DataForSEO covers SERP well but AI Overviews and Reddit unevenly. AEO measurement programs in 2026 need all three under one billing layer. This tutorial walks through the migration: drop-in SERP replacement, AI Overviews citation extraction, and Reddit brand-mention tracking.
Prerequisites
- Python 3.10+
- Scavio API key
- Existing DataForSEO pipeline to migrate
Walkthrough
Step 1: Map DataForSEO SERP to Scavio
One-line swap: same query in, typed JSON out.
Python
import requests, os
API_KEY = os.environ['SCAVIO_API_KEY']
def serp(q):
r = requests.post('https://api.scavio.dev/api/v1/google',
headers={'x-api-key': API_KEY},
json={'query': q, 'num_results': 100})
return r.json().get('organic_results', [])Step 2: Pull AI Overviews citations
Toggle `include_ai_overview: true` on the same call.
Python
def ao_citations(q):
r = requests.post('https://api.scavio.dev/api/v1/google',
headers={'x-api-key': API_KEY},
json={'query': q, 'include_ai_overview': True})
ao = r.json().get('ai_overview', {})
return ao.get('citations', [])Step 3: Reddit brand-mention tracking
Daily Reddit scan per brand keyword.
Python
def reddit_mentions(brand):
r = requests.post('https://api.scavio.dev/api/v1/reddit/search',
headers={'x-api-key': API_KEY},
json={'query': brand})
return r.json().get('posts', [])[:25]Step 4: Normalize across surfaces
Single row shape for SERP, AO, and Reddit.
Python
def normalize(brand, q):
rows = []
for r in serp(q): rows.append({'brand': brand, 'surface':'serp', 'url': r['link']})
for c in ao_citations(q): rows.append({'brand': brand, 'surface':'ai_overview', 'url': c})
for p in reddit_mentions(brand): rows.append({'brand': brand, 'surface':'reddit', 'url': p.get('url','')})
return rowsStep 5: Cost comparison
Replace DataForSEO bill with predictable credits.
Python
# DataForSEO: variable per-endpoint
# Scavio: $30/mo for 7,000 credits flat
# Typical 200-keyword daily snapshot: ~6,000 credits/mo
# Net: under $30/mo for most teams.Python Example
Python
import os, requests
API_KEY = os.environ['SCAVIO_API_KEY']
def snapshot(q):
r = requests.post('https://api.scavio.dev/api/v1/google',
headers={'x-api-key': API_KEY},
json={'query': q, 'include_ai_overview': True, 'num_results': 100})
return r.json()
d = snapshot('best ai agents 2026')
print('SERP:', len(d.get('organic_results',[])), 'AO citations:', len((d.get('ai_overview') or {}).get('citations',[])))JavaScript Example
JavaScript
const API_KEY = process.env.SCAVIO_API_KEY;
export async function snapshot(q) {
const r = await fetch('https://api.scavio.dev/api/v1/google', {
method: 'POST',
headers: { 'x-api-key': API_KEY, 'Content-Type': 'application/json' },
body: JSON.stringify({ query: q, include_ai_overview: true, num_results: 100 })
});
return r.json();
}Expected Output
JSON
Same SERP rows DataForSEO returned, plus AI Overviews citations as a first-class field, plus Reddit brand mentions in one credit pool. Daily 200-keyword snapshot fits under the $30/mo plan.