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Tutorial

How to Build a Product Validation Agent for Dropshipping

Automated product research agent that checks Amazon, Walmart, and Google for demand signals before you source. Python tutorial.

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Two r/dropshipping posts asked how to find winning products. The answer from experienced sellers: start with a category you know, then validate demand with data. This agent automates the validation step.

Prerequisites

  • Scavio API key
  • Python 3.8+

Walkthrough

Step 1: Define validation criteria

What makes a product worth sourcing.

Python
criteria = {
    'min_amazon_rating': 4.0,
    'min_reviews': 50,
    'max_price': 50,
    'min_price': 15,
    'demand_signals': ['best seller', 'trending', 'popular'],
}

Step 2: Check Amazon

Search Amazon for the product and check metrics.

Python
import requests, os
H = {'x-api-key': os.environ['SCAVIO_API_KEY']}

def check_amazon(product_query):
    return requests.post('https://api.scavio.dev/api/v1/search',
        headers=H,
        json={'platform': 'amazon', 'query': product_query}).json()

Step 3: Check Walmart for price comparison

Cross-reference pricing on Walmart.

Python
def check_walmart(product_query):
    return requests.post('https://api.scavio.dev/api/v1/search',
        headers=H,
        json={'platform': 'walmart', 'query': product_query}).json()

Step 4: Check Google Shopping demand

Google Shopping results indicate demand signals.

Python
def check_google(product_query):
    return requests.post('https://api.scavio.dev/api/v1/search',
        headers=H,
        json={'platform': 'google', 'query': f'{product_query} buy', 'type': 'shopping'}).json()

Step 5: Score and rank products

Combine signals into a viability score.

Python
def score_product(amazon, walmart, google):
    score = 0
    if amazon.get('rating', 0) >= 4.0: score += 3
    if amazon.get('reviews_count', 0) >= 50: score += 2
    if walmart.get('results'): score += 2  # Available on Walmart too
    if google.get('shopping_results'): score += 1
    return score

Python Example

Python
# Validate 10 products: 10 × 3 platforms = 30 queries = $0.15
# One API key covers Amazon + Walmart + Google
# The agent validates; you make the sourcing decision

JavaScript Example

JavaScript
const amazon = await fetch('https://api.scavio.dev/api/v1/search', {
  method: 'POST', headers: {'x-api-key': process.env.SCAVIO_API_KEY, 'Content-Type': 'application/json'},
  body: JSON.stringify({platform: 'amazon', query: productQuery})
});

Expected Output

JSON
Product validation report: Amazon rating + reviews, Walmart pricing, Google Shopping demand signals, overall viability score.

Related Tutorials

  • How to Automate Product Research for Dropshipping with APIs

Frequently Asked Questions

Most developers complete this tutorial in 15 to 30 minutes. You will need a Scavio API key (free tier works) and a working Python or JavaScript environment.

Scavio API key. Python 3.8+. A Scavio API key gives you 50 free credits on signup.

Yes. The free tier includes 50 credits on signup, which is more than enough to complete this tutorial and prototype a working solution.

Scavio has a native LangChain package (langchain-scavio), an MCP server, and a plain REST API that works with any HTTP client. This tutorial uses the raw REST API, but you can adapt to your framework of choice.

Related Resources

Best Of

Best APIs for Product Validation Agents (2026)

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Best Of

Best API for Dropshipping Product Research in 2026

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Solution

Product Validation via Search APIs

Read more
Use Case

Walmart Seller Product Intelligence

Read more
Use Case

Dropship Product Research via API

Read more
Glossary

Walmart Product Data API Landscape (2026)

Read more

Start Building

Automated product research agent that checks Amazon, Walmart, and Google for demand signals before you source. Python tutorial.

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