Pricing Strategy

You are an expert in SaaS pricing and monetization strategy. Your goal is to help design pricing that captures value, drives growth, and aligns with customer willingness to pay.

Before Starting

Check for product marketing context first: If .agents/product-marketing.md exists (or .claude/product-marketing.md, or the legacy product-marketing-context.md filename, in older setups), read it before asking questions. Use that context and only ask for information not already covered or specific to this task.

Gather this context (ask if not provided):

1. Business Context

• What type of product? (SaaS, marketplace, e-commerce, service)
• What's your current pricing (if any)?
• What's your target market? (SMB, mid-market, enterprise)
• What's your go-to-market motion? (self-serve, sales-led, hybrid)

2. Value & Competition

• What's the primary value you deliver?
• What alternatives do customers consider?
• How do competitors price?

3. Current Performance

• What's your current conversion rate?
• What's your ARPU and churn rate?
• Any feedback on pricing from customers/prospects?

4. Goals

• Optimizing for growth, revenue, or profitability?
• Moving upmarket or expanding downmarket?

---

Pricing Fundamentals

The Three Pricing Axes

1. Packaging — What's included at each tier?

• Features, limits, support level
• How tiers differ from each other

2. Pricing Metric — What do you charge for?

• Per user, per usage, flat fee
• How price scales with value

3. Price Point — How much do you charge?

• The actual dollar amounts
• Perceived value vs. cost

Value-Based Pricing

Price should be based on value delivered, not cost to serve:

• Customer's perceived value — The ceiling
• Your price — Between alternatives and perceived value
• Next best alternative — The floor for differentiation
• Your cost to serve — Only a baseline, not the basis

Key insight: Price between the next best alternative and perceived value.

---

Value Metrics

What is a Value Metric?

The value metric is what you charge for—it should scale with the value customers receive.

Good value metrics:

• Align price with value delivered
• Are easy to understand
• Scale as customer grows
• Are hard to game

Common Value Metrics

Choosing Your Value Metric

Ask: "As a customer uses more of [metric], do they get more value?"

• If yes → good value metric
• If no → price doesn't align with value

---

Tier Structure Overview

Good-Better-Best Framework

Good tier (Entry): Core features, limited usage, low price Better tier (Recommended): Full features, reasonable limits, anchor price Best tier (Premium): Everything, advanced features, 2-3x Better price

Tier Differentiation

• Feature gating — Basic vs. advanced features
• Usage limits — Same features, different limits
• Support level — Email → Priority → Dedicated
• Access — API, SSO, custom branding

For detailed tier structures and persona-based packaging: See references/tier-structure.md

---

Pricing Research

Van Westendorp Method

Four questions that identify acceptable price range:

1. Too expensive (wouldn't consider)
2. Too cheap (question quality)
3. Expensive but might consider
4. A bargain

Analyze intersections to find optimal pricing zone.

MaxDiff Analysis

Identifies which features customers value most:

• Show sets of features
• Ask: Most important? Least important?
• Results inform tier packaging

For detailed research methods: See references/research-methods.md

---

When to Raise Prices

Signs It's Time

Market signals:

• Competitors have raised prices
• Prospects don't flinch at price
• "It's so cheap!" feedback

Business signals:

• Very high conversion rates (>40%)
• Very low churn (<3% monthly)
• Strong unit economics

Product signals:

• Significant value added since last pricing
• Product more mature/stable

Price Increase Strategies

1. Grandfather existing — New price for new customers only
2. Delayed increase — Announce 3-6 months out
3. Tied to value — Raise price but add features
4. Plan restructure — Change plans entirely

---

Pricing Page Best Practices

Above the Fold

• Clear tier comparison table
• Recommended tier highlighted
• Monthly/annual toggle
• Primary CTA for each tier

Common Elements

• Feature comparison table
• Who each tier is for
• FAQ section
• Annual discount callout (17-20%)
• Money-back guarantee
• Customer logos/trust signals

Pricing Psychology

• Anchoring: Show higher-priced option first
• Decoy effect: Middle tier should be best value
• Charm pricing: $49 vs. $50 (for value-focused)
• Round pricing: $50 vs. $49 (for premium)

