version: "1.0.1" name: "pricing-strategy" description: "Create a Pricing Strategy Pack (value metric, packaging, price points, conversion mechanics, rollout)."

Pricing Strategy

Scope

Covers

• Pricing strategy and price setting (new product or repricing)
• Packaging and plan design (freemium, trials, feature gating, add-ons)
• Willingness-to-pay (WTP) research plan and evidence collection
• Self-serve vs sales-led handoffs (incl. thresholds and operational constraints)
• Conversion mechanics (sampling premium features, trial/discount design)
• Rollout, migration, and measurement (guardrails + review cadence)

When to use

• “Create a pricing strategy / monetization strategy.”
• “Propose packaging and plans for freemium → paid.”
• “We need new price points and a rationale tied to value.”
• “Design a free trial / reverse trial / capped trial.”
• “Figure out when self-serve tops out and when we need sales-led.”

When NOT to use

• You need to define the customer, core use case, or value proposition first (do that before pricing)
• You only want a quick competitor price scrape (no synthesis or decision support) -> use competitive-analysis
• You need legal/tax/accounting advice (coordinate with qualified experts)
• You’re making irreversible billing changes without a rollback/migration plan
• You need to craft brand positioning or messaging strategy -> use positioning-messaging
• You need to assess whether you have product-market fit before setting prices -> use measuring-product-market-fit
• You need to structure partnership or channel deals -> use partnership-bd

Inputs

Minimum required

• Product: what it does, for whom, and the primary job-to-be-done
• Target segment(s) and buying context (B2B/B2C, who pays vs who uses)
• Current pricing (if any): plans, price points, value metric, discounts, trial
• Objective + constraints: what decision this pricing work should change, and by when
• Sales motion: self-serve only, sales-led, or hybrid; typical deal sizes (if known)
• Any evidence: conversion/funnel metrics, retention, revenue mix, win/loss notes, customer quotes, competitor references

Missing-info strategy

• Ask up to 5 questions from references/INTAKE.md.
• If answers aren’t available, proceed with explicit assumptions and label unknowns. Include a “Validation plan” section in the output.

Outputs (deliverables)

Produce a Pricing Strategy Pack in Markdown (in-chat; or as files if requested):

1) Context snapshot (goal, ICP, motion, constraints, time box) 2) Value metric + segmentation hypotheses (primary + alternates) 3) WTP evidence plan (who to talk to, what to ask, how to interpret) 4) Packaging & plans (plan table: who it’s for, limits, included value) 5) Price-point options + recommendation (ranges, rationale, discount policy) 6) Conversion mechanics plan (trial type, sampling premium value, friction reduction) 7) Rollout + instrumentation (migration steps, KPIs/guardrails, monitoring) 8) Pricing review cadence (update triggers; default 6–12 months) 9) Risks / Open questions / Next steps (always included)

Templates: references/TEMPLATES.md

Workflow (7 steps)

1) Intake + decision framing

• Inputs: User context; references/INTAKE.md.
• Actions: Confirm the decision, timeline, and who will use the output. Capture current pricing (if any), motion (self-serve vs sales-led), and constraints (billing, contracts, compliance, brand).
• Outputs: Context snapshot + “success looks like” metrics.
• Checks: A stakeholder can answer: “What decision will this pricing work change?”

2) Clarify value and who pays (segment map)

• Inputs: ICP/use case; current customers/users (if any).
• Actions: Define 1–3 primary segments, buyer vs user roles, and the core value delivered (outcomes + avoided risks). Identify switching costs and “must-have” trust requirements.
• Outputs: Segment map + value narrative per segment.
• Checks: Value is stated as outcomes (not features). Buyer and user are not conflated.

3) Choose pricing architecture (value metric + packaging)

• Inputs: Segment map; product capabilities; constraints.
• Actions: Propose 1 primary value metric (and 1–2 alternates). Design packaging: plans, limits, add-ons, and what is free vs paid. Explicitly define self-serve vs sales-led boundaries (e.g., contract size, security needs, procurement).
• Outputs: Value metric options table + packaging & plans table.
• Checks: Each plan has a clear “who it’s for” and an upgrade path tied to value.

