Solution

Track Prices Across Amazon, Walmart, and Google Shopping

Ecommerce teams need price intelligence across Amazon, Walmart, and Google Shopping, but each platform requires a separate scraper or API integration. Maintaining three scrapers me

The Problem

Ecommerce teams need price intelligence across Amazon, Walmart, and Google Shopping, but each platform requires a separate scraper or API integration. Maintaining three scrapers means three sets of proxy rotations, three HTML parsers, and three on-call rotations when layouts change. The data arrives in different formats with different field names, making cross-platform comparison a manual spreadsheet exercise. By the time the weekly comparison report is ready, the prices have already changed.

The Scavio Solution

Scavio queries Amazon, Walmart, and Google Shopping through the same endpoint with the same JSON schema. A single script fetches prices from all three platforms, normalizes them into a comparison table, and stores daily snapshots for trend analysis. The same field names (title, price, link) appear regardless of platform, so comparison logic writes once and works everywhere. At $0.005/credit, tracking 100 products daily across three platforms costs $45/mo.

Before

Before Scavio, cross-platform price tracking meant three separate scrapers, three maintenance burdens, and a weekly manual comparison spreadsheet that was outdated before it was finished.

After

After Scavio, one script tracks prices across all three platforms daily. Cross-platform comparison is automated, trends are visible in real time, and the cost is $45/mo for 100 products across three platforms.

Who It Is For

Ecommerce teams tracking competitive pricing, deal aggregators building cross-platform comparison tools, and procurement managers monitoring vendor costs across multiple retailers.

Key Benefits

  • One API endpoint for Amazon, Walmart, and Google Shopping
  • Normalized price schema eliminates manual data mapping
  • Daily automated tracking replaces weekly manual comparisons
  • Historical snapshots enable trend analysis over time
  • 100 products across 3 platforms for $45/mo

Python Example

Python
import requests
import json
from pathlib import Path
from datetime import datetime

API_KEY = "your_scavio_api_key"
PLATFORMS = ["amazon", "walmart"]

def get_prices(product: str) -> dict:
    prices = {"product": product, "checked_at": datetime.utcnow().isoformat()}
    for platform in PLATFORMS:
        res = requests.post(
            "https://api.scavio.dev/api/v1/search",
            headers={"x-api-key": API_KEY},
            json={"platform": platform, "query": product},
            timeout=15,
        )
        res.raise_for_status()
        results = res.json().get("organic", [])
        best = None
        for item in results:
            if item.get("price"):
                if best is None or item["price"] < best["price"]:
                    best = {
                        "price": item["price"],
                        "title": item.get("title", ""),
                        "link": item.get("link", ""),
                        "rating": item.get("rating"),
                    }
        prices[platform] = best
    return prices

def track_products(products: list[str]) -> list[dict]:
    results = [get_prices(p) for p in products]
    date = datetime.utcnow().strftime("%Y-%m-%d")
    Path(f"price_tracker_{date}.json").write_text(json.dumps(results, indent=2))
    return results

products = ["sony wh-1000xm5", "airpods pro 2", "samsung galaxy s25"]
tracked = track_products(products)
for item in tracked:
    print(f"\n{item['product']}:")
    for platform in PLATFORMS:
        data = item.get(platform)
        if data:
            print(f"  {platform}: ${data['price']} - {data['title'][:50]}")
        else:
            print(f"  {platform}: not found")

JavaScript Example

JavaScript
const API_KEY = "your_scavio_api_key";
const PLATFORMS = ["amazon", "walmart"];

async function getPrices(product) {
  const prices = { product, checkedAt: new Date().toISOString() };
  for (const platform of PLATFORMS) {
    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, query: product }),
    });
    if (!res.ok) throw new Error(`scavio ${res.status}`);
    const results = (await res.json()).organic ?? [];
    const withPrice = results.filter((r) => r.price).sort((a, b) => a.price - b.price);
    prices[platform] = withPrice[0] ? { price: withPrice[0].price, title: withPrice[0].title ?? "", link: withPrice[0].link ?? "" } : null;
  }
  return prices;
}

const products = ["sony wh-1000xm5", "airpods pro 2"];
for (const p of products) {
  const data = await getPrices(p);
  console.log(`\n${data.product}:`);
  for (const pl of PLATFORMS) console.log(`  ${pl}: ${data[pl] ? `$${data[pl].price}` : "not found"}`);
}

Platforms Used

Amazon

Product search with prices, ratings, and reviews

Walmart

Product search with pricing and fulfillment data

Google Shopping

Shopping results with multi-retailer pricing

Frequently Asked Questions

Ecommerce teams need price intelligence across Amazon, Walmart, and Google Shopping, but each platform requires a separate scraper or API integration. Maintaining three scrapers means three sets of proxy rotations, three HTML parsers, and three on-call rotations when layouts change. The data arrives in different formats with different field names, making cross-platform comparison a manual spreadsheet exercise. By the time the weekly comparison report is ready, the prices have already changed.

Scavio queries Amazon, Walmart, and Google Shopping through the same endpoint with the same JSON schema. A single script fetches prices from all three platforms, normalizes them into a comparison table, and stores daily snapshots for trend analysis. The same field names (title, price, link) appear regardless of platform, so comparison logic writes once and works everywhere. At $0.005/credit, tracking 100 products daily across three platforms costs $45/mo.

Ecommerce teams tracking competitive pricing, deal aggregators building cross-platform comparison tools, and procurement managers monitoring vendor costs across multiple retailers.

Yes. Scavio's free tier includes 250 credits per month with no credit card required. That is enough to validate this solution in your workflow.

Track Prices Across Amazon, Walmart, and Google Shopping

Scavio queries Amazon, Walmart, and Google Shopping through the same endpoint with the same JSON schema. A single script fetches prices from all three platforms, normalizes them in