Growth & Strategy
Personas
SaaS & Startup
Time to ROI
Medium-term (3-6 months)
Last year, I had a conversation with a B2B SaaS client that completely changed how I think about pricing models. They were burning through cash with their traditional subscription tiers while their biggest customers barely used half the features they were paying for.
Here's what made it worse: their smallest customers were hitting usage limits constantly, creating support nightmares and churn. Sound familiar? You're probably dealing with the same misalignment between what customers pay and what they actually use.
That's when we decided to experiment with something the SaaS world rarely talks about honestly: feature usage billing. Not consumption-based pricing, not seat-based tiers, but charging customers based on which specific features they actually use and how much.
The results? Customer satisfaction went up, churn decreased, and revenue became more predictable. But getting there required challenging everything we thought we knew about SaaS pricing. Here's what you'll learn from our experiment:
Why traditional SaaS pricing is fundamentally broken for most businesses
The real difference between usage billing and feature usage billing
A step-by-step framework for implementing feature-based pricing
The mistakes that will kill your feature billing experiment
When to stick with traditional pricing (and when to run)
Fair warning: this approach isn't for everyone. But if you're tired of the one-size-fits-all subscription model, this might be exactly what your SaaS needs. Check out our other SaaS growth strategies for more unconventional approaches.
Industry Reality
What every SaaS pricing "expert" will tell you
Every SaaS pricing consultant will give you the same playbook. Start with three tiers: Basic, Professional, and Enterprise. Add some features to each tier, price them at $9, $29, and $99 per month, and watch the money roll in.
The conventional wisdom goes like this:
Simplicity sells - customers hate complex pricing
Predictable revenue - monthly recurring revenue is king
Upselling is easy - move customers up tiers naturally
Billing is straightforward - same amount every month
Customer acquisition cost - you know exactly what a customer is worth
This advice exists because it worked for the SaaS pioneers. Salesforce, HubSpot, and Slack all use variations of this model. It's been battle-tested by companies that are now worth billions.
But here's where this conventional wisdom falls apart: most modern SaaS products aren't like those pioneers. Your customers don't use your product the same way every month. They don't need all the features all the time. And they definitely don't fit neatly into three usage patterns.
The result? You end up with customers who feel like they're overpaying for features they don't use, while your power users hit arbitrary limits and get frustrated. Meanwhile, you're leaving money on the table from customers who would happily pay more for the specific features that drive their business results.
That's exactly where my client found themselves - stuck between unhappy customers and unpredictable revenue. Time for a different approach.
Consider me as your business complice.
7 years of freelance experience working with SaaS and Ecommerce brands.
The client was a B2B automation platform - think Zapier but for a specific industry vertical. They had built this incredibly powerful tool with dozens of features, from basic workflow automation to advanced analytics and AI-powered insights.
Their pricing looked textbook perfect: Starter ($49/month), Professional ($149/month), and Enterprise ($499/month). Each tier had more features, higher limits, and better support. Classic SaaS pricing 101.
But when I dug into their metrics, the picture was ugly:
Their Starter customers were constantly hitting workflow limits and churning after 2-3 months. These weren't price-sensitive customers - they were running successful businesses. They just needed more of the basic automation features, not the advanced analytics they couldn't access anyway.
Meanwhile, their Enterprise customers were paying $499/month but only using about 30% of the available features. Most never touched the advanced AI tools or the premium integrations. They were essentially paying for a Mercedes but driving it like a Honda Civic.
The worst part? Their best prospects - mid-market companies - couldn't justify the jump from $149 to $499, even though they desperately needed just 2-3 specific advanced features. The gap was too big, and the feature bundling made no sense for their use cases.
We tried the obvious fixes first. Added a "Growth" tier at $299. Created usage-based pricing for workflows. Even experimented with seat-based pricing. Nothing moved the needle significantly because we were still thinking inside the subscription box.
That's when I started questioning whether the subscription model itself was the problem. What if instead of selling access to feature bundles, we sold access to the specific features customers actually wanted to use?
Here's my playbook
What I ended up doing and the results.
After months of customer interviews and data analysis, we designed a completely different approach. Instead of traditional tiers, we implemented what I call "feature usage billing" - customers pay a base platform fee plus usage-based charges for specific advanced features.
