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Days Sales Outstanding – Rolling Mean Report
x402
Days Sales Outstanding – Rolling Mean Report is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-22).
Calculates trailing full-window rolling means of Days Sales Outstanding (DSO) across an ordered series of observations, returning results with formula, units, and limitations.
Price / call$0.01
Success—
StatusUnknown
How this service works
Days sales outstanding - Rolling mean report: Calculate trailing full-window means over ordered observations, preserving invalid-row gaps. Metric: Days sales outstanding. Supplied figures only; returns JSON with formula, units and limitations. One of 50 calculators with 20 analysis modes. No live feed, financial advice or trade execution. 0.01 USDC includes one bounded rolling mean report report.
Output
A JSON object containing the rolling mean DSO values for each valid full-window position, along with the DSO formula used (average receivables / net credit sales × period days), units, gap preservation details for invalid rows, and limitations of the calculation.
Example use cases
Quarterly DSO trend smoothing
“I have 8 quarters of receivables data and want to smooth out the noise — can you run a rolling mean DSO with a window of 4 quarters? The data starts with Q1: $10,000 avg receivables, $50,000 net credit sales, 90 days; Q2: $11,000 and $52,000 over 91 days; Q3: $9,500 and $48,000 over 92 days; Q4: $12,000 and $55,000 over 90 days; Q5–Q8 mirror Q1–Q4.”
Annual DSO rolling average for AR review
“We do an annual AR review and I need the trailing 3-year rolling mean of days sales outstanding. Here are 5 years of data — year 1: $8,000 receivables, $40,000 credit sales, 365 days; year 2: $9,000 and $45,000 over 365 days; year 3: $8,500 and $42,000 over 365 days; year 4: $10,000 and $50,000 over 365 days; year 5: $9,200 and $46,000 over 365 days. Use a window of 3.”
Monthly collection efficiency analysis
“Can you compute a 6-month rolling mean DSO from my monthly figures? I have 12 months of data. Months 1–6: avg receivables $5,000–$6,000 stepping up by $200 each month, net credit sales $30,000–$35,000 stepping up $1,000/month, all over 30 days. Months 7–12 mirror months 1–6 but scaled up 10%. Use window size 6.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-finance-receivable-days-rolling?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a statistically smoothed view of Days Sales Outstanding over an ordered time series, particularly when preserving gaps from invalid rows is important. It is ideal for finance teams analyzing AR collection trends across multiple periods where point-in-time DSO is too noisy. Use it over a simple DSO calculator when you have at least 2 observations and want trailing window averaging rather than a single-period result.
Side effects
- Fewer than 2 rows provided — minimum row count not met
- Window size larger than number of rows — insufficient data for even one full window
- net_credit_sales of zero would cause division-by-zero — field requires exclusiveMinimum > 0
- Values exceeding maximum bounds (1,000,000,000,000) rejected with validation error
- Non-numeric or missing required fields cause schema validation failure
- Window larger than 200 or rows exceeding 200 items rejected
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| window | integer |
Tags
x402
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