Choosing the Right Value Metric for Your Pricing Model

Should you price per user? Per transaction? Per data volume? Per outcome?

Your value metric—the unit you charge for—is one of the most consequential pricing decisions you'll make. It determines how your revenue scales, which customers you attract, and whether pricing naturally expands or creates friction.

After working through value metric decisions for three B2B products and analyzing dozens of SaaS pricing models, I've learned that the right value metric aligns what customers value with how they naturally grow on your platform.

Here's how to choose a value metric that drives mutual success.

Understand What a Value Metric Actually Does

A value metric isn't just how you charge—it's how value scales for both you and your customer.

A good value metric:

• Aligns with how customers perceive value
• Scales naturally as customers get more value
• Creates expansion revenue without sales intervention
• Is simple enough to understand and predict
• Doesn't penalize customer success

Example: Slack pricing per active user. As teams grow and get value from Slack, usage naturally expands to more people. Revenue grows with value delivered. Users don't feel penalized because more teammates joining is a positive outcome.

Counter-example: Pricing per message sent. Makes users think twice before communicating. Success (more communication) feels like a penalty (higher costs). Misaligned value metric.

The right value metric feels fair and natural. The wrong one creates friction at every expansion conversation.

Map Your Value Metric to Customer Value Drivers

Start by understanding what actually drives value for customers.

Ask: What makes this product more valuable to customers over time?

For a marketing automation platform:

• More campaigns run → value metric could be campaigns/month
• More contacts in database → value metric could be contact volume
• More users on the team → value metric could be seats
• More revenue attributed → value metric could be % of revenue

Test alignment: Does the metric grow when customers are successful?

Good alignment: CRM priced per sales rep. More reps = more revenue = more value from CRM.

Poor alignment: Project management priced per project. Customers consolidate projects to save money, fighting against tool adoption.

Validate with customers: "As you get more value from our product, what changes? Team size? Volume? Frequency of use?"

Their answer points to your value metric.

Evaluate Common Value Metric Models

Most B2B SaaS uses one of these pricing approaches.

Per-seat pricing:

• Works when: Product is user-centric, value scales with team size
• Example: Asana, Slack (per active user)
• Pros: Predictable, simple, understood by market
• Cons: Can limit adoption, doesn't work for shared access models

Usage-based pricing:

• Works when: Value directly correlates with volume
• Example: Twilio (per API call), AWS (per compute/storage)
• Pros: Aligns cost with value, fair for variable usage
• Cons: Less predictable revenue, requires good usage tracking

Tiered feature-based pricing:

• Works when: Different features serve different customer segments
• Example: Basic/Pro/Enterprise tiers
• Pros: Simple, creates upgrade path
• Cons: Doesn't capture usage expansion within a tier

Outcome-based pricing:

• Works when: Clear, measurable outcome you can track
• Example: Recruiting tools priced per hire, ad platforms per conversion
• Pros: Perfect alignment of value and cost
• Cons: Hard to measure, requires sophisticated tracking

Hybrid models:

• Works when: Multiple dimensions of value exist
• Example: Base platform fee + usage charges, or seats + data volume
• Pros: Captures multiple value drivers
• Cons: More complex to communicate and forecast

Choose the model where scaling the metric naturally indicates customer success.

Test Whether Your Metric Encourages or Discourages Adoption

The wrong value metric fights against product adoption.

Red flags:

Customers game the system to reduce costs:

• Sharing logins to avoid per-seat charges
• Batching actions to stay under volume limits
• Removing users to save money

Pricing penalizes success behaviors:

• "I'd invite more teammates but it's too expensive"
• "I'd use this more but I'm worried about the bill"
• "I'm deleting old data to stay in my tier"

Expansion requires sales involvement:

• Can't naturally expand without contract renegotiation
• Customers bump into hard tier limits
• Pricing doesn't grow smoothly with usage

Green flags:

Customers expand organically:

• Natural growth in metric as they succeed
• Expansion happens automatically, no sales call needed
• Customers feel pricing is fair as they grow

Success behaviors align with revenue:

• "More people should use this"
• "Let's use it for more use cases"
• "We're getting great ROI, happy to expand"

The best value metrics create a virtuous cycle: customer success → natural expansion → more value delivered → fair pricing growth.

