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Frameworks, core principles and top case studies for SaaS pricing, learnt and refined over 28+ years of SaaS-monetization experience.
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In the competitive SaaS landscape, how you charge for your product can be just as important as the product itself. Usage-based pricing has emerged as a powerful alternative to traditional subscription models, allowing companies to align revenue with the value customers actually receive. But for founders, one question looms large: which metrics should you actually measure and bill against?
As a founder myself, I've navigated these waters and seen how the right pricing metrics can accelerate growth while the wrong ones can create friction and churn. Let's explore how to select, implement, and optimize usage-based pricing metrics that work for both your business and your customers.
Why Usage-Based Pricing Is Gaining Momentum
Usage-based pricing ties what customers pay directly to how much value they extract from your product. According to OpenView's 2022 SaaS Benchmarks report, companies with usage-based models grow faster—demonstrating 38% higher revenue growth compared to their pure subscription counterparts.
This pricing approach offers several advantages:
- Lower entry barriers: Customers can start small and scale their usage (and payments) as they derive value
- Reduced churn risk: When customers use less, they pay less, rather than canceling entirely
- Revenue expansion: As customers succeed and grow their usage, your revenue grows automatically
- Natural product-market fit indicator: Usage directly reflects product value
But implementing this model successfully hinges on selecting the right metrics.
The Framework for Choosing Your Pricing Metrics
The best usage-based pricing metrics share three critical characteristics:
1. Value Alignment
The most powerful pricing metrics directly correlate with the value customers receive. Ask yourself:
- What outcomes do customers achieve with your product?
- How do customers measure success when using your solution?
Example: Twilio charges per message sent because each message represents a customer communication touchpoint—a clear unit of value.
2. Predictability & Control
Customers need to feel they can predict and control their costs:
- Can customers reasonably forecast their usage?
- Do they have mechanisms to control or limit their spending if needed?
- Is usage highly volatile or relatively stable?
Example: MongoDB shifted from charging based on server capacity to data stored because customers found server capacity difficult to predict, creating billing anxiety.
3. Simplicity & Transparency
Complex pricing creates friction in the sales process and can damage trust:
- Can you explain your pricing model in one sentence?
- Will customers intuitively understand what drives their costs up or down?
- Can usage be clearly measured and verified by customers?
According to a study by Price Intelligently, 92% of SaaS companies that simplified their pricing saw increased conversion rates within three months.
Common Usage-Based Pricing Metrics to Consider
Different product categories naturally lend themselves to different consumption KPIs:
Infrastructure & Developer Tools
- API calls/requests
- Compute time
- Data processed/stored
- Bandwidth
Real-world example: AWS Lambda charges based on the number of requests and computation time, directly tying costs to resource consumption.
Communication & Collaboration Tools
- Active users
- Messages sent
- Storage used
- Integration events
Real-world example: Slack's pricing includes a free tier with limited message history, then charges per active user with unlimited history retention.
Data & Analytics Platforms
- Data volume ingested
- Query volume/complexity
- Report generations
- Data exports
Real-world example: Snowflake charges based on compute usage and storage, allowing customers to scale their data warehouse spending in line with actual usage.
Marketing & Customer Engagement
- Contacts stored
- Campaigns sent
- Engagement events tracked
- Audience reach
Real-world example: Mailchimp prices based on the number of contacts and emails sent monthly, scaling as customer marketing efforts expand.
Startup Metrics vs. Enterprise Metrics: Finding the Right Balance
For early-stage startups, simpler metrics often work better:
- Focus on adoption: Choose metrics that encourage product usage rather than restricting it
- Minimize complexity: Each additional billing metric adds sales friction
- Prioritize predictability: Surprising bills lead to churn, especially with smaller customers
As you move upmarket to enterprise customers:
- Multiple metrics may be necessary: Larger organizations often have more complex usage patterns
- Consider hybrid models: Combining subscriptions with usage components can provide baseline predictability with upside potential
- Add governance features: Usage caps, alerts, and dashboards become critical
According to Profitwell research, enterprises typically prefer pricing models with some predictability, with 76% favoring hybrid fixed/usage-based approaches over pure consumption pricing.
Implementation: Making Usage-Based Pricing Work
Successfully implementing usage-based pricing requires more than just selecting metrics:
Technical Infrastructure
You'll need robust usage tracking and billing systems to:
- Capture usage events accurately
- Aggregate data reliably
- Calculate bills correctly
- Provide usage transparency to customers
Many founders underestimate this technical lift. Consider leveraging specialized billing platforms like Stripe Billing, Chargebee, or usage-specific solutions like Metronome or Amberflo before building in-house.
Pricing Structure Decisions
Once you've selected your metrics, you'll need to determine:
- Pricing tiers vs. continuous pricing: Will you have usage buckets or charge precisely for every unit?
- Volume discounts: How will you reward larger customers?
- Minimums and commitments: Will you require baseline commitments?
Tomasz Tunguz of Redpoint Ventures found that 83% of public SaaS companies with usage-based models employ some form of minimum commitment to ensure baseline revenue predictability.
Customer Success Alignment
Usage-based models change how customer success teams operate:
- Success becomes directly tied to encouraging appropriate product usage
- Monitoring usage patterns can identify churn risks early
- Customer education about usage optimization becomes critical
Testing Your Usage-Based Pricing Model
Before full implementation, consider:
- Shadow billing: Run your new pricing model alongside existing pricing to understand impact
- Cohort testing: Test with a subset of new customers
- Customer interviews: Get qualitative feedback on perceived fairness and value alignment
Startup metrics expert and VC Davi