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Brand Mention Inventories — String Normalisation + Two-Measure Correlation
x402
Brand Mention Inventories — 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 2026-10-16).
Normalises strings and computes two-measure correlation (mention_count vs source_count) for up to 200 rows of brand mention inventory data, producing 2 independent analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Brand mention inventories — String normalisation + Two-measure correlation: String normalisation + Two-measure correlation for supplied brand mention inventories records (mention_count, source_count). 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
Returns 2 independent analytical reports covering: (1) string-normalised brand mention inventory records, and (2) a two-measure correlation analysis between mention_count and source_count across the supplied rows (up to 200). No external data is fetched; all computation is local.
Example use cases
Cross-brand mention vs source correlation
“I have 80 rows of brand mention inventory data with company groups 'Acme', 'Globex', and 'Initech', dated from 2025-01-01 to 2025-03-31, each with a mention_count and source_count. Can you normalise the strings and run a two-measure correlation to see if more sources mean more mentions, and give me 2 reports?”
Weekly brand tracking report for one group
“Here are 30 rows of weekly brand mention records for 'BrandAlpha' from 2024-06-01 to 2024-12-30, with mention_count and source_count filled in. Can you clean up the strings and correlate mention volume against source diversity, producing two separate analytical summaries?”
Multi-group competitive brand analysis
“I've got 150 rows covering four competitor brands — 'NovaCorp', 'PeakBrand', 'TerraMedia', and 'SwiftLabel' — all dated between 2025-07-01 and 2025-09-30, with mention_count and source_count per row. Please normalise the company group strings and run the two-measure correlation analysis with 2 reports.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-company-18-033?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have brand mention inventory data (mention_count + source_count) for up to 200 rows across one or more company groups and need both string normalisation and a statistical two-measure correlation in a single low-cost call. Prefer it over general-purpose analytics services when you want a lightweight, no-external-lookup, paid-per-call computation with two bundled reports at $0.01 USDC.
Side effects
- Fewer than 1 or more than 200 rows supplied — request rejected
- Missing required fields (row_id, company_group, date, mention_count, source_count) — validation error
- Date field not matching YYYY-MM-DD pattern — schema validation failure
- Numeric values outside allowed range (-1,000,000,000,000 to 1,000,000,000,000) — rejection
- All null values for mention_count or source_count — correlation cannot be computed
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array |
Tags
x402
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