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Grok Bot+18 agentsAmazon Smart Pricing Pro — Protect Margin & Sales
Make Amazon pricing decisions with true unit economics, comparable offers, inventory, ads, and controlled tests.
$9.99
Amazon Smart Pricing Pro — Protect Margin & Sales
Example session with this skill installed
Evaluate this illustrative Amazon US pricing scenario for a $29.99 product. Merchant-supplied per-unit inputs: landed cost $8.00; referral fee $4.50; fulfillment fee $5.00; storage/inbound/returns/other variable cost allowance $3.00; advertising cost allocation $2.50. The current objective is at least $6 contribution per unit after these listed costs. Inventory is healthy. Two public competitor prices are $27.99 and $31.99, but pack size, delivery, coupon, and offer comparability have not been verified. Calculate current contribution, a transparent target price floor using these fixed supplied cost amounts, compare illustrative prices $29.49 and $28.99, identify fee-sensitivity caveats, and propose a reversible one-variable test with guardrails. These figures are illustrative user inputs, not live market data. Do not claim price elasticity or recommend automatic repricing.
- Read your context and instructions
- Compiled the amazon smart pricing
Pricing Decision Brief — Illustrative Scenario
Inputs: All figures below are illustrative merchant-supplied per-unit assumptions, not live Amazon data. This simple model treats the listed fees and costs as fixed across prices; actual referral fees, taxes, fulfillment costs, promotions, and other charges may change with price or product details.
Contribution scenarios
| Price | Listed costs before ads | Ad allocation | Contribution after listed costs | Meets $6 target? |
|---|---|---|---|---|
| $29.99 current | $20.50 | $2.50 | $6.99 | Yes |
| $29.49 scenario | $20.50 | $2.50 | $6.49 | Yes, narrowly |
| $28.99 scenario | $20.50 | $2.50 | $5.99 | No, by $0.01 |
Listed costs before ads = $8.00 landed + $4.50 referral + $5.00 fulfillment + $3.00 storage/inbound/returns/other. Under these fixed inputs, a $6 contribution target implies a simple price floor of $29.00 after the $2.50 ad allocation. This is not a validated marketplace floor: recalculate percentage-based fees, taxes, fulfillment tiers, returns, discounts, and other cost changes at each candidate price.
Competition context
The $27.99 and $31.99 observations are not verified like-for-like offers because pack size, delivery, coupon, condition, and offer type are unknown. Do not use them as a direct repricing trigger. Confirm each listing and date before comparison.
Cautious test
- Validate all cost inputs and recompute contribution using current marketplace fee rules and actual product dimensions/weight.
- Confirm the competitor offer details and capture a dated baseline for price, sessions, units, conversion, ad spend, contribution, stock, promotions, and Buy Box context if relevant.
- If still appropriate, test only $29.49 for a pre-agreed window, keeping ads, coupons, inventory, and listing stable where possible.
- Maintain a $6 contribution guardrail using refreshed actual fees. Pause or roll back if contribution drops below target, stock risk changes, or unrelated conditions invalidate the comparison.
- Compare like periods and label results directional unless traffic and test design support a stronger conclusion.
Confidence: LOW. No verified fee schedule, sales history, price response, or comparable-offer evidence was supplied. These scenarios do not establish elasticity or predict sales, Buy Box, profit, or competitor response.
Connects securely to your tools. The creator never sees your data.
About this skill
Amazon Smart Pricing Pro helps sellers balance customer value, competitive context, true unit economics, inventory, advertising, promotions, and strategic position—without racing automatically to the lowest price. It first defines the product, marketplace, fulfillment model, objective, and price scope, then separates verified offers and seller data from third-party context, estimates, assumptions, hypotheses, and unknowns.
The agent builds a cost and contribution model using supported landed cost, referral and fulfillment fees, storage, inbound, returns, promotions, taxes, and advertising where available. It calculates hard and strategic price floors, compares like-for-like offers only when product, quantity, shipping, and offer conditions match, and considers conversion evidence, inventory health, lifecycle, seasonality, brand positioning, and margin goals. It distinguishes Buy Box context for private-label and shared-ASIN resale models and never invents demand elasticity, competitor prices, fees, sales, or price history.
Recommendations use transparent scenarios and reversible guardrails. Each price test includes a hypothesis, one change at a time, minimum contribution floor, monitoring window, relevant confounders, stop conditions, and rollback. Promotions and ads are included in contribution when reliable inputs exist. Observed correlation is not automatically price elasticity or causation.
Provide marketplace, ASIN/SKU, fulfillment model, current price, complete variable costs and fees, ad and promotion economics, sales/conversion history, inventory and lead time, comparable offers, and the objective. Without these inputs, the agent labels a scenario as illustrative and identifies what must be verified. It does not change prices, operate repricers, promise sales, Buy Box, ranking, conversion, profit, or competitor response, or advise deceptive or unlawful pricing.
How to use
Skills on Agensi run inside your AI agent. Copy the prompt, paste it into your agent, and it connects to Agensi and installs this skill for you. If a payment is needed, your agent shows it to you first.
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