---

Pricing Checklist

Before Setting Prices

• Defined target customer personas
• Researched competitor pricing
• Identified your value metric
• Conducted willingness-to-pay research
• Mapped features to tiers

Pricing Structure

• Chosen number of tiers
• Differentiated tiers clearly
• Set price points based on research
• Created annual discount strategy
• Planned enterprise/custom tier

---

Task-Specific Questions

1. What pricing research have you done?
2. What's your current ARPU and conversion rate?
3. What's your primary value metric?
4. Who are your main pricing personas?
5. Are you self-serve, sales-led, or hybrid?
6. What pricing changes are you considering?

---

Related Skills

• churn-prevention: For cancel flows, save offers, and reducing revenue churn
• cro: For optimizing pricing page conversion
• copywriting: For pricing page copy
• marketing-psychology: For pricing psychology principles
• ab-testing: For testing pricing changes
• revops: For deal desk processes and pipeline pricing
• sales-enablement: For proposal templates and pricing presentations

---

Supporting file: evals/evals.json

{
  "skill_name": "pricing",
  "evals": [
    {
      "id": 1,
      "prompt": "Help me figure out pricing for our new SaaS product. It's a customer support platform for e-commerce stores. We're not sure whether to charge per agent, per ticket, or flat rate. Currently thinking $49-199/month range.",
      "expected_output": "Should check for product-marketing.md first. Should apply the three pricing axes framework: packaging (what's included in each tier), pricing metric (per agent, per ticket, flat rate — evaluate each), price point ($49-199 range evaluation). Should discuss value metrics and which aligns best with value delivered (per agent is common in support, but per ticket aligns with usage). Should recommend a good-better-best tier structure. Should address pricing psychology. Should provide a specific pricing recommendation with rationale.",
      "assertions": [
        "Checks for product-marketing.md",
        "Applies three pricing axes framework",
        "Evaluates multiple pricing metrics",
        "Discusses which metric aligns with value delivered",
        "Recommends good-better-best tier structure",
        "Addresses pricing psychology",
        "Provides specific pricing recommendation with rationale"
      ],
      "files": []
    },
    {
      "id": 2,
      "prompt": "We want to raise our prices by 30%. We've been at $29/month for 2 years and we've added a lot of features. How do we do this without losing customers?",
      "expected_output": "Should apply the 'when to raise prices' and price increase strategies sections. Should recommend a strategy: grandfather existing customers (or give them a grace period), tie the increase to new value, communicate the change clearly with advance notice, consider an annual billing discount as a softening measure. Should address different approaches (immediate for new customers, delayed for existing). Should recommend specific communication strategy. Should note that some churn is expected and acceptable.",
      "assertions": [
        "Applies price increase strategies",
        "Recommends grandfathering or grace period approach",
        "Recommends tying increase to new value",
        "Provides communication strategy",
        "Addresses new vs existing customer timing",
        "Suggests annual billing as softening measure",
        "Notes some churn is expected"
      ],
      "files": []
    },
    {
      "id": 3,
      "prompt": "how do we figure out what people will actually pay? we're launching a new product and have no idea what to charge.",
      "expected_output": "Should trigger on casual phrasing. Should apply the pricing research methods: Van Westendorp price sensitivity analysis (too cheap, bargain, expensive, too expensive), MaxDiff for feature importance, competitive benchmarking. Should explain how to run each method. Should also recommend simpler approaches: talking to potential customers, analyzing competitor pricing, testing different price points. Should provide a practical pricing research plan they can execute.",
      "assertions": [
        "Triggers on casual phrasing",
        "Applies Van Westendorp price sensitivity method",
        "Applies MaxDiff for feature importance",
        "Recommends competitive benchmarking",
        "Explains how to run each method",
        "Suggests practical alternatives (customer interviews, competitive analysis)",
        "Provides executable pricing research plan"
      ],
      "files": []
    },
    {
      "id": 4,
      "prompt": "We have a Basic ($19), Pro ($49), and Enterprise (custom) plan. The Pro plan gets 70% of signups. Should we add a plan between Pro and Enterprise?",
      "expected_output": "Should apply the good-better-best tier structure framework. Should analyze the current situation: Pro capturing 70% is actually healthy, but the gap to Enterprise suggests there may be mid-market customers underserved. Should evaluate whether a 4th tier makes sense: does it address a real gap, or will it create choice paralysis? Should apply pricing psychology (Hick's Law — more options can reduce decisions). Should recommend either a 4th tier with clear differentiation or adjusting the Pro plan to better bridge the gap.",
      "assertions": [
        "Applies good-better-best tier structure",
        "Analyzes current tier performance",
        "Evaluates whether 4th tier addresses real gap",
        "Considers choice paralysis risk",
        "Applies pricing psychology (Hick's Law)",
        "Provides specific recommendation with rationale"
      ],
      "files": []
    },
    {
      "id": 5,
      "prompt": "What pricing psychology tactics should we use on our pricing page? We want the $79 plan to be the most popular.",
      "expected_output": "Should apply the pricing psychology section: anchoring (show the $79 plan next to a higher-priced plan), decoy effect (make the lower plan look less valuable), visual emphasis (highlight or 'recommend' the $79 plan), charm pricing ($79 vs $80), Rule of 100 (percentage discounts below $100, dollar discounts above), loss framing (show what lower plans miss). Should provide specific pricing page design recommendations. Should cross-reference cro for broader pricing page optimization.",
      "assertions": [
        "Applies pricing psychology tactics",
        "Applies anchoring effect",
        "Applies decoy effect or visual emphasis",
        "Applies charm pricing or Rule of 100",
        "Provides specific pricing page recommendations",
        "Cross-references cro or marketing-psychology"
      ],
      "files": []
    },
    {
      "id": 6,
      "prompt": "Our pricing page conversion rate is only 1.5%. Can you review the page and suggest improvements?",
      "expected_output": "Should recognize this is a pricing page conversion optimization task, not a pricing strategy task. Should defer to or cross-reference the cro skill, which handles pricing page conversion rate optimization including plan comparison clarity, CTA optimization, and trust signals. Pricing-strategy focuses on the actual pricing decisions (what to charge, how to package), not the page design.",
      "assertions": [
        "Recognizes this as pricing page CRO, not pricing strategy",
        "References or defers to cro skill",
        "Explains that pricing is about pricing decisions",
        "Does not attempt full page CRO audit"
      ],
      "files": []
    }
  ]
}

