The Problem
Generative Engine Optimization (GEO) and Answer Engine Optimization (AEO) are becoming critical as Google AI Overviews expand. But there is no standard tool for tracking whether your brand appears in AI-generated answers. Manual checking does not scale past 10 keywords, and traditional rank trackers do not capture AI Overview citations.
The Scavio Solution
Automate daily queries for target keywords with AI Overview extraction enabled. Parse the AI Overview text for brand mentions, competitor mentions, and citation URLs. Track share-of-voice in AI answers over time. Build a GEO/AEO dashboard that shows which keywords trigger AI Overviews and whether your brand is cited.
Before
Before automated tracking, a marketing team manually checked 20 keywords per week for AI Overview appearances. They missed that a competitor started appearing in AI Overviews for 8 of their core keywords. By the time they noticed, the competitor had 6 weeks of AI Overview visibility advantage.
After
After automating with Scavio, 100 keywords are checked daily. AI Overview presence, brand citations, and competitor mentions are logged to a dashboard. The team detected a competitor entering AI Overviews within 24 hours and adjusted their content strategy within the same week. 100 queries/day at $0.50 total.
Who It Is For
SEO teams, AEO/GEO strategists, and marketing leaders who need to track brand visibility in Google AI Overviews and measure generative engine optimization performance.
Key Benefits
- Daily AI Overview monitoring for 100+ keywords
- Track brand and competitor citations in AI answers
- GEO/AEO share-of-voice metrics over time
- 100 keywords tracked daily for $0.50
- Detect AI Overview changes within 24 hours
Python Example
import requests, os, json
from datetime import date
H = {'x-api-key': os.environ['SCAVIO_API_KEY']}
def check_aeo(keyword: str, brand: str) -> dict:
r = requests.post('https://api.scavio.dev/api/v1/search', headers=H,
json={'platform': 'google', 'query': keyword, 'ai_overview': True},
timeout=10).json()
aio = r.get('ai_overview', {})
aio_text = (aio or {}).get('text', '')
citations = (aio or {}).get('citations', [])
return {
'date': str(date.today()),
'keyword': keyword,
'has_ai_overview': bool(aio),
'brand_cited': brand.lower() in aio_text.lower(),
'citation_count': len(citations),
'citation_domains': [c.get('domain', '') for c in citations[:5]],
}
keywords = ['best crm software 2026', 'crm for small business']
for kw in keywords:
result = check_aeo(kw, 'Acme CRM')
cited = 'CITED' if result['brand_cited'] else 'NOT CITED'
print(f"[{cited}] {kw} | AIO: {result['has_ai_overview']} | Citations: {result['citation_count']}")JavaScript Example
const H = { 'x-api-key': process.env.SCAVIO_API_KEY, 'Content-Type': 'application/json' };
async function checkAeo(keyword, brand) {
const r = await fetch('https://api.scavio.dev/api/v1/search', {
method: 'POST', headers: H,
body: JSON.stringify({ platform: 'google', query: keyword, ai_overview: true })
}).then(r => r.json());
const aio = r.ai_overview || {};
const text = aio.text || '';
const citations = aio.citations || [];
return {
keyword, hasAiOverview: Boolean(r.ai_overview),
brandCited: text.toLowerCase().includes(brand.toLowerCase()),
citationCount: citations.length,
citationDomains: citations.slice(0, 5).map(c => c.domain || ''),
};
}
const r = await checkAeo('best crm software 2026', 'Acme CRM');
console.log(`[${r.brandCited ? 'CITED' : 'NOT CITED'}] ${r.keyword} | AIO: ${r.hasAiOverview}`);Platforms Used
Web search with knowledge graph, PAA, and AI overviews