Pricing Strategy: Models That Maximize Revenue

Pricing is the fastest lever to increase revenue. You can hire more sales reps, optimize your funnel, or launch new features. Or you can change a number on your pricing page and see 20-40% revenue growth in 90 days.

Most startups underprice. They anchor on competitor pricing, fear customer pushback, or simply guess. The result? Millions in lost revenue and a broken unit economics model.

This guide gives you the exact frameworks, formulas, and tactics we use to optimize pricing for 150+ SaaS companies. From your first pricing decision through enterprise expansion, you'll know exactly how to capture the value you create.

The Four Pricing Models

Every pricing strategy starts with a model. Choose based on your market, product, and customer sophistication.

Model 1: Cost-Plus Pricing

Add a markup to your costs. Simple, but dangerously limiting.

Formula:

Price = Cost + (Cost × Markup %)

When It Works:

Commodity products with thin margins
Markets with intense price competition
Early validation before value-based pricing

The Problem: Cost-plus ignores customer value. You leave money on the table when customers would pay more, and you lose deals when costs exceed perceived value.

Example: A cloud storage company priced at cost-plus: $0.023/GB (AWS cost) + 30% = $0.030/GB. They captured $2M ARR but discovered enterprise customers valued their security features at $0.08/GB. Switching to value-based pricing increased ARR to $6M with the same customer count.

Model 2: Value-Based Pricing

Price according to the economic value you create for customers. This is the gold standard for SaaS.

Formula:

Price = Customer Value Created × Capture Rate (10-30%)

Implementation Steps:

Quantify Customer Value
- Time saved × Hourly rate
- Revenue increase × Margin
- Risk reduction × Cost of failure
- Efficiency gains × Scale
Calculate ROI
```
ROI = (Value Created - Price) / Price × 100
```
Target: 300-500% ROI for enterprise, 500-1000% for SMB
Set Capture Rate
- Enterprise: 20-30% of value created
- Mid-market: 15-20%
- SMB: 10-15%

Real Example: Gong.io priced based on conversation intelligence value. They calculated that sales teams using Gong closed 20% more deals. For a team with $5M pipeline, that's $1M in additional revenue. At 20% capture rate, Gong priced at $200K annually—10× higher than cost-plus would suggest. Customers still saw 400% ROI.

Model 3: Competitive Pricing

Price relative to alternatives. Use as reference, not anchor.

Three Competitive Strategies:

| Strategy | Approach | When to Use | |----------|----------|-------------| | Price Parity | Match competitor pricing | Commodity features, late market entry | | Premium Pricing | 20-50% above competitors | Superior product, strong brand | | Penetration Pricing | 20-40% below competitors | New market, land-and-expand strategy |

Competitive Analysis Framework:

| Competitor | Their Price | Their Model | Your Differentiation | Your Price | |------------|------------|-------------|---------------------|------------| | Salesforce | $150/user | Per-seat | Easier setup | $120/user | | HubSpot | $800/month | Tiered | Better reporting | $900/month | | Pipedrive | $75/user | Per-seat | Enterprise features | $100/user |

Real Example: Notion entered the crowded productivity space with competitive pricing. They priced 30% below Evernote and Confluence while offering superior features. This penetration strategy won 4M users in 2 years. Once established, they raised prices 25% with minimal churn.

Model 4: Dynamic Pricing

Adjust prices based on real-time demand, customer segment, or usage patterns.

Dynamic Pricing Types:

| Type | Mechanism | Example | |------|-----------|---------| | Usage-Based | Price scales with consumption | AWS, Twilio | | Segment-Based | Different prices for different customers | Student discounts, enterprise tiers | | Time-Based | Prices change by season/day | Airlines, hotels | | Demand-Based | Prices rise with demand | Surge pricing, limited inventory |

Implementation Requirements:

Real-time usage tracking
Customer segmentation capability
Pricing flexibility in billing system
Clear communication to avoid backlash

Real Example: Twilio uses pure usage-based pricing. Customers pay per SMS sent, per minute of voice calls, per API request. This aligns perfectly with customer value—more usage means more business value. Twilio's NRR (net revenue retention) exceeds 130% because customers naturally expand as they grow.

