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Customer Segment Observations — Record Quality Audit, String Normalisation & Numeric Row Ordering
x402
Customer Segment Observations — Record Quality Audit, String Normalisation & Numeric Row Ordering is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-25).
Runs three local analytical reports on customer segment observation data: record quality audit, string normalisation, and numeric row ordering for account_count or revenue_amount fields.
Price / call$0.01
Success—
StatusUnknown
How this service works
Customer segment observations — Record quality audit + String normalisation + Numeric row ordering: Record quality audit + String normalisation + Numeric row ordering for supplied customer segment observations records (account_count, revenue_amount). Up to 200 rows; 3 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 3 supplied-data reports for up to 200 rows.
Output
Three independent analytical reports: (1) a record quality audit flagging issues like nulls, out-of-range values, or malformed dates across the supplied rows; (2) a string normalisation report showing cleaned/standardised versions of string fields like company_group; (3) a numeric row ordering report ranking rows by the selected numeric field (account_count or revenue_amount). All computed locally from the supplied data with no external lookups.
Example use cases
Pre-pipeline data quality check
“I've got about 50 customer segment rows with company groups, dates, account counts, and revenue amounts — can you audit them for record quality issues, normalise the string fields, and order them by revenue_amount so I can catch any problems before loading them into our warehouse?”
Monthly segment report cleanup
“Before I share the monthly segment report with leadership, can you run quality audit, string normalisation, and numeric ordering on these 120 customer segment observations? The key metrics are account_count and revenue_amount, and I want the rows ordered by account_count.”
New data feed validation
“We just received a batch of 80 customer segment records from a third-party feed — can you check their quality, normalise the company group strings, and order the rows by revenue_amount to see if the data looks reasonable?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-company-16-196?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need three bundled analytical operations — quality audit, string normalisation, and numeric ordering — on up to 200 customer segment observation rows in a single low-cost call. It is ideal for pre-processing or validating customer segment data before ingestion into downstream systems, and it operates entirely on supplied data with no external dependencies. Prefer it over general-purpose data tools when working specifically with customer segment records containing account_count and revenue_amount fields.
Side effects
- More than 200 rows submitted — request rejected with validation error
- Missing required fields (row_id, company_group, date, account_count, revenue_amount) — row-level validation error
- Invalid date format (not YYYY-MM-DD) — schema validation failure
- Numeric values outside allowed range (±1,000,000,000,000) — validation error
- Invalid field enum value (not account_count or revenue_amount) — schema error
- Empty rows array — minItems violation
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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