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Customer Segment Observations — Category Frequencies + Two-Measure Correlation
x402
Customer Segment Observations — Category Frequencies + Two-Measure Correlation is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-16).
Analyzes customer segment observation records to produce two reports: category frequency distribution by company group and Pearson/Spearman correlation between account_count and revenue_amount.
Price / call$0.01
Success—
StatusUnknown
How this service works
Customer segment observations — Category frequencies + Two-measure correlation: Category frequencies + Two-measure correlation 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 structured analytical reports: (1) a frequency table showing how often each company_group category appears across the supplied rows, and (2) a correlation report quantifying the statistical relationship between account_count and revenue_amount across all records — both computed locally with no external calls.
Example use cases
Segment group frequency for sales review
“I have 80 rows of customer segment observations with company_group, date, account_count, and revenue_amount — can you tell me how frequently each company group appears in the data and whether the number of accounts correlates with the revenue they bring in?”
Correlation check between accounts and revenue
“I want to know if account_count and revenue_amount move together in my customer segment records — I have about 120 rows tagged with company_group and dates. Can you compute the correlation between those two measures and also show me the category frequency breakdown?”
Monthly segment performance pattern analysis
“We have 150 rows of monthly customer segment observations from the past year, each with a company_group, account_count, and revenue_amount. Can you analyze how often each group shows up and whether higher account counts tend to mean higher revenue?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-company-16-108?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have up to 200 customer segment observation records and need both a categorical frequency distribution by company group and a two-measure linear/rank correlation between account_count and revenue_amount in a single low-cost API call ($0.01 USDC). Prefer this over general-purpose analytics tools when you want a fast, self-contained statistical summary without sending data to a third-party ML or BI platform.
Side effects
- More than 200 rows submitted — request will be rejected or truncated
- Missing required fields (row_id, company_group, date, account_count, or revenue_amount) cause validation errors
- All account_count or revenue_amount values are null — correlation report cannot be computed
- Date strings not matching YYYY-MM-DD pattern cause schema validation failure
- Insufficient numeric variance in one measure produces degenerate or undefined correlation
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array |
Tags
x402
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