1000XM5 Headphones",
      "brand": "Sony",
      "model": "WH-1000XM5",
      "upc": "027242923058",          // best: exact cross-retailer match
      "mpn": "WH1000XM5/B",
      "query": "Sony WH-1000XM5",      // search string (defaults to label)
      "map_price": 399.99,             // authoritative MAP floor
      "authorized_sellers": ["Best Buy", "Crutchfield"]
    }
  ],
  "retailers": ["target", "bestbuy", "newegg", "walmart"],
  "default_map_price": null,           // fallback floor for products with no map_price
  "infer_map": false,                  // infer an ADVISORY MAP proxy when none supplied
  "authorized_sellers": ["Best Buy"],  // run-wide list; per-product overrides it
  "max_results_per_retailer": 24,
  "use_browser_fallback": true
}

Quick path: skip products and pass search_terms: ["Sony WH-1000XM5", "Bose QC Ultra"] to monitor by name. Supply a UPC or MPN for exact matching; supply map_price for authoritative violation flags.

MAP threshold priority: per-product map_price -> run-wide default_map_price -> (if infer_map) an inferred proxy from the observed cross-retailer price distribution (manufacturer list/MSRP anchor). Inferred thresholds are advisory and clearly labelled (map_source: "inferred_*" + a _disclaimer); they are not your contractual MAP.

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Output

One dataset; record_type distinguishes rows: listing, sku_match, seller_audit, violation_summary, access_notes, fetch_error, retailer_pending, no_match.

A listing in map_monitor mode:

{
  "record_type": "listing",
  "product_query": "Sony WH-1000XM5 Headphones",
  "matched": true, "match_method": "upc", "match_confidence": 1.0,
  "retailer": "walmart", "seller": "DealZone Electronics", "seller_type": "third_party",
  "title": "Sony WH-1000XM5 Wireless Noise Cancelling Headphones - Black",
  "upc": "027242923058", "mpn": "WH1000XM5B",
  "price": 348.0, "list_price": 399.99, "availability": "in_stock",
  "map_threshold": 399.99, "map_source": "user",
  "map_violation": true, "violation_amount": 51.99, "violation_pct": 0.13,
  "violation_severity": "moderate",
  "unauthorized_seller": true, "enforcement_priority": true,
  "url": "https://www.walmart.com/ip/1872934501", "via": "browser"
}

Dataset views: overview (AI-agent / dashboard skim), violations (the enforcement worklist - below-MAP listings only), detailed (every field).

Severity grading

violation_pct = how far below MAP the price is. minor <=5%, moderate 5-15%, severe >15%. A price exactly at MAP is compliant (at_map: true). enforcement_priority: true marks a below-MAP price from an unauthorized seller - the top target.

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Pricing (pay-per-event)

Event	Price	When
listing_record	$0.004	Per normalized listing matched to your SKU.
sku_match	$0.008	Per product collapsed across retailers (non-price_scan modes).
map_violation_flag	$0.012	Per listing flagged below MAP (the premium signal).
scheduled_delta_run	$0.050	Per scheduled monitor run (new-violations digest).

A _RunBudget guard caps runaway compute and a hard record cap protects against unbounded cost; over-large inputs are rejected pre-flight and routed to a labelled demo run rather than failing.

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Monitor mode (ongoing violation alerts)

Save your config as a task and schedule it (Apify Console -> Schedules). On a scheduled run the actor computes the delta vs the prior run, emits a monitor_digest of new violations / price drops, optionally POSTs it to a Slack monitor_webhook_url, and charges one scheduled_delta_run. This is the recurring, compliance-driven workflow brands actually pay for.

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Running it

In the Apify Console: pick a mode, add your products + retailers, Start. Or via API:

apify call YOUR_USERNAME/map-price-monitor --input '{
  "mode": "map_monitor",
  "search_terms": ["Sony WH-1000XM5"],
  "retailers": ["target", "bestbuy", "newegg"],
  "default_map_price": 399.99
}'

AI agents: use the paired mcp-map-price-monitor MCP server (scan_prices, check_map_violations, match_across_retailers, audit_sellers)

• x402 (USDC on Base) and Skyfire ready.