Jobs to Be Done
- Size and validate new features by mining live search demand
- Track competitor launches across Google News, YouTube, and Amazon
- Pull review sentiment on rival products to inform roadmaps
- Measure how the market describes your product in SERPs and videos
- Package research artifacts for exec and design reviews
Common Workflows
Feature-demand validation
Before greenlighting a feature, a PM queries Scavio across Google, YouTube, and News for 30 variations of the problem statement. The resulting volumes, forum links, and creator coverage become a demand memo attached to the spec in Linear.
Example: scavio.google('how to automate expense reports') + scavio.youtube(same) -> memo.pdf
Competitor launch radar
A Slack bot pings the PM team whenever a competitor domain appears in Google News, a new product video crosses 10K views on YouTube, or a fresh SKU shows up on Amazon. Scavio powers all three checks behind a single scheduled job.
Example: scavio.google_news('site:competitor.com') + scavio.youtube(competitor) -> slack
Review sentiment rollup
Each quarter the team pulls the latest 5K Amazon and Walmart reviews across three competitor SKUs, runs them through a topic model, and ships a one-page sentiment brief with pull quotes into the quarterly planning doc.
Example: scavio.amazon.reviews(asins) -> topic_model -> qbr.doc
Pain Points Scavio Solves
- Waiting on data teams slows down roadmap decisions
- User research is expensive for fast directional calls
- Competitor moves surface in disconnected tools and tabs
- Hard to quantify market reception for feature ideas
Tools Product Managers Pair With Scavio
Linear, Notion, Figma, Productboard, Amplitude, ChatGPT. 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_news('site:competitor.com', recency='30d')"},
)
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