The Problem
Walmart product research for dropshipping, competitive analysis, and pricing intelligence requires data from Walmart's marketplace. Scraping Walmart is harder than Amazon: aggressive bot detection, frequent layout changes, and limited scraping tool support. Most commercial scraping tools focus on Amazon and neglect Walmart.
The Scavio Solution
Use Scavio's Walmart search endpoint to get structured product data: titles, prices, ratings, availability, and fulfillment options. One API call returns the same data a scraper would extract, without any scraping infrastructure.
Before
Before using the API, the e-commerce team tried 3 different Walmart scraping tools over 6 months. All broke within weeks. Manual research on Walmart.com limited product coverage to 20-30 products per analyst per day.
After
After switching to Scavio, Walmart product data is available via API at $0.005/query. The team monitors 500 Walmart products daily for $2.50/day. Data is always fresh and structured. Analyst time is redirected to strategy instead of data collection.
Who It Is For
Dropshippers researching Walmart products. E-commerce teams monitoring cross-platform pricing. Competitive intelligence analysts covering Walmart marketplace.
Key Benefits
- Structured Walmart product data without scraping infrastructure
- Prices, ratings, reviews, and availability in JSON format
- 500 products monitored daily for $2.50
- No scraping tool maintenance or proxy management
- Cross-reference with Amazon data in the same API
Python Example
import requests
API_KEY = "your_scavio_api_key"
def search_walmart(query: str) -> list[dict]:
res = requests.post(
"https://api.scavio.dev/api/v1/search",
headers={"x-api-key": API_KEY},
json={"platform": "walmart", "query": query},
timeout=15,
)
res.raise_for_status()
return [{
"title": p.get("title", ""),
"price": p.get("price"),
"rating": p.get("rating"),
"link": p.get("link", ""),
} for p in res.json().get("organic", [])[:10]]
def compare_cross_platform(query: str) -> dict:
walmart = search_walmart(query)
amazon_res = requests.post(
"https://api.scavio.dev/api/v1/search",
headers={"x-api-key": API_KEY},
json={"platform": "amazon", "query": query},
timeout=15,
)
amazon = [{"title": p.get("title", ""), "price": p.get("price")} for p in amazon_res.json().get("organic", [])[:10]]
return {"query": query, "walmart": walmart, "amazon": amazon}
results = compare_cross_platform("robot vacuum")
print(f"Walmart: {len(results['walmart'])} products, Amazon: {len(results['amazon'])} products")JavaScript Example
const API_KEY = "your_scavio_api_key";
async function searchWalmart(query) {
const res = await fetch("https://api.scavio.dev/api/v1/search", {
method: "POST",
headers: { "x-api-key": API_KEY, "content-type": "application/json" },
body: JSON.stringify({ platform: "walmart", query }),
});
return ((await res.json()).organic ?? []).slice(0, 10).map((p) => ({ title: p.title ?? "", price: p.price, rating: p.rating }));
}
const products = await searchWalmart("robot vacuum");
products.forEach((p) => console.log(`$${p.price} | ${p.rating} stars | ${p.title.slice(0, 50)}`));Platforms Used
Walmart
Product search with pricing and fulfillment data