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Customer Segment Observations — Record Quality Audit + Exact Row Deduplication + Trailing Mean Series
x402
Customer Segment Observations — Record Quality Audit + Exact Row Deduplication + Trailing Mean Series is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-20).
Runs three analytical reports (record quality audit, exact row deduplication, and trailing mean series) on customer segment observations data containing account counts and revenue amounts, for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Customer segment observations — Record quality audit + Exact row deduplication + Trailing mean series: Record quality audit + Exact row deduplication + Trailing mean series 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, anomalies, or format issues in the supplied rows; (2) an exact row deduplication report identifying fully identical records; and (3) a trailing (rolling) mean series computed over the selected numeric field (account_count or revenue_amount) using the specified window size — all derived locally from the supplied data with no external calls.
Example use cases
Pre-pipeline data quality check
“Before I load my segment data into our warehouse, can you audit the record quality, flag any exact duplicate rows, and run a trailing mean with window 2 on revenue_amount for this batch of customer segment observations across group-a and group-b?”
Segment deduplication for reporting
“I have up to 150 rows of customer segment observations with account_count and revenue_amount — can you find any exact duplicate rows and give me a quality audit so I can clean them up before my weekly report?”
Rolling average trend analysis
“Can you compute a trailing mean series with window size 4 over account_count for my customer segment observations, and also tell me if there are any data quality or duplication issues in the dataset?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-company-16-216?utm_source=zero.xyzWhen to prefer
Use this endpoint when you need three bundled local analytics — quality audit, deduplication, and rolling mean — on customer segment time series data (account_count and revenue_amount) in a single low-cost call. It is ideal for pre-processing pipelines, data cleaning checks before reporting, or exploratory EDA on small-to-medium segment datasets (up to 200 rows). It does not make external lookups or predictions, so it's appropriate when you want deterministic, offline computation on data you already have.
Side effects
- More than 200 rows submitted — request rejected or truncated
- Missing required fields (row_id, company_group, date, account_count, revenue_amount) cause validation errors
- Invalid date format (not YYYY-MM-DD) causes parsing failure
- Window size larger than number of rows results in insufficient data for trailing mean
- Numeric values outside allowed range (-1,000,000,000,000 to 1,000,000,000,000) rejected
- Empty rows array returns error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| window | integer |
Tags
x402
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