Pricing Psychology: The Science of Perceived Value

How you present prices matters as much as the numbers themselves.

Price Anchoring

Establish a reference point that makes your preferred option attractive.

Anchoring Formula:

Anchor Price = Target Price × 1.5 to 2.0

Example: Figma wanted to charge $12/editor/month. They created an anchor:

Enterprise: $45/editor (anchor)
Professional: $12/editor (target)
Starter: $0 (freemium hook)

The $45 anchor made $12 feel reasonable. Professional tier sales increased 40% after adding the Enterprise anchor.

Real Example: Salesforce uses the "Contact Us" enterprise tier as an anchor. The unspoken high price of enterprise makes the $150/user/month Professional edition feel accessible to mid-market buyers.

The Decoy Effect

Add an inferior option to make your target option shine.

Classic Decoy Structure:

| Option | Price | Value | Purpose | |--------|-------|-------|---------| | Basic | $50 | 50 units | Budget option | | Target (Pro) | $100 | 120 units | Preferred choice | | Decoy | $95 | 55 units | Makes Pro look obvious | | Premium | $200 | 200 units | Upsell anchor |

The $95 decoy is worse than Pro on both price and value. It exists solely to make Pro the obvious choice.

Real Example: The Economist famously used a decoy: Online subscription ($59), Print subscription ($125), or Print + Online ($125). The print-only option was the decoy—no one chose it, but it made Print + Online look like a steal. Print + Online sales increased 43%.

Charm Pricing

Prices ending in 9 or 99 create the perception of value.

Charm Pricing Data:

| Price | Conversion Rate | Perception | |-------|----------------|------------| | $99 | 3.2% | Value-focused | | $100 | 2.8% | Premium | | $97 | 3.1% | Discount |

When to Use Charm Pricing:

SMB and prosumer products
E-commerce and self-serve
Price-sensitive segments

When to Avoid:

Enterprise sales (round numbers signal quality)
Luxury/premium positioning
B2B with procurement (99 endings look "retail")

Real Example: Slack uses charm pricing for their Standard plan ($7.25/user) but round numbers for Plus ($12.50) and Enterprise Grid (custom). The charm price attracts startups; round numbers signal enterprise-grade for larger customers.

Good-Better-Best Tiering

Three-tier pricing captures 80% of revenue optimization. Structure tiers to guide customers to your preferred option.

The Three-Tier Framework

| Tier | Positioning | Price Ratio | Purpose | |------|-------------|-------------|---------| | Good | Starter/Basic | 1× (base) | Capture price-sensitive segment | | Better | Professional/Growth | 2-3× | Target option for majority | | Best | Enterprise/Elite | 4-10× | Capture high-value customers |

Tier Design Principles

Principle 1: Clear Feature Differentiation

Each tier must have obvious, valuable differences:

| Feature | Good | Better | Best | |---------|------|--------|------| | Users | 5 | 25 | Unlimited | | Storage | 10 GB | 100 GB | Unlimited | | Support | Email | Priority | Dedicated CSM | | Integrations | 10 | 50 | Unlimited | | API Access | No | Yes | Advanced |

Principle 2: Strategic Omission

Exclude critical features from lower tiers to drive upgrades:

SSO/Security features → Enterprise only
Advanced analytics → Professional+
API access → Professional+
Custom branding → Growth+

Principle 3: Price Ratio Psychology

The jump from Good to Better should feel like a small upgrade; Better to Best should feel significant.

Optimal Ratios:

| Ratio | Psychology | Example | |-------|------------|---------| | Good:Better = 1:2 | "Double the value" | $49 → $99 | | Better:Best = 1:3 | "Serious upgrade" | $99 → $299 | | Good:Best = 1:6 | "Completely different tier" | $49 → $299 |

Real Example: Notion's pricing follows perfect tier ratios:

Free: $0 (hook)
Plus: $8/month (1×)
Business: $15/month (1.9×)
Enterprise: $25/month (3.1×)

The 2× jump from Plus to Business feels accessible. Enterprise at 3× signals "contact us for real pricing" for large teams.

