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Competitor Supplied Prices — String Normalisation + Two-Measure Correlation
x402
Competitor Supplied Prices — String Normalisation + Two-Measure Correlation is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-19).
Normalises strings and computes two-measure correlation across up to 200 competitor price records (list_price, package_quantity), returning two analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Competitor supplied prices — String normalisation + Two-measure correlation: String normalisation + Two-measure correlation for supplied competitor supplied prices records (list_price, package_quantity). Up to 200 rows; 2 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 2 supplied-data reports for up to 200 rows.
Output
Two independent analytical reports: one covering string normalisation results for the supplied competitor price records, and one covering the two-measure correlation between list_price and package_quantity across up to 200 rows. Results are computed locally with no external lookups or predictions.
Example use cases
Competitor pricing correlation analysis
“I've got 80 rows of competitor price data with company groups, dates, list prices, and package quantities — can you normalise the strings and run a two-measure correlation between list_price and package_quantity to see if there's a pattern?”
Multi-brand price-quantity relationship study
“We collected competitor pricing records from three company groups over the past quarter — about 150 rows total with row IDs, dates, list prices, and package quantities. Run string normalisation and give me both analytical reports on the correlation between price and quantity.”
Spot-check competitor pricing data quality
“Here are 30 rows of raw competitor price records with row IDs, company groups like 'group-a' and 'group-b', dates, list prices, and package quantities — can you normalise the strings and compute the two-measure correlation so I can see how clean the data is and whether price tracks quantity?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-company-07-033?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have pre-collected competitor pricing records (list_price, package_quantity) and need both string normalisation and a statistical correlation between those two numeric measures in a single low-cost call. Ideal for offline batch analysis of up to 200 rows without requiring live data lookups, external predictions, or professional assessment.
Side effects
- More than 200 rows submitted — exceeds maxItems limit
- Missing required fields (row_id, company_group, date, list_price, package_quantity) on any row
- Date field does not match YYYY-MM-DD pattern
- Numeric fields exceed allowed magnitude bounds (±1,000,000,000,000)
- Empty rows array (minItems: 1 not met)
- row_id exceeds 80 character maxLength
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array |
Tags
x402
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