Pricing Strategy Advisor

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name: pricing-strategy-advisor description: Turn pricing notes, margin pressure, competitor context, discount behavior, and channel constraints into a practical pricing strategy brief with objective framing, move options, test ideas, and guardrails. Use when ecommerce teams, brand operators, category managers, or consultants need pricing guidance without live competitor crawlers, ERP feeds, or analytics APIs.

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Pricing Strategy Advisor

Overview

Use this skill to structure pricing decisions when the team has partial information but still needs a clear commercial recommendation. It helps with pricing architecture, margin recovery, launch pricing, and discount discipline.

This MVP is heuristic. It does not fetch live competitor prices, cost feeds, marketplace data, or conversion dashboards. It relies on the user's supplied context and assumptions.

Trigger

Use this skill when the user wants to:

decide whether to raise, hold, narrow, or tier prices

recover margin without blindly killing conversion

tighten discount discipline or promo hygiene

design a price ladder, bundle, or good-better-best structure

prepare a pricing memo before a launch, seasonal reset, or negotiation

Example prompts

"Help me decide whether we should raise prices or cut discount depth"

"Design a better pricing ladder for our core line"

"We have competitor pressure and rising costs. What pricing moves make sense?"

"Create a pricing test plan for this product launch"

Workflow

1. Clarify the pricing objective and what business trade-off matters most. 2. Normalize the strongest signals, such as cost, conversion, competitor pressure, and discount behavior. 3. Separate structural pricing issues from temporary promo, inventory, or channel noise. 4. Recommend a short list of moves with guardrails and experiment ideas. 5. Return a markdown strategy brief with risks, metrics, and assumptions.

Inputs

The user can provide any mix of:

current and target prices, margins, or cost changes

competitor references or marketplace context

conversion, volume, AOV, or bundle behavior

promo cadence, coupon usage, or markdown history

channel constraints such as MAP, retailer parity, or marketplace conflict

inventory pressure, premium positioning, or launch goals

Outputs

Return a markdown pricing brief with:

primary pricing objective

pricing posture summary

recommended moves and trade-offs

test design ideas and guardrails

metrics to monitor and escalation notes

assumptions, confidence notes, and limits

Safety

Do not claim access to live competitor or conversion data.

Do not present price elasticity as proven unless the user supplies evidence.

Avoid auto-approving permanent price increases, channel exceptions, or MAP violations.

Keep final pricing changes human-approved.

Downgrade confidence when channel conflict or unit economics are unclear.

Best-fit Scenarios

DTC and marketplace brands reviewing price strategy quarterly or around major campaigns

operators who need a structured recommendation before changing discount or ladder logic

founders balancing growth, margin, and positioning without a full pricing stack

consultants preparing a first-pass pricing memo

Not Ideal For

real-time competitor repricing systems

heavily regulated pricing environments that require legal review

highly quantitative elasticity modeling with experimental control data

workflows that must write prices directly into commerce systems

Acceptance Criteria

Return markdown text.

Include objective, recommendation, guardrail, and monitoring sections.

Keep the advisory framing explicit.

Make trade-offs practical for operators and decision-makers.