---

Supporting file: references/research-methods.md

Pricing Research Methods

Contents

• Van Westendorp Price Sensitivity Meter (The Four Questions, How to Analyze, Survey Tips, Sample Output)
• MaxDiff Analysis (How It Works, Example Survey Question, Analyzing Results, Using MaxDiff for Packaging)
• Willingness to Pay Surveys
• Usage-Value Correlation Analysis

Van Westendorp Price Sensitivity Meter

The Van Westendorp survey identifies the acceptable price range for your product.

The Four Questions

Ask each respondent:

1. "At what price would you consider [product] to be so expensive that you would not consider buying it?" (Too expensive)
2. "At what price would you consider [product] to be priced so low that you would question its quality?" (Too cheap)
3. "At what price would you consider [product] to be starting to get expensive, but you still might consider it?" (Expensive/high side)
4. "At what price would you consider [product] to be a bargain—a great buy for the money?" (Cheap/good value)

How to Analyze

1. Plot cumulative distributions for each question
2. Find the intersections:
   • Point of Marginal Cheapness (PMC): "Too cheap" crosses "Expensive"
   • Point of Marginal Expensiveness (PME): "Too expensive" crosses "Cheap"
   • Optimal Price Point (OPP): "Too cheap" crosses "Too expensive"
   • Indifference Price Point (IDP): "Expensive" crosses "Cheap"

The acceptable price range: PMC to PME Optimal pricing zone: Between OPP and IDP

Survey Tips

• Need 100-300 respondents for reliable data
• Segment by persona (different willingness to pay)
• Use realistic product descriptions
• Consider adding purchase intent questions

Sample Output

Price Sensitivity Analysis Results:
─────────────────────────────────
Point of Marginal Cheapness:  $29/mo
Optimal Price Point:          $49/mo
Indifference Price Point:     $59/mo
Point of Marginal Expensiveness: $79/mo

Recommended range: $49-59/mo
Current price: $39/mo (below optimal)
Opportunity: 25-50% price increase without significant demand impact

---

MaxDiff Analysis (Best-Worst Scaling)

MaxDiff identifies which features customers value most, informing packaging decisions.

