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Customer Segment Observations — Numeric Distribution + Adjacent Row Changes
x402
Customer Segment Observations — Numeric Distribution + 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 2026-10-20).
Analyzes customer segment observation data (account_count, revenue_amount) by producing a numeric distribution report and an adjacent row change report for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Customer segment observations — Numeric distribution + Adjacent row changes: Numeric distribution + Adjacent row changes 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 specified field (account_count or revenue_amount): (1) a numeric distribution report summarizing the statistical spread and frequency of values, and (2) an adjacent row changes report showing delta differences between consecutive rows in the supplied dataset. Both reports are computed locally from the supplied data with no external lookups.
Example use cases
Monthly revenue trend audit by segment
“I have 120 rows of customer segment observations with company_group, date, and revenue_amount — can you run both a numeric distribution report and a row-by-row change report on the revenue_amount field so I can see how revenue shifts across consecutive records?”
Account count spread analysis for sales team
“I've got a dataset of 80 customer segment records with account_count values across different company groups and dates — give me the numeric distribution and adjacent row changes for account_count so my sales team can understand the spread and movement.”
Segment data quality check via statistical summary
“Can you analyze these 40 customer segment observation rows — each with row_id, date, company_group, account_count, and revenue_amount — and produce a numeric distribution plus adjacent row changes report for revenue_amount to spot any anomalies?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-company-16-077?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have customer segment observation data with account_count or revenue_amount fields and need both a distributional summary and a sequential row-change analysis in a single low-cost call. It is best suited for batch offline analysis of up to 200 pre-collected records rather than real-time streaming or predictive use cases. Prefer this over generic stats tools when your data is already structured with company_group, date, and numeric segment metrics.
Side effects
- More than 200 rows submitted — request will be rejected or truncated
- Missing required fields (row_id, company_group, date, account_count, revenue_amount) cause validation errors
- Invalid date format (must match YYYY-MM-DD pattern) causes schema rejection
- Field selector not in allowed enum ['account_count','revenue_amount'] causes error
- Numeric values out of the allowed range (-1e12 to 1e12) rejected
- Empty rows array (minItems:1 not met) causes failure
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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