Pricing Strategy

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

Before Starting

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?
What makes you different/better?

3. Current Performance

What's your current conversion rate?
What's your average revenue per user (ARPU)?
What's your churn rate?
Any feedback on pricing from customers/prospects?

4. Goals

Are you optimizing for growth, revenue, or profitability?
Are you trying to move upmarket or expand downmarket?
Any pricing changes you're considering?

Pricing Fundamentals

The Three Pricing Axes

Every pricing decision involves three dimensions:

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
The perceived value vs. cost

Value-Based Pricing Framework

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

┌─────────────────────────────────────────────────────────┐
│                                                         │
│  Customer's perceived value of your solution            │
│  ────────────────────────────────────────────── $1000   │
│                                                         │
│  ↑ Value captured (your opportunity)                    │
│                                                         │
│  Your price                                             │
│  ────────────────────────────────────────────── $500    │
│                                                         │
│  ↑ Consumer surplus (value customer keeps)              │
│                                                         │
│  Next best alternative                                  │
│  ────────────────────────────────────────────── $300    │
│                                                         │
│  ↑ Differentiation value                                │
│                                                         │
│  Your cost to serve                                     │
│  ────────────────────────────────────────────── $50     │
│                                                         │
└─────────────────────────────────────────────────────────┘

Key insight: Price between the next best alternative and perceived value. Cost is a floor, not a basis.

Pricing Research Methods

Van Westendorp Price Sensitivity Meter

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

The Four Questions:

Ask each respondent:

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

How to Analyze:

Plot cumulative distributions for each question
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 Van Westendorp Analysis 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:

List 8-15 features you could include
Show respondents sets of 4-5 features at a time
Ask: "Which is MOST important? Which is LEAST important?"
Repeat across multiple sets until all features compared
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:

Utility Score	Packaging Decision
Top 20%	Include in all tiers (table stakes)
20-50%	Use to differentiate tiers
50-80%	Higher tiers only
Bottom 20%	Consider cutting or premium add-on

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

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

Metric	Best For	Example
Per user/seat	Collaboration tools	Slack, Notion
Per usage	Variable consumption	AWS, Twilio
Per feature	Modular products	HubSpot add-ons
Per contact/record	CRM, email tools	Mailchimp, HubSpot
Per transaction	Payments, marketplaces	Stripe, Shopify
Flat fee	Simple products	Basecamp
Revenue share	High-value outcomes	Affiliate platforms

Choosing Your Value Metric

Step 1: Identify how customers get value

What outcome do they care about?
What do they measure success by?
What would they pay more for?

Step 2: Map usage to value

Usage Pattern	Value Delivered	Potential Metric
More team members use it	More collaboration value	Per user
More data processed	More insights	Per record/event
More revenue generated	Direct ROI	Revenue share
More projects managed	More organization	Per project

Step 3: Test for alignment

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

Mapping Usage to Value: Framework

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

Tier Structure

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

Persona	Size	Needs	WTP	Example
Freelancer	1 person	Basic features	Low	$19/mo
Small Team	2-10	Collaboration	Medium	$49/mo
Growing Co	10-50	Scale, integrations	Higher	$149/mo
Enterprise	50+	Security, support	High	Custom

Step 2: Map features to personas

Feature	Freelancer	Small Team	Growing	Enterprise
Core features	✓	✓	✓	✓
Collaboration	—	✓	✓	✓
Integrations	—	Limited	Full	Full
API access	—	—	✓	✓
SSO/SAML	—	—	—	✓
Audit logs	—	—	—	✓
Custom contract	—	—	—	✓

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

Example: Slack

Free tier for small teams
Message history limit creates upgrade trigger
Free users invite others (viral growth)
Converts when team hits limit

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

When to Raise Prices

Signs It's Time

Market signals:

Competitors have raised prices
You're significantly cheaper than alternatives
Prospects don't flinch at price
"It's so cheap!" feedback

Business signals:

Very high conversion rates (>40%)
Very low churn (<3% monthly)
Customers using more than they pay for
Unit economics are strong

Product signals:

You've added significant value since last pricing
Product is more mature/stable
New features justify higher price

Price Increase Strategies

1. Grandfather existing customers

New price for new customers only
Existing customers keep old price
Pro: No churn risk
Con: Leaves money on table, creates complexity

2. Delayed increase for existing

Announce increase 3-6 months out
Give time to lock in old price (annual)
Pro: Fair, drives annual conversions
Con: Some churn, requires communication

3. Increase tied to value

Raise price but add features
"New Pro tier with X, Y, Z"
Pro: Justified increase
Con: Requires actual new value

4. Plan restructure

Change plans entirely
Existing customers mapped to nearest fit
Pro: Clean slate
Con: Disruptive, requires careful mapping

Communicating Price Increases

For new customers:

Just update pricing page
No announcement needed
Monitor conversion rate

For existing customers:

Subject: Updates to [Product] pricing

Hi [Name],

I'm writing to let you know about upcoming changes to [Product] pricing.

[Context: what you've added, why change is happening]

Starting [date], our pricing will change from [old] to [new].

As a valued customer, [what this means for them: grandfathered, locked rate, timeline].

[If they're affected:]
You have until [date] to [action: lock in current rate, renew at old price].

[If they're grandfathered:]
You'll continue at your current rate. No action needed.

We appreciate your continued support of [Product].

[Your name]

Pricing Page Best Practices

Above the Fold

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

Tier Presentation

Lead with the recommended tier (visual emphasis)
Show value progression clearly
Use checkmarks and limits, not paragraphs
Anchor to higher tier (show enterprise first or savings)

Common Elements

Pricing Psychology to Apply

Anchoring: Show higher-priced option first
Decoy effect: Middle tier should be obviously best value
Charm pricing: $49 vs. $50 (for value-focused)
Round pricing: $50 vs. $49 (for premium)
Annual savings: Show monthly price but offer annual discount (17-20%)

Price Testing

Methods for Testing Price

1. A/B test pricing page (risky)

Different visitors see different prices
Ethical/legal concerns
May damage trust if discovered

2. Geographic testing

Test higher prices in new markets
Different currencies/regions
Cleaner test, limited reach

3. New customer only

Raise prices for new customers
Compare conversion rates
Monitor cohort LTV

4. Sales team discretion

Test higher quotes through sales
Track close rates at different prices
Works for sales-led GTM

5. Feature-based testing

Test different packaging
Add premium tier at higher price
See adoption without changing existing

What to Measure

Conversion rate at each price point
Average revenue per user (ARPU)
Total revenue (conversion × price)
Customer lifetime value
Churn rate by price paid
Price sensitivity by segment

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

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

Validation

Tested pricing with target customers
Reviewed pricing with sales team
Validated unit economics work
Planned for price increases
Set up tracking for pricing metrics

Questions to Ask

If you need more context:

What pricing research have you done (surveys, competitor analysis)?
What's your current ARPU and conversion rate?
What's your primary value metric (what do customers pay for value)?
Who are your main pricing personas (by size, use case)?
Are you self-serve, sales-led, or hybrid?
What pricing changes are you considering?

Related Skills

page-cro: For optimizing pricing page conversion
copywriting: For pricing page copy
marketing-psychology: For pricing psychology principles
ab-test-setup: For testing pricing changes
analytics-tracking: For tracking pricing metrics

pricing-strategy