Scavio for Review Aggregation

The Problem

Product reviews are scattered across marketplaces. Aggregating and analyzing them requires scraping multiple sites, handling different formats, and managing rate limits.

How Scavio Helps

• Structured review data from Amazon and Walmart
• Ratings, review counts, and review text in JSON
• YouTube review videos for sentiment analysis
• Build automated review monitoring pipelines

Relevant Platforms

Quick Start: Python Example

Here is a quick example searching Amazon for "dyson v15 detect":

import requests

API_KEY = "your_scavio_api_key"

response = requests.post(
    "https://api.scavio.dev/api/v1/amazon/search",
    headers={
        "x-api-key": API_KEY,
        "Content-Type": "application/json",
    },
    json={"query": query, "marketplace": "us"},
)

data = response.json()
for product in data.get("products", [])[:5]:
    print(f"{product['title']} — {product.get('price', 'N/A')} ({product.get('rating', 'N/A')}⭐)")

Built for Product teams, customer success, brand managers

Scavio handles the search infrastructure — proxies, CAPTCHAs, rate limits, and anti-bot detection — so you can focus on building your review aggregation solution. The API returns structured JSON that is ready for processing, analysis, or feeding into AI agents.

Start with the free tier (500 credits/month, no credit card required) and scale to paid plans when you need higher volume.