Growth & Strategy
Personas
SaaS & Startup
Time to ROI
Medium-term (3-6 months)
I still remember the panic call from my client at 2 AM. Their SaaS revenue had dropped 40% in three months after switching to pay-per-use pricing. What was supposed to be their "fair pricing revolution" turned into a nightmare scenario where their best customers were suddenly paying a fraction of what they used to.
Here's the thing nobody talks about with usage-based pricing: it's not automatically better just because it sounds fair. I've worked with multiple SaaS clients experimenting with different pricing models, and I've seen both spectacular successes and complete disasters with pay-per-use approaches.
The SaaS world is obsessed with usage-based pricing right now. Twilio, Stripe, AWS - everyone's pointing to these success stories. But for every success, there are dozens of companies that tried and failed. The difference? Understanding when and how to implement it correctly.
In this playbook, you'll discover:
Why most SaaS companies get pay-per-use pricing completely wrong
The hidden costs of usage-based billing that nobody talks about
When usage pricing actually increases revenue (and when it kills it)
My framework for deciding if your SaaS should make the switch
The implementation strategy that saved my client's business
Let's dive into why SaaS pricing strategy isn't as simple as "charge for what they use."
Industry Reality
What every SaaS founder believes about usage pricing
The conventional wisdom around usage-based pricing sounds compelling: charge customers only for what they actually use, and everyone wins. It's "fair," reduces barriers to entry, and theoretically scales with customer value. Every pricing consultant and SaaS guru is preaching this gospel.
Here's what the industry typically recommends:
Start with freemium or low-cost entry - Let customers try before they commit to major spend
Scale pricing with value delivered - More usage = more value = more revenue, perfectly aligned
Reduce churn through fair pricing - Customers won't leave if they're only paying for what they use
Lower acquisition barriers - No big upfront commitment means easier sales cycles
Automatic expansion revenue - Growth in usage automatically drives revenue growth
This advice exists because successful examples like AWS, Twilio, and Stripe make it look easy. The logic seems bulletproof: if customers pay based on value received, everyone should be happy.
But here's where conventional wisdom falls apart: usage-based pricing only works when your product has predictable, measurable value units that customers understand and can control. Most SaaS products don't meet these criteria, but founders try to force-fit the model anyway.
The real problem? Everyone focuses on the benefits while ignoring the massive operational complexity, unpredictable revenue streams, and customer confusion that comes with poorly implemented usage pricing. It's not a magic bullet - it's a specialized tool that works in specific situations.
Consider me as your business complice.
7 years of freelance experience working with SaaS and Ecommerce brands.
I learned this lesson the hard way while working with a B2B SaaS client in the project management space. They had a solid subscription business - customers paying $50-200 per month for team collaboration features. Revenue was predictable, churn was manageable, and growth was steady.
Then they got seduced by the usage-based pricing trend. "Why should a 5-person team pay the same as a 50-person team?" they asked. Fair point, right?
The decision seemed logical. They'd charge based on "active projects" and "team member invitations." Small teams would pay less, big teams would pay more, and everyone would get exactly what they needed. We spent months building the billing infrastructure, creating usage dashboards, and preparing the transition.
What happened next was a masterclass in unintended consequences.
First, their best customers - mid-sized agencies with consistent usage patterns - saw their bills drop dramatically. These customers had been overpaying on the old flat-rate model, and suddenly they were paying 60% less. Revenue from the top quartile of customers collapsed.
Second, customer behavior changed in weird ways. Teams started gaming the system, sharing accounts, creating workarounds to minimize "billable" usage. Instead of growing naturally into higher plans, they were actively trying to reduce their footprint.
Third, and this was the killer: support costs exploded. Every month, customers questioned their bills. "Why did I get charged for 47 projects when I only remember creating 23?" The customer success team spent more time explaining bills than helping customers succeed.
The final straw came when their enterprise prospects started backing out of deals. CFOs couldn't budget for unpredictable costs. "We need to know what this will cost us annually," they kept hearing. Usage-based pricing had made their product unbuyable for the exact customers they wanted most.
Here's my playbook
What I ended up doing and the results.
After that disaster, I developed a framework for evaluating when usage-based pricing actually makes sense. It's not about following trends - it's about understanding your specific business dynamics.
The Usage Pricing Viability Test
Before even considering usage-based pricing, you need to pass four critical tests:
Test 1: Value Unit Clarity
Can customers easily understand and predict what drives their costs? For AWS, it's compute hours and storage - crystal clear. For my client, "active projects" was ambiguous. When does a project become active? When it's created, when someone works on it, or when it's marked complete?