How It Works

1. List 8-15 features you could include
2. Show respondents sets of 4-5 features at a time
3. Ask: "Which is MOST important? Which is LEAST important?"
4. Repeat across multiple sets until all features compared
5. Statistical analysis produces importance scores

Example Survey Question

Which feature is MOST important to you?
Which feature is LEAST important to you?

□ Unlimited projects
□ Custom branding
□ Priority support
□ API access
□ Advanced analytics

Analyzing Results

Features are ranked by utility score:

• High utility = Must-have (include in base tier)
• Medium utility = Differentiator (use for tier separation)
• Low utility = Nice-to-have (premium tier or cut)

Using MaxDiff for Packaging

---

Willingness to Pay Surveys

Direct method (simple but biased): "How much would you pay for [product]?"

Better: Gabor-Granger method: "Would you buy [product] at [$X]?" (Yes/No) Vary price across respondents to build demand curve.

Even better: Conjoint analysis: Show product bundles at different prices Respondents choose preferred option Statistical analysis reveals price sensitivity per feature

---

Usage-Value Correlation Analysis

1. Instrument usage data

Track how customers use your product:

• Feature usage frequency
• Volume metrics (users, records, API calls)
• Outcome metrics (revenue generated, time saved)

2. Correlate with customer success

• Which usage patterns predict retention?
• Which usage patterns predict expansion?
• Which customers pay the most, and why?

3. Identify value thresholds

• At what usage level do customers "get it"?
• At what usage level do they expand?
• At what usage level should price increase?

Example Analysis

Usage-Value Correlation Analysis:
─────────────────────────────────
Segment: High-LTV customers (>$10k ARR)
Average monthly active users: 15
Average projects: 8
Average integrations: 4

Segment: Churned customers
Average monthly active users: 3
Average projects: 2
Average integrations: 0

Insight: Value correlates with team adoption (users)
        and depth of use (integrations)

Recommendation: Price per user, gate integrations to higher tiers

---

Supporting file: references/tier-structure.md

Tier Structure and Packaging

Contents

• How Many Tiers?
• Good-Better-Best Framework
• Tier Differentiation Strategies
• Example Tier Structure
• Packaging for Personas (Identifying Pricing Personas, Persona-Based Packaging)
• Freemium vs. Free Trial (When to Use Freemium, When to Use Free Trial, Hybrid Approaches)
• Enterprise Pricing (When to Add Custom Pricing, Enterprise Tier Elements, Enterprise Pricing Strategies)

How Many Tiers?

2 tiers: Simple, clear choice

• Works for: Clear SMB vs. Enterprise split
• Risk: May leave money on table

3 tiers: Industry standard

• Good tier = Entry point
• Better tier = Recommended (anchor to best)
• Best tier = High-value customers

4+ tiers: More granularity

• Works for: Wide range of customer sizes
• Risk: Decision paralysis, complexity

---

Good-Better-Best Framework

Good tier (Entry):

• Purpose: Remove barriers to entry
• Includes: Core features, limited usage
• Price: Low, accessible
• Target: Small teams, try before you buy

Better tier (Recommended):

• Purpose: Where most customers land
• Includes: Full features, reasonable limits
• Price: Your "anchor" price
• Target: Growing teams, serious users

Best tier (Premium):

• Purpose: Capture high-value customers
• Includes: Everything, advanced features, higher limits
• Price: Premium (often 2-3x "Better")
• Target: Larger teams, power users, enterprises

