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Returned Goods Value Recovery – Rolling Mean Report
x402
Returned Goods Value Recovery – 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 2026-10-15).
Computes a rolling mean of recovered value and returned goods cost metrics over a configurable window size, returning a smoothed time-series report for retail return recovery analysis.
Price / call$0.01
Success—
StatusUnknown
How this service works
Returned goods value recovery - Rolling mean report: Rolling mean report for Returned goods value recovery. Supplied retail figures only, up to 200 records. No platform access, live rates or order execution. One of 25 new profiles across 20 shared operations in this industry. 0.01 USDC includes one bounded rolling mean report report.
Output
A bounded rolling mean report containing smoothed series data for both recovered_value and returned_goods_cost fields across the supplied rows, computed using the specified window size. Up to 200 input rows are supported, and the output reflects moving averages at each applicable position in the series.
Example use cases
Smoothing seasonal return spikes
“I have weekly retail return data for 20 weeks with recovered values and returned goods costs — can you run a rolling mean with a window of 4 to smooth out the seasonal spikes and show me the trend?”
Monitoring recovery rate over time
“Take these 50 rows of returned merchandise data — each row has the cost of the returned goods and how much we recovered — and give me a rolling mean report with a window of 5 so I can see if our recovery rate is improving.”
Comparing return cost to recovery in bulk
“I've got 100 return transaction records from last quarter with returned_goods_cost and recovered_value for each — run a rolling mean report with window size 10 so I can spot any periods where recovery was consistently low.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ar-retail-return-recovery-rolling?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a statistically smoothed view of retail return recovery performance over a sequence of transactions or time periods, especially to reduce noise in raw return-cost-versus-recovered-value data. It is best suited for bounded datasets (up to 200 records) of retail-specific return figures where a rolling window average is the desired transformation, as opposed to real-time streaming analytics, full distribution summaries, or correlation-based analyses.
Side effects
- Fewer than 2 rows supplied — minimum row count not met
- Window size larger than number of rows — rolling window exceeds dataset length
- returned_goods_cost of zero or negative — exclusiveMinimum constraint violation
- Row count exceeds 200 — maxItems limit exceeded
- Malformed row object — missing required fields recovered_value or returned_goods_cost
- Non-numeric values in numeric fields — schema type validation failure
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| window | integer |
Tags
x402
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