The Problem
ScrapingAnt charges variable credits per request (1-125 based on JS rendering and proxy type). For data available in search results -- product prices, business listings, reviews -- raw scraping with proxy management is unnecessary overhead. HTML parsing breaks when sites change layouts.
The Scavio Solution
Identify which ScrapingAnt queries target search-indexed data (Amazon products, Google business info, Walmart prices). Replace those with Scavio API calls that return the same data as structured JSON. Keep ScrapingAnt only for queries that target behind-auth or custom DOM content that is not in search results.
Before
Before the switch, the team ran 50K ScrapingAnt requests/month with JS rendering enabled (10 credits/request = 500K credits on the $49/mo plan). Scrapers broke 2-3 times per month when Amazon updated their product page layout.
After
After switching search-indexed queries to Scavio, 40K of the 50K requests move to the API at $0.005/request ($200/month). Remaining 10K requests stay on ScrapingAnt for behind-auth pages ($19/mo plan is sufficient). Total cost: $219/mo vs $49/mo, but zero maintenance and zero breakage. Net savings when accounting for 4 hours/month of scraper repair at developer rates.
Who It Is For
Teams using ScrapingAnt for data that appears in search results (product listings, business data, reviews) who want to eliminate proxy management and HTML parsing.
Key Benefits
- Flat 1 credit per request vs 10-125 variable credits
- Typed JSON eliminates HTML parsing and selector maintenance
- Zero Cloudflare or bot detection issues
- Five platforms from one API key
- Keep ScrapingAnt only for non-search-indexed data
Python Example
import requests, os
H = {'x-api-key': os.environ['SCAVIO_API_KEY']}
def get_product_data(query: str, platform: str = 'amazon') -> list:
"""Replace ScrapingAnt product scraping with structured API."""
r = requests.post('https://api.scavio.dev/api/v1/search', headers=H,
json={'platform': platform, 'query': query}, timeout=10).json()
return [{'title': o.get('title'), 'price': o.get('price'),
'rating': o.get('rating'), 'url': o.get('link')}
for o in r.get('organic_results', [])[:10]]
amazon = get_product_data('wireless headphones')
walmart = get_product_data('wireless headphones', 'walmart')
for p in amazon[:3]:
print(f"Amazon: {p['title']} - {p['price']}")JavaScript Example
const H = { 'x-api-key': process.env.SCAVIO_API_KEY, 'Content-Type': 'application/json' };
async function getProductData(query, platform = 'amazon') {
const r = await fetch('https://api.scavio.dev/api/v1/search', {
method: 'POST', headers: H,
body: JSON.stringify({ platform, query })
}).then(r => r.json());
return (r.organic_results || []).slice(0, 10).map(o => ({
title: o.title, price: o.price, rating: o.rating, url: o.link
}));
}
getProductData('wireless headphones').then(r => r.slice(0, 3).forEach(p => console.log(`${p.title}: ${p.price}`)));Platforms Used
Web search with knowledge graph, PAA, and AI overviews
Amazon
Product search with prices, ratings, and reviews
Walmart
Product search with pricing and fulfillment data