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Brand Mention Inventories — Base-100 Series + Two-Measure Correlation
x402
Brand Mention Inventories — Base-100 Series + 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).
Computes a Base-100 indexed time series and two-measure correlation report for supplied brand mention inventory data (mention_count and source_count) across up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Brand mention inventories — Base-100 series + Two-measure correlation: Base-100 series + 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 two analytical reports derived from the supplied brand mention inventory rows: (1) a Base-100 indexed time series normalizing the chosen field (mention_count or source_count) relative to the specified base row, and (2) a two-measure correlation report between mention_count and source_count — all computed locally without live data lookup or external calls.
Example use cases
Normalize brand mentions across competitor groups
“I have weekly mention_count and source_count records for three brand groups over the past quarter — can you run a base-100 index starting from the first row and show me the normalized trend for mention_count alongside a correlation between the two metrics?”
Benchmark campaign lift using base-100 indexing
“Here's my brand mention data before and after our product launch campaign — rows with date, company_group, mention_count, and source_count. Index it to base-100 starting at row 0 so I can see the relative lift, and correlate mention_count with source_count.”
Compare share of voice across company groups
“I've got mention inventory records for five company groups spanning 60 dates. Can you compute a base-100 series on source_count starting from the first entry and also run a two-measure correlation between mention_count and source_count for the whole dataset?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-company-18-165?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have pre-collected brand mention inventory data (mention_count and source_count) and need both a normalized base-100 trend series and a correlation analysis delivered together in a single API call at very low cost ($0.01 USDC). It is ideal for offline or batch analytical workflows where data is already gathered and no live fetching, prediction, or external enrichment is required.
Side effects
- Input array exceeds 200 rows — request rejected
- Missing required fields (row_id, date, company_group, mention_count, source_count) cause validation failure
- Invalid date format (not YYYY-MM-DD) triggers schema error
- base_index out of range (0–199) causes computation error
- Null values in both measure columns may degrade correlation quality
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| base_index | integer |
Tags
x402
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