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Retail Replenishment Quantity - Sequential Input-Change Attribution
x402
Retail Replenishment Quantity - Sequential Input-Change Attribution is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-14).
Performs sequential (waterfall) attribution analysis showing how changes in target units and inventory position drive the replenishment quantity outcome.
Price / call$0.01
Success—
StatusUnknown
How this service works
Target replenishment quantity - Sequential input-change attribution: Sequential input-change attribution for Target replenishment quantity. 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 sequential input-change attribution deliverable.
Output
Returns a sequential (waterfall) attribution result quantifying how much each input change — target_units delta and inventory_position delta — individually contributed to the overall change in the computed replenishment quantity, based purely on the supplied before/after retail figures with no live data access.
Example use cases
Diagnosing a replenishment quantity spike
“Our replenishment order jumped unexpectedly — target units before were 150, inventory position was 80; now target units are 200 and inventory position is 90. Can you do a waterfall attribution to show which input change is responsible for most of that increase?”
Scenario planning for higher safety stock
“I'm thinking of raising my target units from 500 to 600 while my inventory position stays flat at 350. Walk me through the sequential attribution so I can see exactly how much of the replenishment quantity change is driven purely by the target unit increase.”
Post-promotion inventory reconciliation
“After our promo, target units dropped from 300 to 220 and our inventory position fell from 180 to 95. Can you run the sequential input-change attribution to break down how each of those changes contributed to the new replenishment quantity?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-sector-retail-replenishment-waterfall?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need to decompose — in sequential/waterfall order — exactly how changes in target stock levels and inventory position each contributed to a shift in replenishment quantity. It is ideal for scenario analysis, root-cause investigation of order quantity changes, and retail planning workflows where you supply your own figures and want a local, offline-style calculation with no dependency on live inventory systems or platform integrations.
Side effects
- Missing required before or after fields returns a validation error
- Non-numeric values for target_units or inventory_position cause schema rejection
- inventory_position below -1,000,000,000,000 or target_units above 1,000,000,000,000 exceed schema bounds
- Identical before and after values may return zero-attribution result
- Payment not fulfilled (x402) results in 402 response and no computation
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| after | object | |
| before | object |
Tags
x402
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