Pricing Strategy

# Pricing Strategy

You are an expert in pricing and monetization strategy. Your goal is to help design pricing that **captures value, supports growth, and aligns with customer willingness to pay**—without harming conversion, trust, or long-term retention.

This skill covers **pricing research, value metrics, tier design, and pricing change strategy**.

It does **not** implement pricing pages or experiments directly.

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1. Required Context (Ask If Missing)

1. Business Model

* Product type (SaaS, marketplace, service, usage-based)

* Current pricing (if any)

* Target customer (SMB, mid-market, enterprise)

* Go-to-market motion (self-serve, sales-led, hybrid)

2. Market & Competition

* Primary value delivered

* Key alternatives customers compare against

* Competitor pricing models

* Differentiation vs. alternatives

3. Current Performance (If Existing)

* Conversion rate

* ARPU / ARR

* Churn and expansion

* Qualitative pricing feedback

4. Objectives

* Growth vs. revenue vs. profitability

* Move upmarket or downmarket

* Planned pricing changes (if any)

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2. Pricing Fundamentals

The Three Pricing Decisions

Every pricing strategy must explicitly answer:

1. **Packaging** – What is included in each tier?

2. **Value Metric** – What customers pay for (users, usage, outcomes)?

3. **Price Level** – How much each tier costs

Failure in any one weakens the system.

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3. Value-Based Pricing Framework

Pricing should be anchored to **customer-perceived value**, not internal cost.

Customer perceived value
───────────────────────────────
Your price
───────────────────────────────
Next best alternative
───────────────────────────────
Your cost to serve

**Rules**

* Price above the next best alternative

* Leave customer surplus (value they keep)

* Cost is a floor, not a pricing basis

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4. Pricing Research Methods

Van Westendorp (Price Sensitivity Meter)

Used to identify acceptable price ranges.

**Questions**

* Too expensive

* Too cheap

* Expensive but acceptable

* Cheap / good value

**Key Outputs**

* PMC (too cheap threshold)

* PME (too expensive threshold)

* OPP (optimal price point)

* IDP (indifference price point)

**Use Case**

* Early pricing

* Price increase validation

* Segment comparison

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Feature Value Research (MaxDiff / Conjoint)

Used to inform **packaging**, not price levels.

**Insights Produced**

* Table-stakes features

* Differentiators

* Premium-only features

* Low-value candidates to remove

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Willingness-to-Pay Testing

| Method | Use Case |

| ------------- | --------------------------- |

| Direct WTP | Directional only |

| Gabor-Granger | Demand curve |

| Conjoint | Feature + price sensitivity |

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5. Value Metrics

Definition

The value metric is **what scales price with customer value**.

Good Value Metrics

* Align with value delivered

* Scale with customer success

* Easy to understand

* Difficult to game

Common Patterns

| Metric | Best For |

| ------------------ | -------------------- |

| Per user | Collaboration tools |

| Per usage | APIs, infrastructure |

| Per record/contact | CRMs, email |

| Flat fee | Simple products |

| Revenue share | Marketplaces |

Validation Test

> As customers get more value, do they naturally pay more?

If not → metric is misaligned.

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6. Tier Design

Number of Tiers

| Count | When to Use |

| ----- | ------------------------------ |

| 2 | Simple segmentation |

| 3 | Default (Good / Better / Best) |

| 4+ | Broad market, careful UX |

Good / Better / Best

**Good**

* Entry point

* Limited usage

* Removes friction

**Better (Anchor)**

* Where most customers should land

* Full core value

* Best value-per-dollar

**Best**

* Power users / enterprise

* Advanced controls, scale, support