Jobs to Be Done
- Monitor competitor pricing and Buy Box status across marketplaces
- Track own and rival SKU rankings for priority search terms
- Audit product content and review quality across channels
- Detect out-of-stock and new-listing events in the category
- Feed listing data into repricing and merchandising tools
Common Workflows
Cross-marketplace price watch
An hourly job hits Scavio Amazon and Walmart endpoints for 20K tracked ASINs and item IDs, compares prices, ship times, and Buy Box owners against the client's catalog, and pushes repricing signals into the client's repricer with audit trails in BigQuery.
Example: scavio.amazon.product(asins) + scavio.walmart.product(ids) -> repricer.signal
Search ranking and share
For each priority category the team queries Scavio Amazon and Walmart search for the top 200 keywords daily, logs positions for own and rival SKUs, and dashboards share-of-shelf so merchandisers see exactly where they are losing placement week over week.
Example: scavio.amazon.search(category_kws) -> share_of_shelf.dashboard
Review quality audit
Every week Scavio pulls the latest reviews for 500 hero SKUs and competitor equivalents. Topic models surface complaint clusters (packaging, sizing, delivery) and feed the insights into the product team's backlog and the customer service macros library.
Example: scavio.amazon.reviews(skus) + scavio.walmart.reviews(skus) -> topics -> backlog
Pain Points Scavio Solves
- Amazon and Walmart APIs are restrictive and slow to approve
- Manual SKU checks are impossible at enterprise catalog sizes
- Repricers need fresher data than scheduled reports provide
- Losing share of shelf is only noticed after sales drop
Tools E-commerce Managers Pair With Scavio
Shopify, Amazon Seller Central, Helium 10, Zapier, Google Sheets, Tableau. 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.amazon.search('running shoes', country='us', sort='relevance')"},
)
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
Amazon
Product search with prices, ratings, and reviews
Walmart
Product search with pricing and fulfillment data
Google Shopping
Shopping results with multi-retailer pricing
Web search with knowledge graph, PAA, and AI overviews