SaaS comparison pages like 'Scavio vs SerpAPI' capture high-intent search traffic from buyers actively evaluating tools. Building them manually takes hours per page, but a template-driven approach with live pricing data from a SERP API scales to hundreds of pages automatically. Each pricing verification costs $0.005, so validating 100 comparison pages costs $0.50.
Prerequisites
- Python 3.8+
- requests library
- A Scavio API key from scavio.dev
- A list of competitor pairs to compare
Walkthrough
Step 1: Define the comparison template
Create a reusable template structure for X vs Y pages.
Python
import os, requests, json
API_KEY = os.environ['SCAVIO_API_KEY']
SH = {'x-api-key': API_KEY, 'Content-Type': 'application/json'}
def comparison_template(tool_a, tool_b):
return {
'slug': f'{tool_a.lower().replace(" ", "-")}-vs-{tool_b.lower().replace(" ", "-")}',
'title': f'{tool_a} vs {tool_b}: Which Is Better in 2026?',
'meta_title': f'{tool_a} vs {tool_b} Comparison (2026)',
'meta_description': f'Compare {tool_a} and {tool_b} side by side: pricing, features, API design, and real user feedback. Updated May 2026.',
'sections': ['quick_verdict', 'pricing_table', 'feature_comparison',
'user_feedback', 'when_to_choose_each', 'methodology']
}
template = comparison_template('Scavio', 'SerpAPI')
print(f'Page: {template["slug"]}')
print(f'Title: {template["title"]}')
print(f'Sections: {", ".join(template["sections"])}')Step 2: Fetch live pricing and feature data
Use SERP data to get current pricing and feature information.
Python
def fetch_tool_data(tool_name):
"""Get current data about a tool from search results."""
data = requests.post('https://api.scavio.dev/api/v1/search',
headers=SH, json={'query': f'{tool_name} pricing 2026', 'country_code': 'us'}).json()
organic = data.get('organic_results', [])[:3]
pricing_snippet = ''
for r in organic:
snippet = r.get('snippet', '')
if any(w in snippet.lower() for w in ['$', 'free', 'pricing', 'month', 'credit']):
pricing_snippet = snippet[:200]
break
# Reddit sentiment
reddit = requests.post('https://api.scavio.dev/api/v1/search',
headers=SH, json={'query': f'{tool_name} review', 'platform': 'reddit', 'country_code': 'us'}).json()
reddit_mentions = len(reddit.get('organic_results', []))
return {
'name': tool_name,
'pricing_snippet': pricing_snippet,
'reddit_mentions': reddit_mentions,
'top_result': organic[0].get('title', '')[:60] if organic else 'N/A'
}
for tool in ['Scavio', 'SerpAPI']:
info = fetch_tool_data(tool)
print(f'{tool}:')
print(f' Pricing: {info["pricing_snippet"][:80]}')
print(f' Reddit mentions: {info["reddit_mentions"]}')Step 3: Generate comparison content from template
Fill the template with data to produce page content.
Python
def generate_comparison(tool_a_name, tool_b_name, tool_a_data, tool_b_data):
"""Generate comparison page content from template and data."""
template = comparison_template(tool_a_name, tool_b_name)
content = {
**template,
'intro': f'{tool_a_name} and {tool_b_name} both provide search API services. This comparison uses verified pricing data and real user feedback from Reddit to help you choose.',
'pricing': {
tool_a_name: tool_a_data['pricing_snippet'],
tool_b_name: tool_b_data['pricing_snippet']
},
'user_sentiment': {
tool_a_name: f'{tool_a_data["reddit_mentions"]} Reddit discussions',
tool_b_name: f'{tool_b_data["reddit_mentions"]} Reddit discussions'
},
'last_verified': '2026-05-19'
}
return content
a_data = fetch_tool_data('Scavio')
b_data = fetch_tool_data('SerpAPI')
page = generate_comparison('Scavio', 'SerpAPI', a_data, b_data)
print(f'\nGenerated: {page["title"]}')
print(f'Slug: {page["slug"]}')
print(f'Last verified: {page["last_verified"]}')Step 4: Scale to many comparison pages
Generate comparison pages for all competitor pairs automatically.
Python
def batch_generate(tools):
"""Generate comparison pages for all pairs."""
from itertools import combinations
pairs = list(combinations(tools, 2))
pages = []
total_cost = 0
for a, b in pairs:
a_data = fetch_tool_data(a)
b_data = fetch_tool_data(b)
total_cost += 4 * 0.005 # 2 Google + 2 Reddit searches
page = generate_comparison(a, b, a_data, b_data)
pages.append(page)
print(f' Generated: {page["slug"]}')
print(f'\nGenerated {len(pages)} comparison pages')
print(f'Total cost: ${total_cost:.3f}')
print(f'Cost per page: ${total_cost/len(pages):.4f}')
# Save all pages
with open('comparison_pages.json', 'w') as f:
json.dump(pages, f, indent=2)
print(f'Saved to comparison_pages.json')
return pages
tools = ['Scavio', 'SerpAPI', 'DataForSEO', 'Serper', 'Tavily']
pages = batch_generate(tools)Python Example
Python
import os, requests
SH = {'x-api-key': os.environ['SCAVIO_API_KEY'], 'Content-Type': 'application/json'}
def vs_page(tool_a, tool_b):
for tool in [tool_a, tool_b]:
data = requests.post('https://api.scavio.dev/api/v1/search',
headers=SH, json={'query': f'{tool} pricing 2026', 'country_code': 'us'}).json()
snippet = (data.get('organic_results') or [{}])[0].get('snippet', '')[:80]
print(f'{tool}: {snippet}')
print(f'Page: {tool_a.lower()}-vs-{tool_b.lower()} | Cost: $0.010')
vs_page('Scavio', 'SerpAPI')JavaScript Example
JavaScript
const SH = { 'x-api-key': process.env.SCAVIO_API_KEY, 'Content-Type': 'application/json' };
async function vsPage(toolA, toolB) {
for (const tool of [toolA, toolB]) {
const data = await fetch('https://api.scavio.dev/api/v1/search', {
method: 'POST', headers: SH,
body: JSON.stringify({ query: `${tool} pricing 2026`, country_code: 'us' })
}).then(r => r.json());
console.log(`${tool}: ${(data.organic_results||[{}])[0]?.snippet?.slice(0,80) || 'N/A'}`);
}
console.log(`Page: ${toolA.toLowerCase()}-vs-${toolB.toLowerCase()}`);
}
vsPage('Scavio', 'SerpAPI').catch(console.error);Expected Output
JSON
Page: scavio-vs-serpapi
Title: Scavio vs SerpAPI: Which Is Better in 2026?
Sections: quick_verdict, pricing_table, feature_comparison, user_feedback, when_to_choose_each, methodology
Scavio:
Pricing: Scavio offers a free tier with 250 credits/month. Paid plans start at $30...
Reddit mentions: 8
SerpAPI:
Pricing: SerpAPI pricing starts at $25/month for 1,000 searches...
Reddit mentions: 12
Generated 10 comparison pages
Total cost: $0.200
Cost per page: $0.0200