Jobs to Be Done
- Build fast, defensible market scans for pitches and engagements
- Run benchmarking studies across multiple client categories
- Source citations and charts for board-ready decks
- Track competitor intel during transformation projects
- Package repeatable research modules across client accounts
Common Workflows
Pitch-ready market scan
Given a new RFP, the consultant runs a Scavio sprint hitting 300 keywords across Google, News, and YouTube for the target category. An LLM pipeline produces sized TAM references, top players, narrative themes, and a citation list ready for slides within a single work day.
Example: scavio.batch(rfp_kws, ['google','google_news','youtube']) -> llm.pitch_deck
Cross-client benchmarking
For engagements that compare clients against 5-10 peers, Scavio pulls SERP positions, review sentiment, and video coverage per peer. Standardized dashboards show where each client leads or trails and where the engagement should focus first.
Example: for peer in peers: scavio.google(kws) + scavio.amazon.reviews(skus) -> bench
Transformation war room
During a multi-month transformation, Scavio monitors narrative and competitor moves weekly. Changes feed a war-room dashboard tied to workstream owners so the team reacts to outside-in shifts during execution rather than at the next steering committee.
Example: scavio.google_news(themes, recency='7d') -> warroom.dashboard
Pain Points Scavio Solves
- Manual Google and YouTube research is the most expensive labor on the engagement
- Subscription databases are priced per seat and often gated
- Client-ready citations are tedious to assemble by hand
- Repeatable research IP across engagements is hard to build
Tools Consultants Pair With Scavio
PowerPoint, Excel, Tableau, Notion, ChatGPT, Miro. 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.google('hospital supply chain resilience', country='us', recency='90d')"},
)
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
Google News
News search with headlines and sources
YouTube
Video search with transcripts and metadata
Amazon
Product search with prices, ratings, and reviews
Community, posts & threaded comments from any subreddit