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Brand Mention Inventories — Category Frequencies + Keyed Dataset Comparison
x402
Brand Mention Inventories — Category Frequencies + Keyed Dataset Comparison 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 brand mention inventory records to produce category-level frequency summaries and a row-keyed comparison between two supplied datasets (up to 200 rows each, two reports per call).
Price / call$0.01
Success—
StatusUnknown
How this service works
Brand mention inventories — Category frequencies + Keyed dataset comparison: Category frequencies + Keyed dataset comparison 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: (1) a category frequencies report aggregating mention_count and source_count by company_group category across the supplied rows, and (2) a keyed dataset comparison report highlighting differences between the primary and secondary datasets matched by row_id. No external data is fetched; all computation is performed locally on the supplied records.
Example use cases
Quarterly brand mention shift audit
“I have our brand mention data for Q3 and Q4, each with around 150 rows covering company_group, date, mention_count, and source_count — compare them row by row and give me a category frequency breakdown so I can see which groups grew or shrank.”
Competitive brand presence comparison
“I've pulled brand mention records for two competitor groups over the same date range, each dataset has about 80 rows with mention_count and source_count — run a category frequency report and keyed comparison so I can see where each competitor dominates.”
Monthly media coverage frequency summary
“Here are two months of brand mention inventory data for our product lines, up to 200 rows each with daily mention_count and source_count by company_group — give me the category frequency totals and a side-by-side keyed comparison of the two months.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-company-18-111?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have two pre-collected brand mention datasets (up to 200 rows each) and need both a category-level frequency breakdown and a direct row-keyed comparison in a single low-cost call ($0.01 USDC). It is ideal for offline/batch brand monitoring analysis where data is already gathered and no live lookup or external data enrichment is required. Prefer alternatives if you need real-time brand monitoring, live data fetching, predictions, or datasets larger than 200 rows.
Side effects
- Input arrays exceed 200 rows — request rejected or truncated
- 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
- row_id values not consistently keyed between 'rows' and 'other' datasets — comparison may yield unmatched rows
- Null values in mention_count or source_count — may affect aggregation results
- Empty rows array (minItems:1 not met) — request rejected
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| other | array |
Tags
x402
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