Consider Metric Simplicity and Predictability

Customers need to understand and forecast their costs.

Can a buyer easily predict their monthly cost?

Simple: "$50 per user per month" → buyer knows exactly what 20 users costs

Complex: "Base fee of $1,000 + $0.02 per API call + $50 per GB over 100GB + $100 per integration" → impossible to forecast

Test the 30-second explanation rule. Can you explain your pricing to a prospect in 30 seconds and have them understand their approximate cost? If not, simplify.

Provide pricing calculators. If your metric is usage-based, give prospects tools to estimate costs based on their expected volume.

Show typical customer spending. "Most mid-market customers spend $2-5K/month" helps anchor expectations even with variable pricing.

Predictability reduces purchase friction.

Evaluate Competitive and Market Norms

While you shouldn't copy competitors, you should understand category norms.

What value metrics do category leaders use? If everyone in your space prices per-seat, switching to per-usage might confuse buyers or make comparisons difficult.

When to follow market norms: When the existing metric works well and buyers expect it.

When to break from market norms: When the standard metric creates customer pain points you can solve.

Example: Figma broke from Adobe's per-seat model by pricing per editor (designers) with free viewer accounts. This lowered friction for cross-functional teams reviewing designs.

Differentiated value metrics can be powerful, but only if they solve a real problem with the status quo.

Model Revenue Implications

Your value metric determines your revenue trajectory.

Build a growth model for each metric option:

Per-seat model: Revenue = Customers × Average seats per customer × Price per seat

• How does seat count grow over time?
• What's average seats at 1 year vs. 3 years?

Usage-based model: Revenue = Customers × Average usage × Price per unit

• How does usage grow over time?
• What's usage curve across customer lifecycle?

Tier-based model: Revenue = Customers × Tier mix × Average tier price

• What % upgrade to higher tiers over time?
• What's typical upgrade timeline?

Compare expansion potential: Which metric creates the most natural expansion revenue?

Assess downside scenarios: What happens in a downturn? Per-seat pricing contracts when companies cut headcount. Usage-based pricing declines with reduced activity. Which risk is more acceptable?

Revenue predictability vs. growth potential is a trade-off to consider.

Test Your Metric Before Fully Committing

Don't make this decision in a boardroom. Test with real customers.

Launch with initial metric to first 50-100 customers. Monitor:

• Is expansion happening naturally?
• Are customers pushing back on the metric?
• Can we forecast revenue accurately?
• Are we attracting the right customer segments?

Interview customers about pricing fairness. "Do you feel our pricing aligns with the value you receive?" Segment responses by customer tier and usage level.

Model switching costs. If you need to change your value metric later, how disruptive would it be? Better to test and iterate early.

Consider hybrid approaches. Start with simpler metric, add usage dimensions later as you gather data on value correlation.

Your first value metric doesn't have to be your forever metric, but changing it is painful. Test and validate before scaling.

When to Consider Multiple Metrics

Sometimes one metric isn't enough to capture value.

Use multiple metrics when:

• Your product serves very different use cases (SMB self-service vs. enterprise custom)
• Value drivers differ significantly by customer segment
• You need base recurring revenue plus expansion revenue

Common hybrid structures:

• Base platform fee + usage charges (predictable base + expansion upside)
• Seats + data volume (captures both team growth and usage intensity)
• Feature tier + transaction volume (segments by sophistication and scale)

Keep it simple: Maximum of two value drivers. Three or more creates confusion.

The right value metric makes pricing feel natural and fair while aligning your revenue growth with customer success. Choose the metric that grows when customers succeed, is simple to understand, and creates natural expansion. That's when pricing becomes a growth engine instead of a friction point.