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Customer Segment Observations — String Normalisation & Category Frequencies
x402
Customer Segment Observations — 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).
Performs string normalisation and category frequency analysis on customer segment observation records (account_count, revenue_amount) for up to 200 rows, returning two analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Customer segment observations — String normalisation + Category frequencies: String normalisation + Category frequencies 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: (1) a string normalisation report that standardizes the company_group and other string fields across the supplied rows, and (2) a category frequency report showing the distribution and counts of categorical values (such as company_group) along with summaries of numeric fields (account_count, revenue_amount) for up to 200 input rows.
Example use cases
Segment category frequency audit
“I have 50 rows of customer segment data with company_group labels that may be inconsistently named — can you normalise those strings and tell me the frequency of each category, plus break down account_count and revenue_amount distributions?”
Revenue distribution by company group
“Run a category frequency report on these 120 customer segment records — I want to see how often each company_group appears and how the revenue_amount values are distributed across those groups.”
Data quality check on segment observations
“Can you normalise the string fields and compute category frequencies for my 80-row customer segment dataset? I'm especially interested in spotting inconsistencies in the company_group field alongside the account_count values.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-company-16-024?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need both string normalisation and category frequency analysis on customer segment data (account_count, revenue_amount) in a single low-cost call. It is ideal for small-to-medium datasets (up to 200 rows) where you want two complementary local analytical reports without requiring external lookups, predictions, or live data connections. Prefer this over general-purpose analytics tools when working specifically with company-group-segmented customer observation records and cost efficiency ($0.01 per call) is a priority.
Side effects
- Exceeding 200 rows returns a validation error
- Missing required fields (row_id, company_group, date, account_count, revenue_amount) causes rejection
- Invalid date format (non-YYYY-MM-DD) triggers a pattern validation error
- Numeric values outside ±1,000,000,000,000 are rejected
- Empty rows array returns an error
- Payment failure (insufficient USDC) prevents execution
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array |
Tags
x402
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