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Cart Abandonment Rolling Mean Report
x402
Cart Abandonment 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 trailing rolling mean of cart abandonment rates over a supplied ordered series of retail observations using a configurable window size.
Price / call$0.01
Success—
StatusUnknown
How this service works
Cart abandonment - Rolling mean report: Rolling mean report for Cart abandonment. Supplied retail figures only. Local calculation and scenario analysis; no live inventory, account access, platform fee lookup or order execution. One of 25 profiles or calculations across 20 shared operations in this sector. 0.01 USDC includes one bounded rolling mean report deliverable.
Output
Returns a series of rolling mean cart abandonment rate values computed over the supplied ordered rows, one mean per complete window, reflecting the trailing average of (1 - completed_carts/started_carts) or equivalent abandonment metric across the specified window size.
Example use cases
Smoothing weekly cart abandonment trends
“I have 8 weeks of cart data — started and completed counts per week — and I want a rolling mean with a window of 3 to smooth out the week-to-week noise. Can you run that calculation for me?”
Seasonal retail pattern analysis
“I need to see the trailing 4-period rolling average cart abandonment across our 12 months of retail data, with started carts and completed carts supplied for each month. Can you compute that?”
Comparing smoothed abandonment across campaign windows
“We ran a 10-day promo and have daily cart figures for each day. Can you calculate the rolling mean abandonment rate using a window of 2 so I can see how the trend shifted day by day?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-sector-retail-cart-abandonment-rolling?utm_source=zero.xyzWhen to prefer
Use this endpoint when you need to smooth cart abandonment rate data over time using a configurable trailing window, particularly when raw period-to-period figures are noisy and you want trend visibility. Prefer this over single-period or batch calculations when your goal is time-series smoothing rather than individual record evaluation. Best suited for ordered retail datasets of 2–200 periods where you already have started and completed cart counts.
Side effects
- Fewer than 2 rows supplied — minimum input not met
- Window size larger than number of rows — no complete windows available
- started_carts value of zero — division by zero or invalid row rejected
- Non-numeric values in cart fields — schema validation failure
- More than 200 rows supplied — exceeds maxItems limit
- Payment not processed — x402 payment required error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| window | integer |
Tags
x402
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