We spent weeks defining these rules, and customers still got confused. If you can't explain your usage metric in one sentence, you'll have problems.
Test 2: Control & Predictability
Can customers control their usage and predict their costs? This is where most SaaS companies fail. Customers need to be able to say, "If I do X, my bill will be approximately Y."
My client's customers couldn't predict costs because project creation was organic. Sometimes they'd create 5 projects in a month, sometimes 25. The unpredictability killed any budgeting ability.
Test 3: Usage Distribution Analysis
This is the big one: how is usage distributed among your customers? If most customers cluster around similar usage levels, flat-rate pricing is often better. Usage pricing works best when there's dramatic variation in customer needs.
We analyzed my client's data and found that 70% of customers used 15-30 projects per month. The variation wasn't dramatic enough to justify the complexity.
Test 4: Operational Complexity Assessment
Can you handle the operational overhead? Usage billing requires sophisticated tracking, customer communication, dispute resolution, and forecasting. The infrastructure and support costs are significant.
The Hybrid Solution That Worked
Instead of pure usage pricing, we implemented a hybrid model that solved the original problem without the downsides:
Tiered Usage Buckets: Instead of per-project billing, we created clear tiers (Starter: up to 15 projects, Professional: up to 50 projects, Enterprise: unlimited). Customers got predictable pricing with built-in expansion revenue.
Usage-Based Overages: Customers could exceed their tier limits for a small per-project fee, but 95% stayed within their plans. This gave flexibility without unpredictability.
Annual vs Monthly Options: Enterprise customers could choose annual contracts with usage allowances, giving them budget predictability while still scaling with growth.
The key insight: we kept the fairness perception of usage pricing while maintaining the predictability of subscription models.
Value Unit Design
Clear usage metrics that customers understand and can predict are non-negotiable for success.
Control Mechanisms
Customers must be able to manage and forecast their usage to avoid bill shock and budget issues.
Revenue Impact
Understanding usage distribution helps predict whether the model will increase or decrease overall revenue.
Implementation Strategy
Hybrid models often work better than pure usage pricing for most SaaS businesses.
The results from this hybrid approach told the complete story:
Revenue Recovery: Within six months, monthly recurring revenue returned to pre-change levels. The tiered structure with usage allowances let us capture expansion revenue without losing base revenue from existing customers.
Customer Satisfaction: Support tickets about billing dropped 80%. Customers could predict their costs while still getting the "fair" feeling of usage-based elements. The best of both worlds.
Enterprise Adoption: The annual plans with usage allowances solved the enterprise budgeting problem. Large deals started closing again because CFOs could budget accurately.
Unexpected Benefits: Customer retention actually improved. The tiered structure created natural upgrade paths as companies grew, and customers felt they were getting value at every level.
Most importantly, we learned that pricing model success isn't about following industry trends - it's about solving real customer problems while maintaining business viability.
What I've learned and the mistakes I've made.
Sharing so you don't make them.
Here are the key lessons learned from this pricing model experiment:
Predictability beats fairness - Customers value knowing their costs more than paying exactly for usage
Usage distribution matters more than customer size - If usage doesn't vary dramatically, usage pricing adds complexity without benefits
Enterprise customers hate surprises - Unpredictable billing kills enterprise deals faster than high prices
Support costs are real - Usage billing creates ongoing customer service overhead that many companies underestimate
Hybrid models work better - Combining subscription predictability with usage-based elements often delivers the best results
Test before you commit - Run pilots with existing customers before making company-wide changes
Gaming is inevitable - Customers will find ways to minimize usage if it saves money, which can hurt your product adoption
The biggest learning: pricing model success depends more on customer psychology and operational execution than on theoretical fairness. Focus on what works for your specific business and customer base, not industry trends.
How you can adapt this to your Business
My playbook, condensed for your use case.
For your SaaS / Startup
Analyze your usage distribution before switching - if variation is low, stick with tiers
Consider hybrid models with predictable base costs and usage overages
Test with existing customers before company-wide implementation
Build robust tracking and billing infrastructure first
For your Ecommerce store
E-commerce works well with transaction-based pricing for payment processing features
Inventory management tools can use SKU-based pricing effectively
Marketing tools should consider email/contact volume pricing
Always provide cost calculators for predictability