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Brand Mention Inventories — Trailing Mean Series + Date by Category Pivot
x402
Brand Mention Inventories — Trailing Mean Series + Date by Category Pivot 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 trailing mean time series and a date-by-category pivot table for supplied brand mention inventory records (mention_count, source_count) in a single call.
Price / call$0.01
Success—
StatusUnknown
How this service works
Brand mention inventories — Trailing mean series + Date by category pivot: Trailing mean series + Date by category pivot 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
Two independent analytical reports: (1) a trailing mean time series showing smoothed values of the chosen field (mention_count or source_count) over the specified rolling window for each company group, and (2) a date-by-category pivot table cross-tabulating dates against company groups for the selected metric. Both reports are computed locally against the supplied data with no external lookups.
Example use cases
Rolling average for brand PR campaign
“I have daily mention counts and source counts for three brand groups over the past 30 days. Can you compute a trailing mean with a 5-day window on mention_count and also pivot the data by date and company group so I can see how each brand performed each day?”
Competitive share-of-voice smoothing
“Here's my brand mention inventory for 'BrandA' and 'BrandB' from last quarter — each row has a date, company_group, mention_count, and source_count. Give me a trailing mean series using a window of 10 and a date-by-category pivot on source_count so I can compare smoothed media reach side by side.”
Monthly brand monitoring summary
“I've got 150 rows of brand mention data across four company groups for November 2026. Run a trailing mean series with window size 4 on mention_count and produce a date-by-category pivot, so I can spot trends and see which groups were most active on which days.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-company-18-152?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have pre-collected brand mention inventory data (up to 200 rows) and need both a rolling/trailing mean time series and a date-by-category pivot in one low-cost call. Ideal for offline batch analytics on brand monitoring datasets where no live data retrieval or external enrichment is needed. Best when you want two complementary analytical views (trend smoothing + cross-tabulation) for mention_count or source_count in a single request.
Side effects
- Missing required fields (row_id, company_group, date, mention_count, source_count) cause validation errors
- Date strings not matching YYYY-MM-DD pattern are rejected
- More than 200 rows submitted exceeds the row limit
- Window size outside range 2–200 is rejected
- Payment of 0.01 USDC not provided or fails x402 flow results in 402 response
- Null numeric values may affect trailing mean computation depending on handling
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| window | integer |
Tags
x402
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