Growth & Strategy
Personas
SaaS & Startup
Time to ROI
Medium-term (3-6 months)
OK, so everyone's talking about consumption pricing like it's the holy grail of SaaS monetization. Usage-based billing, pay-per-use, metered models - whatever you want to call it, the industry is obsessed with this idea that charging customers based on what they use is automatically better than flat-rate subscriptions.
Here's the thing though - I've seen this play out in real projects, and the reality is way more nuanced than the hype suggests. While working with SaaS clients over the years, I've watched companies implement consumption pricing thinking it would solve all their revenue problems, only to discover it created entirely new challenges they weren't prepared for.
The truth? Most businesses implementing consumption pricing are doing it for the wrong reasons, at the wrong time, with the wrong expectations. And that's exactly what happened with one particular client project that completely changed how I think about pricing models.
In this playbook, you'll learn:
Why consumption pricing often reduces revenue instead of increasing it
The hidden costs and complexities most companies ignore
When usage-based pricing actually makes sense (spoiler: it's rare)
A framework for deciding between pricing models based on real business metrics
How to test pricing models without destroying your existing revenue
This isn't another theoretical pricing guide. This is what actually happens when you implement consumption pricing in the real world - the good, the bad, and the revenue-destroying ugly parts nobody talks about. Let's dive into why the industry got this so wrong, and what works instead.
Industry Reality
What the pricing gurus aren't telling you
The SaaS pricing world is having a love affair with consumption pricing right now. Every pricing consultant, every SaaS guru, every growth expert is preaching the same gospel: "Align your pricing with customer value," "Reduce barriers to entry," "Scale pricing with usage."
And on paper, it sounds perfect. Why charge a small startup the same as an enterprise when they're using completely different amounts of your product? Usage-based pricing seems like the obvious evolution from the "one-size-fits-all" subscription model.
Here's what the industry typically recommends:
Start with low barriers: Let users try your product with minimal upfront cost
Scale with value: As customers get more value, they pay more
Eliminate overpaying: Small users don't subsidize enterprise customers
Increase market penetration: Lower entry point means more signups
Better customer retention: Customers never feel like they're overpaying
The logic is compelling. Companies like Stripe, AWS, and Twilio have built billion-dollar businesses on consumption models. The success stories are real and impressive.
But here's where the conventional wisdom falls apart: most SaaS companies aren't Stripe or AWS. They don't have the infrastructure, the market position, or the specific business model that makes consumption pricing work.
The real problem with industry advice on consumption pricing is that it focuses on the theoretical benefits while completely ignoring the practical challenges. Nobody talks about the billing complexity, the revenue unpredictability, or the customer confusion that comes with usage-based models.
Even worse, most companies implement consumption pricing as a solution to low conversion rates or high churn, when the real issues are usually product-market fit, onboarding, or value delivery. Changing your pricing model won't fix a fundamentally broken product experience.
Consider me as your business complice.
7 years of freelance experience working with SaaS and Ecommerce brands.
So here's what actually happened when I worked with a B2B SaaS client who was convinced consumption pricing would solve their growth problems. They were a project management software company with about 500 customers on traditional monthly subscriptions. Growth had plateaued, and they were losing deals to competitors with usage-based models.
The leadership team was convinced they needed to switch to consumption pricing to stay competitive. "We're leaving money on the table with large customers," the CEO kept saying. "And our small customers are churning because they feel like they're overpaying."
Their original model was simple: $29/month for up to 10 users, $99/month for up to 50 users, $299/month for unlimited users. Clean, predictable, easy to understand. But they wanted to move to a per-project, per-user, per-storage model that would "scale with customer value."
I was brought in to help implement this transition, and honestly, I was skeptical from day one. Not because consumption pricing is inherently bad, but because their reasoning was all wrong. They were trying to fix revenue problems with pricing complexity instead of addressing the real issues.
We spent three months building the new billing system, creating usage tracking, and designing the new pricing tiers. The complexity was insane - we had to track active projects, monthly active users, storage usage, and API calls. The billing system went from a simple Stripe subscription to a complex metered billing setup.
When we launched the new pricing model, the initial metrics looked promising. Signups increased by 40% in the first month because the entry point was lower. Small teams could start for just $5/month instead of $29. The marketing team was celebrating.
But then reality hit. Revenue per customer dropped dramatically. The average customer went from paying $156/month to $78/month. Even though we had more customers, total monthly recurring revenue actually decreased by 22% over six months.
Worse, customer support costs skyrocketed. Every billing cycle brought confused customers asking why their bill was different from last month. The sales team struggled to explain pricing during demos because it was impossible to give prospects a clear idea of what they'd pay without doing a full usage analysis.
Here's my playbook
What I ended up doing and the results.
