Measure Brand Shelf Share in a Walmart Search

Search-result share is the digital shelf — and it's measurable. 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 measure shelf share

Shelf-share on Walmart's digital shelf means: when a buyer searches the category, whose products dominate the grid? Answering that needs the full result set with brand attribution.

A keyword pull returns the grid as rows; brand parsing from title gives the share split.

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": [
    "headphones"
  ],
  "maxResults": 40,
  "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
• Monitor Walmart's TV Category for Price Moves
• Harvest Ratings and Review Counts for a Category
• 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.