Here's the exact framework we built:
Base Platform Access ($39/month)
This included core workflow automation, basic integrations, and standard support. Think of it as the cost of keeping the lights on and providing the fundamental value proposition.
Feature Usage Credits
Advanced features required credits: AI analysis (5 credits per report), premium integrations (2 credits per connection), advanced analytics (10 credits per dashboard), custom webhooks (1 credit per setup).
Credit Packages
Instead of monthly subscriptions, customers bought credit packages: 100 credits ($50), 500 credits ($200), 2000 credits ($600). Credits never expired and could be used across any features.
Usage Transparency
Real-time dashboard showing credit usage, feature costs, and projected monthly spend. No surprises, no hidden fees, complete visibility into what drives their bill.
The implementation required significant technical work. We had to rebuild the billing system, create usage tracking for each feature, and design new onboarding flows. But the hardest part wasn't technical - it was psychological.
We spent weeks crafting the messaging. "Pay for what you use" sounded logical, but customers initially worried about unpredictable bills. We had to position it as "pay for what creates value" and provide tools for them to monitor and control their usage.
The rollout was gradual. We offered existing customers the choice to switch or stay on their current plans. New customers got the feature usage model by default, but with a "safety net" - we'd cap their first month at their expected budget and help them optimize usage patterns.
Within 60 days, something remarkable happened. Customer conversations shifted from "this is too expensive" to "how do I get more value from these features?" They were thinking about ROI instead of cost.
Billing Logic
Base platform + feature credits system
Customer Control
Real-time usage dashboard with spending caps
Revenue Impact
Increased ARPA while reducing churn significantly
Implementation
Gradual rollout with existing customer choice
The results exceeded our expectations. Average revenue per customer increased by 34% within the first quarter, not because we raised prices, but because customers could finally access the high-value features they needed without paying for everything they didn't.
Customer satisfaction scores jumped from 6.8 to 8.9 out of 10. The biggest improvement came from mid-market customers who previously felt stuck between inadequate and overpriced plans. Now they could scale their usage naturally with their business needs.
Churn decreased by 23% in the first six months. Exit interviews revealed that customers appreciated the transparency and control. They knew exactly what they were paying for and could adjust their usage based on business priorities.
Perhaps most importantly, sales conversations became consultative rather than confrontational. Instead of defending pricing tiers, our sales team could focus on identifying which features would drive the most value for each prospect. The pricing model became a sales tool rather than a sales obstacle.
Revenue predictability actually improved despite the variable pricing. Credit purchases created cash flow in advance of usage, and the usage patterns became predictable within 3-4 months for each customer segment.
What I've learned and the mistakes I've made.
Sharing so you don't make them.
The biggest lesson: customers want control, not just value. Traditional SaaS pricing forces customers into predetermined usage patterns. Feature usage billing lets them optimize their investment based on actual business needs.
Here's what I learned from this experiment:
Start with high-value features - Don't make core functionality usage-based. Only advanced features that clearly drive ROI should require credits.
Transparency is everything - Usage dashboards and spending alerts are mandatory. Customers need to feel in control of their costs.
Pricing psychology matters - Credits feel different than direct billing. They create a psychological separation that reduces price sensitivity.
Granular tracking is complex - You need robust analytics to track feature usage accurately. Invest in the infrastructure first.
Customer education is critical - Spend time teaching customers how to optimize their usage. This becomes a retention tool.
Not all features work for this model - Simple features should remain unlimited. Only charge for genuinely advanced or resource-intensive capabilities.
Have a safety net - Offer spending caps or budget alerts to help customers manage costs, especially during the first few months.
This approach works best for SaaS products with clear feature differentiation and customers who have variable usage patterns. It doesn't work for simple tools or products where all features are equally important.
How you can adapt this to your Business
My playbook, condensed for your use case.
For your SaaS / Startup
For SaaS companies considering this model:
Start with your most advanced features that clearly drive ROI
Build robust usage analytics before changing pricing
Test with a small customer segment first
Create clear cost calculators and spending controls
Position as "pay for value" not "pay per use"
For your Ecommerce store
For ecommerce platforms with SaaS components:
Apply to advanced analytics, AI recommendations, or automation tools
Keep core commerce features unlimited
Tie pricing to revenue impact (% of sales generated)
Offer feature bundles for predictable monthly costs
Use during peak seasons to optimize feature investment