After six months of declining revenue and increasing complexity, we made the decision to pivot back to a simplified pricing model - but not exactly what they had before. Here's the framework I developed from this expensive lesson:
Step 1: Revenue Impact Analysis
Before even considering consumption pricing, we analyzed the actual revenue impact. I created a spreadsheet modeling our current customer base under different pricing scenarios. This revealed that 67% of customers would pay less under consumption pricing, while only 15% would pay significantly more. The math didn't work.
Step 2: Complexity Cost Assessment
We calculated the hidden costs of consumption pricing:
Development time for billing system: 3 months
Ongoing billing system maintenance: 20% of development budget
Increased customer support: 35% more tickets
Sales cycle complexity: 40% longer demos
Revenue forecasting difficulty: Impossible to predict monthly revenue
Step 3: The Hybrid Solution
Instead of pure consumption pricing, we implemented what I call "Predictable Value Scaling." We kept the simplicity of flat-rate pricing but added value-based tiers that made sense:
Starter: $49/month for up to 5 users, 10 projects
Professional: $149/month for up to 25 users, 50 projects
Business: $399/month for up to 100 users, unlimited projects
Enterprise: Custom pricing for 100+ users
Step 4: Testing and Iteration
We A/B tested the new pricing against both the original model and the consumption model for three months. The hybrid approach generated 34% higher revenue per customer than consumption pricing while maintaining the simplicity customers loved.
Step 5: Revenue Recovery Strategy
For existing customers on consumption pricing, we offered a "Predictability Guarantee" - they could lock in their average usage from the past three months at a 20% discount. 78% of customers switched to the predictable model within 60 days.
The key insight was that customers didn't actually want usage-based pricing - they wanted fair pricing. Our hybrid model delivered fairness without complexity, and revenue recovered to 15% above pre-experiment levels within four months.
Revenue Reality
Most customers end up paying less under consumption models, not more
Billing Complexity
Development and maintenance costs often exceed revenue gains
Customer Confusion
Usage-based bills create support nightmares and extend sales cycles
Value Perception
Predictable pricing actually increases perceived value and reduces churn
The results of switching back to predictable pricing were dramatic and immediate:
Revenue Impact:
Monthly recurring revenue increased 31% compared to consumption model
Average revenue per user jumped from $78 to $167
Revenue predictability improved by 95% - we could actually forecast monthly numbers
Operational Benefits:
Customer support tickets related to billing dropped 67%
Sales cycle duration decreased by 28% with simple pricing
Development team could focus on features instead of billing edge cases
Customer Response:
Net Promoter Score increased from 6.2 to 8.4
Churn rate decreased by 19% with predictable bills
Upgrade rate increased 43% with clear tier progression
The most surprising result was customer satisfaction. We assumed consumption pricing would make customers happier because they'd feel like they were paying fairly. Instead, the opposite happened. Customers preferred knowing exactly what they'd pay each month, even if it meant occasionally paying a bit more than their exact usage.
What I've learned and the mistakes I've made.
Sharing so you don't make them.
Here are the seven key lessons I learned from this expensive experiment with consumption pricing:
Complexity is a tax on revenue: Every additional variable in your pricing model increases confusion and reduces conversion rates. The cognitive load of understanding usage-based pricing often outweighs the perceived fairness.
Predictability beats precision: Customers value knowing their monthly costs more than paying the exact amount they "should" based on usage. Budget planning trumps usage optimization.
Support costs are hidden killers: Consumption pricing generates significantly more support requests. Every usage spike, billing question, and forecast request becomes a support ticket.
Sales cycles get longer: It's impossible to give prospects a clear price without detailed usage analysis. This extends demos and complicates the buying process.
Revenue forecasting becomes impossible: You can't predict monthly revenue when usage varies. This makes business planning and investor reporting much harder.
Most customers pay less, not more: Unless you have truly massive usage variation between customers, consumption pricing typically reduces average revenue per user.
Implementation costs are underestimated: Building billing systems, usage tracking, and support processes takes 3-5x longer than expected and requires ongoing maintenance.
The biggest lesson? Don't change pricing to fix product problems. If customers are churning or not converting, consumption pricing won't solve underlying product-market fit issues. Fix the product experience first, then optimize pricing.
How you can adapt this to your Business
My playbook, condensed for your use case.
For your SaaS / Startup
For SaaS companies considering consumption pricing:
Only consider it if usage varies 10x+ between customer segments
Test with a small subset before full implementation
Calculate total cost of ownership including billing complexity
Offer hybrid models with predictable minimums
For your Ecommerce store
For E-commerce businesses exploring usage models:
Consider transaction-based pricing for marketplace models
Test usage tiers for API or data-heavy products
Maintain simple subscription options alongside usage plans
Focus on volume discounts rather than pure consumption