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Price After Percent Discount – Weighted Result Mean
x402
Price After Percent Discount – Weighted Result Mean is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-18).
Computes the weighted mean of post-discount prices given a list of list prices, discount percentages, and per-row weights.
Price / call$0.01
Success—
StatusUnknown
How this service works
Price after percent discount - Weighted result mean: Weighted result mean for Price after percent discount. 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 weighted result mean deliverable.
Output
Returns a single numeric value representing the weighted arithmetic mean of the after-discount prices across all input rows, where each row's after-discount price is computed as list_price × (1 − discount_percent/100) and then weighted by the corresponding weight value.
Example use cases
Blended sale price for seasonal promotion
“We're running a promo across three SKUs with list prices of $50, $80, and $120, discounts of 10%, 15%, and 25%, and sales volumes of 200, 150, and 50 units. What's the volume-weighted average price customers actually pay after the discounts?”
Scenario analysis for discount strategy
“Compare these two discount scenarios for me: products priced at $200 and $300 with discounts of 5% and 10%, weighted equally — what's the weighted mean final price?”
Supplier cost estimate after tiered discounts
“I have five supplier items at list prices $40, $60, $90, $120, $150 with negotiated discounts of 8%, 12%, 18%, 20%, and 25%, and order weights of 3, 5, 2, 4, 1. Calculate the weighted average price I'd actually pay.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-sector-retail-discount-price-weighted-mean?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a locally computed, offline weighted mean of discounted retail prices without requiring live inventory, platform fee data, or order execution. Ideal for scenario analysis, bulk pricing estimates, or aggregating discount outcomes across product lines where custom weighting (e.g. by volume, importance, or frequency) is needed.
Side effects
- Fewer than 2 rows provided — validation error
- Weights array length does not match rows array length — schema mismatch error
- discount_percent outside 0–100 range — validation error
- list_price or weight exceeds maximum bounds (1e12) — validation error
- More than 200 rows submitted — maxItems exceeded error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| weights | array |
Tags
x402
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