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Customer Segment Observations — IQR Outlier Flags + Secondary-Measure Weighted Mean
x402
Customer Segment Observations — IQR Outlier Flags + Secondary-Measure Weighted Mean is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-20).
Runs two local analytical reports on customer segment data: IQR-based outlier detection on account_count or revenue_amount, plus a secondary-measure weighted mean calculation.
Price / call$0.01
Success—
StatusUnknown
How this service works
Customer segment observations — IQR outlier flags + Secondary-measure weighted mean: IQR outlier flags + Secondary-measure weighted mean for supplied customer segment observations records (account_count, revenue_amount). 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 for the submitted rows: (1) IQR outlier flags identifying which rows fall outside the interquartile range for the selected measure, and (2) a secondary-measure weighted mean calculation. Both reports are computed locally from the supplied data with no external lookups.
Example use cases
Flagging revenue anomalies in segment data
“I have weekly revenue_amount observations for three company groups over the last quarter — can you run IQR outlier detection and a weighted mean on the revenue_amount field so I can spot which segment weeks had abnormal revenue?”
Account count outlier audit for BI report
“Run an IQR outlier analysis and weighted mean on these account_count records across my company groups — I need to flag any unusual spikes before I publish the monthly BI report. Here are up to 50 rows with row IDs, dates, company_group, account_count, and revenue_amount.”
Comparing segment balance across company groups
“Can you analyze this set of customer segment observations — about 80 rows with group labels, dates, account counts, and revenue amounts — and give me IQR outlier flags plus a weighted mean on account_count to see which groups are out of balance?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-company-16-177?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need both IQR-based outlier detection and a weighted mean computed together in a single paid call on customer segment data containing account_count and revenue_amount fields grouped by company. Ideal for batch statistical analysis of up to 200 segment observations without needing an external analytics platform. Best when data is already structured with row IDs, dates, and company group labels.
Side effects
- Fewer than 1 row submitted — minimum row count not met
- More than 200 rows submitted — exceeds maximum batch size
- Missing required fields (row_id, company_group, date, account_count, revenue_amount) on any row
- Invalid date format (must match YYYY-MM-DD pattern)
- Payment not provided or insufficient USDC (requires 0.01 USDC)
- Numeric values outside allowed range (-1,000,000,000,000 to 1,000,000,000,000)
- Invalid field enum value — must be 'account_count' or 'revenue_amount'
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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