Naming Your Tiers

Tier names influence perceived value:

| Naming Convention | Best For | Examples | |------------------|----------|----------| | Functional (Basic/Pro/Enterprise) | B2B SaaS | HubSpot, Salesforce | | Size-Based (Starter/Growth/Scale) | PLG companies | Notion, Figma | | Outcome-Based (Essential/Professional/Business) | Service businesses | QuickBooks, FreshBooks | | Brand-Aligned (Creator/Team/Agency) | Creative tools | Webflow, Canva |

Freemium vs. Free Trial: Choosing Your Model

Both acquisition models work, but for different products and markets.

Freemium Model

Best For:

Network effect products (Slack, Dropbox)
Low marginal cost (SaaS, digital products)
Viral growth potential
Self-serve onboarding

Freemium Metrics:

| Metric | Target | Red Flag | |--------|--------|----------| | Free-to-Paid Conversion | 2-5% | <1% | | Time to Upgrade | 30-90 days | >180 days | | Free User LTV | $0 (acquisition cost only) | Negative | | Viral Coefficient | >0.3 | <0.1 |

Freemium Tier Design:

| Element | Strategy | Example | |---------|----------|---------| | Usage Limits | Generous but not unlimited | Slack: 10K messages | | Feature Gating | Core features free, power features paid | Figma: 3 projects free | | User Limits | Individual free, teams pay | Notion: 10 guests free | | Time Limits | None (evergreen free tier) | - |

Real Example: Figma's freemium model drives 80% of new user acquisition. They offer:

Unlimited files (generous)
3 projects (limitation)
2 editors (team gating)
Basic prototyping (core value)

Free users upgrade when they hit the 3-project limit or need more editors. Conversion rate: 4.2%, with average time-to-upgrade of 67 days.

Free Trial Model

Best For:

Complex products requiring setup
Enterprise sales with high ACV
Products with clear time-to-value
Sales-assisted conversion

Trial Metrics:

| Metric | Target | Red Flag | |--------|--------|----------| | Trial-to-Paid Conversion | 15-30% | <10% | | Trial Length | 7-30 days | >30 days | | Activation Rate | 60-80% | <40% | | Time-to-Value | <3 days | >7 days |

Trial Optimization Tactics:

| Tactic | Implementation | Impact | |--------|---------------|--------| | Reverse Trial | Full features, downgrade after trial | +25% conversion | | Usage-Based Extension | Extend trial for completing milestones | +15% activation | | Credit Card Required | Higher intent, lower volume | +40% conversion, -30% signups | | No Credit Card | Lower barrier, higher volume | Standard approach |

Real Example: Datadog uses 14-day free trials with reverse trial mechanics. Users get full access to all features. At day 10, they receive a "value summary" email showing exactly how much monitoring data they collected. Trial-to-paid conversion: 22%, with 73% activating within 3 days.

Hybrid Models

Many successful companies use both:

| Model | Structure | Example | |-------|-----------|---------| | Freemium + Trial | Free tier with premium trial | HubSpot | | Trial + Freemium | Trial first, downgrade to free | Dropbox | | Usage-Based Free | Free up to X, then pay | Twilio |

Real Example: HubSpot's hybrid model:

Free CRM: Unlimited contacts, basic features (freemium)
Trial: 14-day access to Marketing Hub Pro
Conversion Path: Free → Trial → Paid

This captures users at all stages: free for startups, trial for evaluating teams, paid for committed users.

Raising Prices: The Art of the Increase

Most companies should raise prices annually. Done right, you'll grow revenue without losing customers.

