walmartecommerceapi

Walmart Seller Product Research via API

Walmart product data via API: pricing, ratings, review counts, seller info at $0.005/query. No scraping, no proxies. Cross-platform comparison with Amazon included.

8 min

Walmart seller product research via API returns structured product data -- pricing, ratings, review counts, seller info -- without scraping Walmart's JavaScript-heavy frontend. At $0.005/query, you can research 7,000 products per month on the $30 plan, covering niche research, competitor monitoring, and pricing analysis without proxy infrastructure.

What Walmart product data includes

  • Product title, price, and availability
  • Rating and review count
  • Seller name and marketplace vs first-party flag
  • Product images and category
  • Search position for keyword ranking analysis

Basic Walmart product search

Python
import requests

def walmart_search(query: str, num_results: int = 10) -> list:
    """Search Walmart products via API."""
    resp = requests.post(
        "https://api.scavio.dev/api/v1/search",
        headers={"x-api-key": "YOUR_KEY"},
        json={
            "query": query,
            "platform": "walmart",
            "num_results": num_results
        }
    )
    data = resp.json()
    return data.get("product_results", [])

# Research a product niche
products = walmart_search("air fryer large capacity")
for p in products:
    print(f"{p.get('title', 'N/A')[:60]}")
    print(f"  Price: {p.get('price', 'N/A')}")
    print(f"  Rating: {p.get('rating', 'N/A')} ({p.get('reviews_count', 0)} reviews)")
    print()

Cross-platform price comparison

Python
import requests

def compare_prices(query: str) -> dict:
    """Compare product prices across Amazon and Walmart."""
    comparison = {}

    for platform in ["amazon", "walmart"]:
        resp = requests.post(
            "https://api.scavio.dev/api/v1/search",
            headers={"x-api-key": "YOUR_KEY"},
            json={
                "query": query,
                "platform": platform,
                "num_results": 5
            }
        )
        data = resp.json()
        products = data.get("product_results", [])
        comparison[platform] = [
            {
                "title": p.get("title", "")[:50],
                "price": p.get("price", "N/A"),
                "rating": p.get("rating", "N/A")
            }
            for p in products
        ]

    return comparison

result = compare_prices("robot vacuum self emptying")
for platform, products in result.items():
    print(f"\n{platform.upper()}:")
    for p in products:
        print(f"  {p['title']} - {p['price']} ({p['rating']})")

Competitor monitoring for Walmart sellers

JavaScript
// Daily competitor price tracking
async function monitorCompetitors(keywords) {
  const report = [];

  for (const kw of keywords) {
    const resp = await fetch("https://api.scavio.dev/api/v1/search", {
      method: "POST",
      headers: {
        "x-api-key": process.env.SCAVIO_KEY,
        "Content-Type": "application/json"
      },
      body: JSON.stringify({
        query: kw,
        platform: "walmart",
        num_results: 10
      })
    });

    const data = await resp.json();
    const products = data.product_results || [];

    report.push({
      keyword: kw,
      lowestPrice: products.reduce((min, p) => {
        const price = parseFloat(p.price?.replace("$", "") || "999");
        return price < min ? price : min;
      }, 999),
      topSeller: products[0]?.title?.slice(0, 40) || "N/A",
      avgRating: products.reduce((sum, p) =>
        sum + (parseFloat(p.rating) || 0), 0
      ) / (products.length || 1)
    });
  }

  return report;
}

Use cases for Walmart sellers

  1. Niche research: find product categories with demand but low competition
  2. Price optimization: track competitor pricing daily
  3. Listing quality audit: compare your titles/ratings vs top sellers
  4. Cross-platform arbitrage: find price gaps between Amazon and Walmart

Cost for Walmart research

50 products/day research = 1,500 queries/month = $7.50 on Scavio. Daily competitor monitoring of 20 keywords = 600/month = $3.00. Total for a typical Walmart seller research workflow: under $15/month.