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PAL | Competitor Price & Stock Change Monitor

Pricing

from $3.50 / 1,000 completed competitor price stock delta monitors

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PAL | Competitor Price & Stock Change Monitor

PAL | Competitor Price & Stock Change Monitor

Monitor public competitor product data, track price and availability changes across runs, and flag significant changes at a configurable threshold. Export JSON/CSV; webhooks via Apify integrations.

Pricing

from $3.50 / 1,000 completed competitor price stock delta monitors

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Practical AI Lab

Practical AI Lab

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Turn public ecommerce product pages into repeatable, machine-readable price-change and stock-status intelligence.

Track a defined set of product URLs. The first run captures a baseline. Later runs with the same monitor ID compare published prices and inventory labels, showing up/down changes, percentage movement, currency shifts, or stock-status changes.

Who it's for

Ecommerce analysts, repricing software developers, marketplace operators, and AI agents building repeatable competitor intelligence workflows.

60-second quick start

  1. Enter 1-50 publicly accessible HTTPS product URLs. The pages must expose static schema.org/Product JSON-LD (not Javascript-rendered-only listings).
  2. Choose a unique monitorId for a product group. For a quick test use demo-products.
  3. Run once to receive eventType: first_seen.
  4. Run again with the same monitor ID to receive unchanged or a change event.
  5. Add the Actor to an Apify Schedule (e.g. daily) with the same inputs for ongoing checks; read each run's dataset through the Apify API or webhook.

Sample input:

{"urls":["https://scrapeme.live/shop/Pikachu/"],"monitorId":"demo-products","emitUnchanged":true,"minPriceChangePercent":5}

New: prioritize material changes. Set minPriceChangePercent (default 5%) to mark significant price movements; stock, currency and price-visibility changes also surface an alertSignal. Filter alertSignal=true in your downstream automation. This signal alone does not send any emails or notifications. For automatic notifications, set up an Apify Schedule and a webhook or integration.

Example output fields: alertSignal, alertKind, alertReason, name, sourceUrl, price, currency, availability, previousPrice, priceDelta, priceDeltaPercent, eventType, changed, summary, checkedAt.

Events: first_seen, unchanged, price_up, price_down, stock_status_changed, price_and_stock_changed, currency_changed, price_visibility_changed.

What makes this useful

  • Historical comparison built into the Actor, using an account-scoped named Apify key-value store.
  • Deterministic deltas (not unsupported AI guesses); compatible with AI agent workflows via the Apify API.
  • Public pages only. No scraping of accounts, credential collection, captcha bypass or external hosting.
  • Run limits, 2MB HTML limit, 12s fetch timeout, up to 50 pages and 20 offers per page.
  • Per-product failures reported without charging for a successful snapshot.

Pricing

Intended pay-per-event model: one product-check event per successfully checked priced product (including unchanged results). Errors and missing price are not billed. Check the live Apify price before using: this README does not assert a rate until monetization is configured. Apify may also charge a small run-start event.

Limitations and correct interpretation

  • Reports only published structured metadata and stock labels. It does not verify live cart inventory, market-wide prices or actual sales. Websites may provide stale/missing information.
  • Static HTML only; JavaScript-only and blocked sites may return no results or errors. Some sites do not permit automated extraction; users must comply with website terms and applicable laws.
  • A monitor ID is a dedicated baseline namespace. Use different IDs for different workflows. Avoid simultaneous runs using the same ID, which could race.
  • Prices are compared only when currency matches; price is not converted.
  • State is kept in Apify key-value storage; retention, costs and access follow the customer's Apify account settings.
  • Financial, repricing, and profit impacts are not guaranteed.

PAL brand — Practical AI Lab. No dependency on Render.