When to Raise Prices

Signals It's Time:

Win rate exceeds 40% (you're underpriced)
Customer expansion revenue exceeds 30%
Competitors raised prices without losing market share
New feature releases increased value significantly
CAC payback period exceeds 18 months

Pricing Increase Formula:

New Price = Current Price × (1 + Value Increase %)

Typical Annual Increases:

5-10% for mature products
15-25% for rapidly improving products
50-100% for major platform shifts

The 90-Day Price Increase Playbook

Month 1: Preparation

Week 1-2: Analysis

Calculate price elasticity using historical data
Segment customers by value realization
Identify at-risk customers (price-sensitive, recent churn signals)

Week 3-4: Communication Strategy

Draft customer communication
Prepare sales talking points
Create grandfathering policy

Month 2: Announcement

Week 5-6: Advance Notice

Email all customers 60 days before effective date
Host Q&A webinar for enterprise accounts
Publish FAQ on pricing page

Sample Announcement Email:

Subject: Upcoming pricing updates for [Product]

Hi [Name],

In 60 days, we're updating our pricing to reflect the significant platform improvements we've delivered over the past year.

What's Changing:

Pro plan: $99 → $119/month (20% increase)

New AI features included at all tiers

Annual billing discount increasing to 20%

What Stays the Same:

Your current rate is locked for 12 months (grandfathered)

No changes to your existing features

Questions? Reply to this email or book a call with our team.

Thanks for being a valued customer. [CEO Name]

Week 7-8: Sales Preparation

Train sales team on objection handling
Prepare discount authority matrix
Update all collateral and proposals

Month 3: Implementation

Week 9-10: New Pricing Live

Update pricing page
Change in-app upgrade flows
Activate new customer pricing

Week 11-12: Legacy Customer Follow-Up

Reach out to at-risk segments
Offer annual prepay to lock current rates
Monitor churn and downgrade rates

Grandfathering Strategies

Protect existing customers while capturing value from new ones:

| Strategy | Approach | When to Use | |----------|----------|-------------| | Full Grandfathering | Existing customers keep current price forever | Loyal long-term customers | | Time-Limited | 12-month grandfathering, then new pricing | Standard approach | | Feature Lock | Keep price but freeze feature access | Major platform changes | | Gradual Migration | 25% increase annually until aligned | Large price gaps |

Real Example: Slack raised prices 25% in 2019. They grandfathered existing customers for 3 years, then moved them to new pricing with 6 months notice. Churn increased only 0.5% during the transition. Net revenue grew 35% from the price increase alone.

Real-World Pricing Strategies

Example 1: Slack (Freemium to Enterprise)

The Evolution:

| Year | Key Pricing Change | Impact | |------|-------------------|--------| | 2014 | Free for unlimited users (growth phase) | 1M users in 1 year | | 2016 | Introduced paid tiers ($6.67-$15/user) | First revenue | | 2019 | 25% price increase | $400M additional ARR | | 2021 | Enterprise Grid ($ customized) | Fortune 500 penetration |

Key Decisions:

Generous free tier: 10K message history, unlimited users (growth at all costs)
Per-seat pricing: Simple, predictable, scales with customer value
Enterprise creation: Separate product for $100K+ ACV deals

The Result: IPO at $23B valuation with 130%+ net revenue retention.

Example 2: Figma (Design Tool Pricing)

The Strategy:

Figma disrupted Adobe's design monopoly through innovative pricing:

| Tier | Price | Target | Key Gating | |------|-------|--------|------------| | Starter | Free | Individual designers | 3 projects, 2 editors | | Professional | $12/editor | Small teams | Unlimited projects, version history | | Organization | $45/editor | Large teams | Design systems, analytics | | Enterprise | Custom | Fortune 500 | SSO, SCIM, dedicated support |

Psychology Tactics:

Editor-based pricing: Aligns with team growth (more editors = more value)
Project limitation: Natural upgrade trigger at 3 projects
Organization jump: 4× price signals serious upgrade

The Result: $20B Adobe acquisition offer (rejected), $10B valuation as independent company.

