Monitor Walmart's TV Category for Price Moves

Price moves show up in search before they show up in anyone's report. Thirdwatch's Walmart Scraper returns Walmart search results as clean product rows — title, price, rating, review count, and seller — with sponsored placements filtered out.

Skip the setup: Run this as a ready-to-go task on Apify — pre-loaded with the configuration from this guide.

Why monitor a category

Category monitoring means catching price cuts when they land, not in a weekly digest. A scheduled search pull gives you a dated price series per product.

Schedule the task; price and productId give you the diff keys across runs.

The Actor renders the search page and extracts the product grid, so a query or filtered URL in means priced, rated product rows out.

How does this compare to the alternatives?

Why this Actor

• Complete product rows — price, original price, rating, review count, seller, image, URL, productId.
• Sponsored placements are filtered out, so rows are organic results.
• Keyword queries or filtered search URLs — facets and sort orders carry through.
• Fresh-session retries recover automatically when a request is challenged.
• US residential routing is built in — Walmart's defenses expect it.

How to do it in 3 steps

Step 1: Configure the input

Set the inputs as shown below — queries takes the targets, free-text searches work, or paste filtered searchUrls — including category and facet URLs.

Step 2: Run the Actor

Run it from the console, the API, or the linked saved task. One dataset row is written per product.

Step 3: Use the output

Each row carries title, live price, original price, rating, review count, seller, image, product ID, and the canonical product URL.

{
  "queries": [
    "65 inch tv"
  ],
  "maxResults": 20,
  "proxyCountry": "US"
}

Each dataset row looks like:

{
  "title": "Apple MacBook Neo 13-inch A18 Pro, 8GB, 512GB - Indigo",
  "price": 849,
  "originalPrice": null,
  "currency": "USD",
  "rating": 4.5,
  "reviewCount": 455,
  "seller": "",
  "imageUrl": "https://i5.walmartimages.com/...",
  "url": "https://www.walmart.com/ip/.../1968270055",
  "productId": "1968270055",
  "sourceQuery": "laptop"
}

What to watch for

This is a browser-rendered surface — runs cost meaningfully more than pure-HTTP actors and take a couple of minutes. A small share of runs still hit a challenge after all retries; they report an error row, and rerunning the task clears it.

Related use cases

• Snapshot Walmart Laptop Prices as Data
• Harvest Ratings and Review Counts for a Category
• Measure Brand Shelf Share in a Walmart Search
• Audit First-Party vs Marketplace Sellers on Walmart
• All Thirdwatch use-case guides

Run the Walmart Scraper on Apify Store — pay per result, free to try, no credit card to test.