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Customer Segment Observations — Exact Row Deduplication + IQR Outlier Flags
x402
Customer Segment Observations — Exact Row Deduplication + IQR Outlier Flags 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).
Deduplicates exact rows and flags IQR-based outliers in customer segment observation records containing account_count and revenue_amount fields, producing two analytical reports for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Customer segment observations — Exact row deduplication + IQR outlier flags: Exact row deduplication + IQR outlier flags 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
Two analytical reports: (1) an exact row deduplication report identifying which rows are exact duplicates, and (2) an IQR outlier flagging report marking rows whose selected numeric field (account_count or revenue_amount) falls outside the interquartile range bounds. Both reports are generated locally without external lookups.
Example use cases
Revenue outlier detection by segment
“I have monthly customer segment data with company groups, dates, and revenue amounts — can you run IQR outlier flagging on the revenue_amount field and also deduplicate any exact duplicate rows? Here are my records: group-a on 2026-01-01 with 500 accounts and $12000 revenue, group-b on 2026-01-02 with 450 accounts and $980000 revenue, etc.”
Account count anomaly audit
“Can you check my customer segment observations for exact duplicate rows and flag any anomalous account_count values using IQR? I want to clean up this dataset before I run our quarterly analysis — I'll send you up to 150 rows with row_id, company_group, date, and account_count.”
Pre-pipeline data quality check
“Before I load this segment data into our BI tool, can you deduplicate it and flag any IQR outliers in the revenue_amount column? I've got about 80 rows across several company groups spanning Q3 2026.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-company-16-049?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have customer segment observation records with account_count and/or revenue_amount fields and need both duplicate removal and statistical outlier detection in a single low-cost call. Ideal for pre-pipeline data quality checks on datasets up to 200 rows. Prefer this over generic data quality tools when your data is specifically structured around company groups, dates, and segment-level numeric metrics.
Side effects
- Exceeding 200-row limit causes rejection
- Missing required fields (row_id, company_group, date, account_count, revenue_amount) causes validation error
- Invalid date format (not YYYY-MM-DD) causes parsing failure
- Providing fewer than 1 row causes error
- Field value outside allowed numeric range causes rejection
- IQR computation may be unreliable with very small datasets (fewer than 4 rows)
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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