---

Tier Differentiation Strategies

Feature gating:

• Basic features in all tiers
• Advanced features in higher tiers
• Works when features have clear value differences

Usage limits:

• Same features, different limits
• More users, storage, API calls at higher tiers
• Works when value scales with usage

Support level:

• Email support → Priority support → Dedicated success
• Works for products with implementation complexity

Access and customization:

• API access, SSO, custom branding
• Works for enterprise differentiation

---

Example Tier Structure

┌────────────────┬─────────────────┬─────────────────┬─────────────────┐
│                │ Starter         │ Pro             │ Business        │
│                │ $29/mo          │ $79/mo          │ $199/mo         │
├────────────────┼─────────────────┼─────────────────┼─────────────────┤
│ Users          │ Up to 5         │ Up to 20        │ Unlimited       │
│ Projects       │ 10              │ Unlimited       │ Unlimited       │
│ Storage        │ 5 GB            │ 50 GB           │ 500 GB          │
│ Integrations   │ 3               │ 10              │ Unlimited       │
│ Analytics      │ Basic           │ Advanced        │ Custom          │
│ Support        │ Email           │ Priority        │ Dedicated       │
│ API Access     │ ✗               │ ✓               │ ✓               │
│ SSO            │ ✗               │ ✗               │ ✓               │
│ Audit logs     │ ✗               │ ✗               │ ✓               │
└────────────────┴─────────────────┴─────────────────┴─────────────────┘

---

Packaging for Personas

Identifying Pricing Personas

Different customers have different:

• Willingness to pay
• Feature needs
• Buying processes
• Value perception

Segment by:

• Company size (solopreneur → SMB → enterprise)
• Use case (marketing vs. sales vs. support)
• Sophistication (beginner → power user)
• Industry (different budget norms)

Persona-Based Packaging

Step 1: Define personas

Step 2: Map features to personas

Step 3: Price to value for each persona

• Research willingness to pay per segment
• Set prices that capture value without blocking adoption
• Consider segment-specific landing pages

---

Freemium vs. Free Trial

When to Use Freemium

Freemium works when:

• Product has viral/network effects
• Free users provide value (content, data, referrals)
• Large market where % conversion drives volume
• Low marginal cost to serve free users
• Clear feature/usage limits for upgrade trigger

Freemium risks:

• Free users may never convert
• Devalues product perception
• Support costs for non-paying users
• Harder to raise prices later

When to Use Free Trial

Free trial works when:

• Product needs time to demonstrate value
• Onboarding/setup investment required
• B2B with buying committees
• Higher price points
• Product is "sticky" once configured

Trial best practices:

• 7-14 days for simple products
• 14-30 days for complex products
• Full access (not feature-limited)
• Clear countdown and reminders
• Credit card optional vs. required trade-off

Credit card upfront:

• Higher trial-to-paid conversion (40-50% vs. 15-25%)
• Lower trial volume
• Better qualified leads

Hybrid Approaches

Freemium + Trial:

• Free tier with limited features
• Trial of premium features
• Example: Zoom (free 40-min, trial of Pro)

Reverse trial:

• Start with full access
• After trial, downgrade to free tier
• Example: See premium value, live with limitations until ready

---

Enterprise Pricing

When to Add Custom Pricing

Add "Contact Sales" when:

• Deal sizes exceed $10k+ ARR
• Customers need custom contracts
• Implementation/onboarding required
• Security/compliance requirements
• Procurement processes involved

Enterprise Tier Elements

Table stakes:

• SSO/SAML
• Audit logs
• Admin controls
• Uptime SLA
• Security certifications

Value-adds:

• Dedicated support/success
• Custom onboarding
• Training sessions
• Custom integrations
• Priority roadmap input

Enterprise Pricing Strategies

Per-seat at scale:

• Volume discounts for large teams
• Example: $15/user (standard) → $10/user (100+)

Platform fee + usage:

• Base fee for access
• Usage-based above thresholds
• Example: $500/mo base + $0.01 per API call

Value-based contracts:

• Price tied to customer's revenue/outcomes
• Example: % of transactions, revenue share