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Cart Abandonment IQR Outlier Flags
x402
Cart Abandonment IQR Outlier Flags 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).
Detects statistical outliers in cart abandonment rate data using the interquartile range (IQR) method across up to 200 supplied rows of retail cart data.
Price / call$0.01
Success—
StatusUnknown
How this service works
Cart abandonment - IQR outlier flags: IQR outlier flags 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 iqr outlier flags deliverable.
Output
Returns a set of IQR-based outlier flags for each supplied row of cart data, indicating which observations fall beyond 1.5 times the interquartile range of the computed cart abandonment rates across the dataset. No live inventory, account access, or platform integration is included — purely local statistical calculation on the supplied figures.
Example use cases
Weekly abandonment anomaly detection
“Here's my weekly cart data for the past 8 weeks — started carts and completed carts for each week. Can you flag any weeks where the abandonment rate is a statistical outlier using IQR? Week 1: 500 started, 150 completed; week 2: 520 started, 160 completed; week 3: 510 started, 20 completed; week 4: 490 started, 145 completed; week 5: 505 started, 155 completed; week 6: 515 started, 158 completed; week 7: 498 started, 149 completed; week 8: 502 started, 151 completed.”
Multi-store abandonment outlier scan
“I have cart data across 10 store locations and want to know which stores have statistically abnormal cart abandonment rates — can you run an IQR outlier check? Store A: 200 started, 60 completed; Store B: 210 started, 63 completed; Store C: 195 started, 5 completed; Store D: 205 started, 61 completed; Store E: 198 started, 59 completed; Store F: 202 started, 62 completed; Store G: 207 started, 64 completed; Store H: 199 started, 58 completed; Store I: 201 started, 61 completed; Store J: 204 started, 60 completed.”
Campaign period checkout anomaly check
“We ran 5 promotions this quarter and I want to see if any promotion period had an outlier cart abandonment rate. Can you flag outliers using IQR on this data? Promo 1: 300 started, 90 completed; Promo 2: 320 started, 96 completed; Promo 3: 310 started, 93 completed; Promo 4: 295 started, 15 completed; Promo 5: 305 started, 91 completed.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-sector-retail-cart-abandonment-outliers?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need fast, local statistical outlier detection on cart abandonment rate data using the IQR method, without requiring live platform integration, inventory access, or order execution. Best suited for batch analysis of 2–200 rows of historical or scenario cart data where you want to flag which records are statistically anomalous.
Side effects
- Fewer than 2 rows supplied — minimum 2 rows required
- More than 200 rows supplied — maximum is 200
- started_carts value of 0 (excluded by exclusiveMinimum) causes validation error
- Missing required fields started_carts or completed_carts in any row
- Non-numeric values passed for started_carts or completed_carts
- Values exceeding maximum of 1,000,000,000,000 rejected
- Payment failure or insufficient USDC balance prevents execution
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array |
Tags
x402
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