Example 3: Notion (All-in-One Workspace)

The Freemium Mastery:

Notion's pricing drives 70%+ organic growth:

| Tier | Price | Target | Strategy | |------|-------|--------|----------| | Free | $0 | Personal use | Generous limits, viral templates | | Plus | $8 | Power users | Unlimited file uploads | | Business | $15 | Teams | SAML, advanced permissions | | Enterprise | $25 | Large orgs | Audit logs, SCIM |

Pricing Innovations:

Guest access: Free tier allows 10 guests (viral spread)
Template marketplace: Free distribution, paid customization
AI add-on: $8/month for AI features (new revenue stream)

The Result: 30M users, $10B valuation, 85%+ gross margins.

A/B Testing Prices

Test pricing changes with statistical rigor. Never guess.

Price Testing Framework

Step 1: Hypothesis Formation

| Test | Hypothesis | Expected Impact | |------|-----------|-----------------| | Increase Pro price 20% | Low price sensitivity | +15% revenue, -5% conversion | | Add enterprise tier | Uncaptured enterprise value | +25% average deal size | | Change to usage-based | Better value alignment | +30% NRR over 12 months |

Step 2: Test Design

Geographic Testing:

Show new pricing to visitors from Region A
Control group sees old pricing in Region B
Run for 30-60 days minimum

Segment Testing:

New customers see new pricing
Existing customers grandfathered
Compare CAC, LTV, conversion by cohort

Step 3: Statistical Significance

Required sample sizes for reliable results:

| Confidence Level | Minimum Conversions per Variant | Test Duration | |-----------------|--------------------------------|---------------| | 90% | 100 | 2-4 weeks | | 95% | 200 | 4-8 weeks | | 99% | 500 | 8-12 weeks |

Step 4: Decision Criteria

| Metric | Implement if | Reject if | |--------|-------------|-----------| | Revenue per visitor | +10% or more | Negative or <5% | | Conversion rate | Within 10% of control | >15% decrease | | Customer acquisition cost | Within 15% of control | >25% increase |

Real Example: Airtable tested 20% price increase on new signups for 60 days. Results:

Conversion rate: -8% (acceptable)
Revenue per visitor: +11% (winner)
CAC: +3% (minimal impact)

They implemented the increase globally. Annual revenue impact: $12M.

Pricing Strategy Tools

Research and Analysis

| Tool | Purpose | Price | |------|---------|-------| | Price Intelligently | Pricing strategy consulting | Custom | | ProfitWell | SaaS pricing analytics | Free-$1,000/month | | ChartMogul | Subscription analytics | $100-$2,000/month | | Gainsight | Customer health/ expansion | Custom |

A/B Testing

| Tool | Purpose | Best For | |------|---------|----------| | Optimizely | Website price testing | Enterprise | | VWO | Conversion optimization | Mid-market | | Google Optimize | Free price testing | Startups | | Intellimize | AI-driven optimization | Scale-ups |

Competitive Intelligence

| Tool | Purpose | Price | |------|---------|-------| | Crayon | Competitive pricing tracking | $500+/month | | Kompyte | Competitor monitoring | $800+/month | | G2 | Customer review analysis | Free-$10K/year | | Owler | Company intelligence | Free-$720/year |

Conclusion

Pricing is strategy. It signals your market position, captures the value you create, and determines your growth trajectory.

Start with value-based pricing. Calculate the economic value you deliver and capture 15-30% of it. Structure good-better-best tiers with clear differentiation. Choose freemium for viral products, free trials for complex sales.

Raise prices annually as you add value. Grandfather existing customers to maintain trust. A/B test changes with statistical rigor.

The companies that win aren't those with the best products—they're those who capture the most value from the products they have. Slack, Figma, and Notion didn't succeed because their products were 10× better. They succeeded because their pricing strategies captured 10× more value.

Your pricing page is your most important sales rep. Optimize it ruthlessly.

Related Guides

Need help optimizing your pricing strategy? Contact our team for a free consultation.