Jobs to Be Done
- Track answer-engine citations across five engines daily
- Run AEO experiments with clear before and after measurement
- Report answer-engine visibility as a board-level KPI
- Identify which content structures earn citations
- Feed AEO signal into content operations and editorial calendars
Common Workflows
Daily citation sweep
Run the full keyword set through ask endpoints for ChatGPT, Perplexity, Claude, and Gemini; diff versus yesterday; alert on citation drift.
Example: scavio.ask('perplexity', q).citations -> diff -> slack
Citation-source teardown
For every cited URL, pull the page, identify structural patterns (schema, headings, answer blocks), and feed the patterns back to writers.
Example: for url in citations: teardown(url) -> writer_brief
AEO experiment framework
Push a content change, measure citation delta across engines over two weeks, and log the result as a first-class experiment in the AEO database.
Example: experiment(before, push, after=14d) -> aeo_db
Brand visibility dashboard
Vibe-coded dashboard in Lovable that shows weekly citation share per brand per engine for exec-level reporting.
Example: lovable + scavio -> aeo war room
Pain Points Scavio Solves
- No native tools for answer-engine visibility tracking
- Engines change citation behavior week to week
- No clear framework for AEO experiments
- Clients ask for AEO proof but tooling cannot produce it
Tools AEO Specialists Pair With Scavio
Ahrefs, Semrush, Clearscope, Notion, Looker Studio, Linear. Scavio returns structured JSON that fits into any of these tools.
Quick Start
import requests
response = requests.post(
"https://api.scavio.dev/api/v1/search",
headers={"x-api-key": "your_scavio_api_key"},
json={"query": "scavio.ask('chatgpt', 'best crm 2026').citations"},
)
data = response.json()
# Analyze results for your workflow
for result in data.get("organic_results", [])[:10]:
print(result["title"], "-", result["link"])Platforms You Will Use
Web search with knowledge graph, PAA, and AI overviews
Community, posts & threaded comments from any subreddit
YouTube
Video search with transcripts and metadata