4) Treat price as a measure of value (WTP plan)

• Inputs: Value narrative; packaging; any evidence.
• Actions: Draft a WTP evidence plan: which segments to interview, what scenarios to test, and how to triangulate price sensitivity (qual + quant). Keep hypotheses explicit; avoid “pricing by vibes”.
• Outputs: WTP plan + interview/survey prompts (as needed).
• Checks: For each plan, the price is justified by value delivered and a plan to validate WTP.

5) Design conversion mechanics (sampling + friction reduction)

• Inputs: Funnel metrics; onboarding/trial experience.
• Actions: Propose how users experience paid value before paying: sampling premium features, reverse trial/capped trial, and/or time-boxed trial. Identify monetary friction to remove (trial costs, upfront commitments) and define guardrails to protect revenue leakage.
• Outputs: Conversion mechanics plan + experiment backlog.
• Checks: Mechanics demonstrate premium value in-product; there are clear abuse controls and success metrics.

6) Recommend price points + rollout and ops plan

• Inputs: Packaging; WTP plan; constraints.
• Actions: Propose 2–3 price-point options (good/better/best), plus a recommendation with tradeoffs. Include discounting/annual plans, sales assist triggers, and a migration/rollback approach. Define a pricing review cadence (default revisit every 6–12 months, or when value changes materially).
• Outputs: Recommended price points + rollout/migration plan + review cadence.
• Checks: Recommendation is operationally feasible (billing, sales, support) and has a rollback/migration path.

7) Quality gate + finalize

• Inputs: Draft pack.
• Actions: Run references/CHECKLISTS.md and score with references/RUBRIC.md. Add Risks / Open questions / Next steps and a short validation plan (what to learn next, by when).
• Outputs: Final Pricing Strategy Pack.
• Checks: Assumptions are explicit; evidence needs are clear; the pack is ready to share.

Quality gate (required)

• Use references/CHECKLISTS.md and references/RUBRIC.md.
• Always include: Risks, Open questions, Next steps.

Examples

Example 1 (B2B SaaS, hybrid motion): “Use pricing-strategy. We sell workflow automation to mid-market ops teams. Current: $49/user/mo with low conversion. Goal: improve paid conversion and expansion. Motion: self-serve + sales assist. Output: a Pricing Strategy Pack with packaging options and a rollout plan.”

Example 2 (Freemium → paid, consumer): “Use pricing-strategy. We’re a creator tool with freemium + subscription. We want to introduce a reverse trial and improve upgrades without hurting retention. Output: pricing + trial mechanics + experiment backlog.”

Boundary example (redirect): “We need a full competitive landscape analysis with feature comparison tables and market positioning.” Response: redirect to competitive-analysis -- this request is about understanding the competitive landscape, not setting pricing. Use competitive insights as an input to pricing-strategy afterward.

Boundary example (insufficient context): “Pick a price for us with no product, customer, or market context.” Response: request minimum inputs (ICP/use case, value metric candidates, objective) and propose a WTP plan + 2-3 pricing architecture options with explicit assumptions.

Anti-patterns

Avoid these common failure modes when developing pricing strategy:

1. Cost-plus pricing -- Setting prices by adding a margin to costs instead of anchoring to customer-perceived value. Costs set the floor; value sets the ceiling. Always start with value metrics and willingness-to-pay.
2. Competitor-copy pricing -- Matching a competitor's price without understanding whether your value proposition, segment, or cost structure is comparable. Competitor prices are a reference point, not a strategy.
3. Feature-gating without value logic -- Putting features behind paywalls based on development cost or engineering effort rather than customer value perception. Gate features that unlock more value as the customer grows.
4. Ignoring the buyer/user split -- In B2B, the person who pays (buyer/procurement) and the person who uses the product are often different. Pricing must address both: usage value for the user, ROI narrative for the buyer.
5. One-and-done pricing -- Setting prices at launch and never revisiting. Pricing should be reviewed every 6-12 months or when value delivery changes materially. Always define a review cadence.