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Brand Mention Inventories — Daily Sum Series + Adjacent Row Changes
x402
Brand Mention Inventories — Daily Sum Series + Adjacent Row Changes 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).
Analyzes supplied brand mention inventory rows to produce a daily sum time series and adjacent row change report for mention_count or source_count.
Price / call$0.01
Success—
StatusUnknown
How this service works
Brand mention inventories — Daily sum series + Adjacent row changes: Daily sum series + Adjacent row changes 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 reports: (1) a daily sum series showing the aggregated total of the selected field (mention_count or source_count) per date, and (2) an adjacent row changes report showing the delta between consecutive rows for the selected field — both computed locally from the supplied data without any external lookup.
Example use cases
Daily brand mention trend analysis
“I have 150 rows of brand mention data for our three company groups across Q3 — each row has a date, company_group, mention_count, and source_count. Can you compute the daily sum series and show me the adjacent row changes for mention_count so I can see how daily totals are trending?”
Source coverage spike detection
“Here are our brand mention inventory records for the past 60 days across two groups. Run the daily sum series and adjacent row changes on source_count — I want to spot any days where the number of sources covering us jumped or dropped sharply.”
Competitor mention comparison over time
“I've compiled mention inventory rows for competitor-a and competitor-b from January through March, with mention_count and source_count per day. Generate the daily sum series and adjacent row changes for mention_count so I can compare how their mention volumes evolved week by week.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-company-18-137?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have up to 200 pre-collected brand mention inventory rows and need both a daily aggregated time series AND consecutive-row delta analysis in a single low-cost call. It is ideal for offline/batch analytical workflows where the data is already assembled and no live data fetching, external enrichment, or prediction is required.
Side effects
- Missing required fields (row_id, date, company_group) cause validation errors
- Dates not matching YYYY-MM-DD pattern are rejected
- More than 200 rows exceed the maxItems limit and are rejected
- Null values in mention_count or source_count may affect aggregation results
- Invalid field enum value (not mention_count or source_count) causes an error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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