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Customer Segment Observations — Record Quality Audit, String Normalisation & Category Frequencies
x402
Customer Segment Observations — Record Quality Audit, String Normalisation & Category Frequencies 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 analytical reports (record quality audit, string normalisation, and category frequencies) on up to 200 rows of customer segment observation data containing account counts and revenue amounts.
Price / call$0.01
Success—
StatusUnknown
How this service works
Customer segment observations — Record quality audit + String normalisation + Category frequencies: Record quality audit + String normalisation + Category frequencies 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 missing values, type mismatches, or out-of-range entries; (2) normalised string representations of text fields like company_group; and (3) category frequency counts showing how often each distinct category value appears across the supplied rows. All computed locally without external lookups.
Example use cases
Pre-analysis data quality check
“Before I run my revenue analysis, can you audit these customer segment records for quality issues and normalise the company_group strings? I have about 50 rows with account_count and revenue_amount values, and I want to catch any nulls, inconsistencies, or formatting problems.”
Category distribution summary for segment report
“I need to know how frequently each company group appears across my 120 customer segment observation rows — can you run a category frequency breakdown on the company_group field for me?”
Monthly segment data cleanup
“I've got this month's customer segment data — around 80 rows with date, company_group, account_count, and revenue_amount — can you run all three reports: record quality audit, string normalisation, and category frequencies, so I can clean it up before loading it into our dashboard?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-company-16-195?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need lightweight, offline data quality and profiling reports on small-to-medium customer segment datasets (up to 200 rows) without sending data to external live services. It is ideal for pre-processing pipelines where you want record quality auditing, string normalisation, and category frequency summaries bundled into a single low-cost call ($0.01 USDC for all three reports).
Side effects
- Exceeding 200 rows returns a validation error
- Missing required fields (row_id, company_group, date, account_count, revenue_amount) causes row-level rejection
- Malformed date strings not matching YYYY-MM-DD pattern trigger pattern validation errors
- Numeric values outside ±1,000,000,000,000 bounds are rejected
- Empty rows array returns an error
- Payment failure via x402 protocol prevents execution
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array |
Tags
x402
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