Scavio for Cross-Marketplace Product Research

The Problem

Helium 10 and Jungle Scout cover Amazon depth but miss winners on Walmart and Reddit-driven trends. Cross-platform discovery via Scavio surfaces those.

How Scavio Helps

• Cross-platform Amazon + Walmart + Google Shopping
• Reddit demand signal
• Sub-$50/mo total stack
• Daily ranked output
• LLM scoring rubric

Relevant Platforms

Quick Start: Python Example

Here is a quick example searching Google for "winning home fitness products under $50 across marketplaces":

# Google v2 is a passthrough: results sit at the top level, not under a data key.
import requests

API_KEY = "sk_live_your_key"
query = "best noise cancelling headphones 2026"

response = requests.post(
    "https://api.scavio.dev/api/v2/google",
    headers={
        "Authorization": f"Bearer {API_KEY}",
        "Content-Type": "application/json",
    },
    json={"query": query},
    timeout=60,
)
response.raise_for_status()

data = response.json()
rows = data.get("organic_results") or []
for row in rows[:5]:
    print(row.get("position"))
    print("  ", row.get("title"), row.get("link"), row.get("snippet"))

Built for Cross-platform dropshippers, multi-marketplace sellers, e-commerce VAs running daily product research

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

Start with the free tier (50 credits on signup, no credit card required) and scale to paid plans when you need higher volume.