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Customer Segment Observations — Category Frequencies + Equal-Width Histogram
x402
Customer Segment Observations — Category Frequencies + Equal-Width Histogram 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).
Generates two local analytical reports — category frequency counts and an equal-width histogram — for customer segment observation data (account_count, revenue_amount) across up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Customer segment observations — Category frequencies + Equal-width histogram: Category frequencies + Equal-width histogram 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) category frequency counts showing how often each company_group appears in the dataset, and (2) an equal-width histogram for the chosen numeric field (account_count or revenue_amount) with the specified number of bins, including bin boundaries and record counts per bin. All computation is performed locally with no external lookups.
Example use cases
Revenue distribution across customer segments
“I have 120 rows of customer segment observations with revenue_amount and company_group fields. Can you compute a 10-bin equal-width histogram of revenue_amount so I can see how revenue is distributed across segments?”
Account count frequency breakdown by group
“I've got my quarterly customer segment data — about 80 rows each with a company_group and account_count. Can you give me category frequencies for company_group and a histogram of account_count using 5 bins?”
Segment data quality sanity check via distribution
“Before I present this to leadership, can you run a frequency and histogram analysis on my 200-row customer segment dataset using account_count as the target field and 8 bins? I want to see if the distribution looks reasonable.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-company-16-106?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need two complementary statistical views — frequency counts by category and a numeric histogram — on a single batch of customer segment records without any external data enrichment or prediction. Ideal for quick distributional sanity checks, segment reporting, or exploratory data analysis on datasets up to 200 rows. Prefer this over more complex endpoints when you only need local computation and have both categorical (company_group) and numeric (account_count or revenue_amount) fields to analyze simultaneously.
Side effects
- Rows array is empty or missing — validation error returned
- More than 200 rows supplied — request rejected with max-items error
- Invalid date format (not YYYY-MM-DD) in any row — schema validation failure
- bins value outside 1–30 range — rejected with min/max constraint error
- field value not one of 'account_count' or 'revenue_amount' — enum validation error
- Null values in numeric fields may affect histogram boundaries or bin counts
- Payment of 0.01 USDC not included or rejected — x402 payment required error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| bins | integer | |
| rows | array | |
| field | string |
Tags
x402
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