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Brand Mention Inventories — Numeric Distribution + Keyed Dataset Comparison
x402
Brand Mention Inventories — Numeric Distribution + 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).
Computes numeric distribution statistics and performs keyed row-by-row comparison between two supplied brand mention inventory datasets (mention_count, source_count) for up to 200 rows each.
Price / call$0.01
Success—
StatusUnknown
How this service works
Brand mention inventories — Numeric distribution + Keyed dataset comparison: Numeric distribution + 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
Two analytical reports: (1) a numeric distribution summary (e.g. min, max, mean, percentiles, histogram buckets) for the selected field (mention_count or source_count) across the primary dataset; (2) a keyed row-by-row comparison between the primary dataset and the secondary (other) dataset, highlighting differences per row_id for the selected field. All computation is local — no external lookups.
Example use cases
Competitor brand share shift analysis
“I have two brand mention datasets for our top competitors — one from last quarter and one from this quarter, each with mention_count and source_count by company group. Can you run a numeric distribution report and a keyed comparison on mention_count so I can see where the biggest shifts happened?”
PR campaign impact measurement
“Before and after our press release, we tracked brand mentions across sources. Here are two datasets of up to 150 rows each with mention_count and source_count. Please compute the distribution stats and do a keyed dataset comparison on source_count to show us what changed.”
Multi-brand monitoring audit
“We need to audit our brand monitoring data quality — I have two exports from different tracking tools, both with mention_count and source_count for the same company groups and dates. Run a numeric distribution and a keyed comparison on mention_count so we can spot discrepancies.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-company-18-084?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have pre-collected brand mention inventory data in tabular form and need both a numeric distribution analysis and a keyed side-by-side comparison between two datasets in a single call. It is ideal for offline/batch analytical workflows where no live data lookup is needed, and when cost efficiency matters (both reports for $0.01 USDC). Prefer alternatives if you need live brand mention fetching, sentiment analysis, or more than 200 rows per dataset.
Side effects
- Rows array empty or missing — validation error
- More than 200 rows submitted — rejected with max items error
- Row missing required fields (row_id, company_group, date, mention_count, source_count) — schema validation failure
- Invalid date format (not YYYY-MM-DD) — pattern mismatch error
- Numeric values outside allowed range (±1 trillion) — validation error
- field enum value not 'mention_count' or 'source_count' — rejected
- Mismatched row_ids between primary and other datasets — comparison may yield sparse results or nulls
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| other | array |
Tags
x402
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