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Brand Mention Inventories — Grouped Summary + Base-100 Index Series
x402
Brand Mention Inventories — Grouped Summary + Base-100 Index Series 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 grouped numeric summary and a Base-100 indexed time series for brand mention inventory records (mention_count, source_count) across up to 200 rows using local analytical engines.
Price / call$0.01
Success—
StatusUnknown
How this service works
Brand mention inventories — Grouped numeric summary + Base-100 series: Grouped numeric summary + Base-100 series 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 independent analytical reports: (1) a grouped numeric summary of the selected field (mention_count or source_count) broken down by company_group and date, and (2) a Base-100 index series anchored at the specified base_index row, showing relative change over time. Both reports are computed locally without external lookups.
Example use cases
Monthly brand share index by company
“I have four months of brand mention data for three competitor groups — can you produce a grouped numeric summary and a Base-100 index series for mention_count, setting row 0 as the baseline? Here are the rows: row-1, Alpha Corp, 2024-01-01, mentions=500, sources=12; row-2, Beta Inc, 2024-01-01, mentions=320, sources=8; row-3, Alpha Corp, 2024-02-01, mentions=580, sources=14; row-4, Beta Inc, 2024-02-01, mentions=290, sources=7.”
Source diversity trend analysis
“Can you run a grouped summary and Base-100 index on source_count for my brand monitoring records, starting the index at row 0? Data: row-1, group-a, 2024-03-01, mention_count=80, source_count=15; row-2, group-b, 2024-03-01, mention_count=60, source_count=9; row-3, group-a, 2024-03-08, mention_count=95, source_count=18; row-4, group-b, 2024-03-08, mention_count=70, source_count=11.”
Campaign impact baseline comparison
“I want to see how our brand mentions changed relative to our pre-campaign baseline — please generate a grouped numeric summary and Base-100 index series for mention_count using row index 2 as the base. Rows: row-1, OurBrand, 2024-05-01, mentions=200, sources=20; row-2, Competitor, 2024-05-01, mentions=180, sources=15; row-3, OurBrand, 2024-06-01, mentions=350, sources=30; row-4, Competitor, 2024-06-01, mentions=175, sources=14.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-company-18-092?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 grouped aggregate summary and a Base-100 normalized time series in a single low-cost call. It is ideal for offline/batch analytical reporting on brand tracking datasets without needing live data fetches, external API calls, or prediction services. Best suited for competitive intelligence dashboards, campaign measurement, and brand share trend analysis across company groups.
Side effects
- Fewer than 1 row submitted — minItems constraint violation
- More than 200 rows submitted — maxItems constraint violated, request rejected
- Invalid date format (not YYYY-MM-DD pattern) causes row rejection
- base_index out of range (must be 0–199 and within submitted row count)
- Null values in mention_count or source_count may affect summary completeness
- Invalid field enum value (must be 'mention_count' or 'source_count')
- row_id missing or exceeding 80 characters causes schema validation failure
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| base_index | integer |
Tags
x402
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