Growth & Strategy
Personas
SaaS & Startup
Time to ROI
Medium-term (3-6 months)
So I'm going to be honest with you - I used to hate the idea of pay-as-you-go SaaS. You know, the whole "charge customers based on what they actually use" thing felt like a nightmare to forecast revenue. Give me that sweet, predictable monthly recurring revenue any day, right?
But then something happened that changed my entire perspective. I was working with this B2B SaaS client who was bleeding customers faster than they could acquire them. Beautiful product, solid features, but their flat-rate pricing was basically subsidizing their biggest users while scaring away smaller prospects who didn't need all those bells and whistles.
That's when I realized we were approaching this completely backwards. The subscription model isn't failing because it's bad - it's failing because we're applying it to everything without thinking about whether it actually makes sense for the customer.
Here's what you're going to learn from my experience navigating this shift:
Why the "everyone pays the same" model is actually hurting your growth
The real reason customers prefer usage-based pricing (hint: it's not about money)
How to implement pay-as-you-go without tanking your cash flow
What metrics actually matter when you're not chasing MRR anymore
The hybrid approach that lets you keep predictable revenue while offering usage flexibility
Look, I'm not saying subscription SaaS is dead. But if you're not at least considering usage-based models for your next product, you're probably leaving money on the table. Let me show you what I've learned from helping SaaS companies make this transition.
Reality Check
What every SaaS founder thinks they know about pricing
OK, so if you've been in the SaaS game for more than five minutes, you've probably heard the gospel of recurring revenue. Monthly subscriptions are the holy grail, right? Predictable income, easier forecasting, higher valuations - basically every SaaS metric that VCs love to see.
The traditional wisdom goes something like this:
Subscription models create predictable cash flow - You know exactly how much money is coming in each month
Flat-rate pricing is simpler to understand - Customers know what they're paying, no surprises on the bill
Higher customer lifetime value - Once someone's paying monthly, they tend to stick around longer
Easier sales conversations - No need to explain complex usage calculations or worry about bill shock
Better unit economics - You can optimize for a specific price point and build your entire business model around it
And you know what? This advice isn't wrong. For a lot of SaaS products, especially those with consistent usage patterns, subscription pricing makes total sense. Tools like Slack or Notion work great with per-seat pricing because usage is pretty predictable.
But here's where the conventional wisdom falls apart: it assumes that all SaaS products should follow the same pricing model, regardless of how customers actually use them. It's like saying every restaurant should charge a fixed monthly fee instead of charging per meal - sure, it might work for some cafeterias, but try explaining that to someone who only wants coffee once a week.
The problem is that most founders hear "recurring revenue" and immediately think "monthly subscriptions" without considering whether their product actually fits that model. They're optimizing for investor metrics instead of customer value, and that's exactly where things start to go sideways.
Consider me as your business complice.
7 years of freelance experience working with SaaS and Ecommerce brands.
So this client comes to me - let's call them CloudAnalytics because that's basically what they did. They'd built this really solid data processing platform that could handle everything from small CSV files to massive enterprise datasets. Beautiful product, great team, but they were stuck in what I call the "subscription trap."
Their pricing was classic SaaS: three tiers starting at $99/month for the "Starter" plan, $299 for "Professional," and $999 for "Enterprise." Sounds reasonable, right? Except their usage patterns were all over the place. Some customers would process hundreds of gigabytes one month and barely touch the platform the next. Others needed massive compute power for a few hours but then went quiet for weeks.
The real kicker? Their biggest customers were actually subsidized by their smallest ones. The enterprise clients were pushing the infrastructure to its limits but paying the same monthly fee whether they processed 10GB or 10TB. Meanwhile, small businesses who just needed to crunch some numbers occasionally were paying $99 for maybe an hour of actual usage per month.
I remember sitting in on a customer interview where this startup founder basically said, "Look, I love your tool, but I can't justify $299 a month when I only use it twice a month. I'd happily pay $50 per job, but this monthly thing makes no sense for us." That's when it clicked - we were solving the wrong problem.
The client was obsessing over MRR growth and churn rates, but they were missing the bigger picture. Half their customers felt like they were overpaying, and the other half felt like they were getting an unfair deal because the infrastructure costs weren't aligned with pricing. No wonder their Net Promoter Score was mediocre despite having a genuinely great product.
What really sealed the deal for me was when we looked at their customer acquisition costs. They were spending $400 to acquire customers paying $99/month, with an average lifespan of 8 months. The math just didn't work, especially when you factored in the infrastructure costs for their heavy users.
Here's my playbook
What I ended up doing and the results.
OK, so here's what we actually did. Instead of scrapping their entire pricing model overnight - because that would've been insane - we decided to test a hybrid approach with new customers first.
The strategy was simple: offer both subscription and pay-as-you-go options, then track which customers chose what and how their behavior differed. We set up three pricing tracks:
Traditional Monthly Plans - Kept the existing $99/$299/$999 structure for customers who wanted predictable billing
Pure Pay-as-You-Go - $0.10 per GB processed, $2 per hour of compute time, no monthly minimums
Hybrid Model - $49 base fee plus usage charges at 50% of the pure pay-as-you-go rates
The implementation wasn't as scary as we thought. We used Stripe's metered billing API to handle the usage tracking, and built a simple dashboard where customers could see their real-time usage and projected costs. The key was making everything transparent - no surprise bills, clear usage metrics, and the ability to set spending alerts.
For the usage tracking itself, we instrumented their API to capture two main metrics: data volume processed and compute hours consumed. Every job got tagged with these metrics, and we'd aggregate them at the end of each billing cycle. Simple stuff, really.
The interesting part was how we positioned it. Instead of framing it as "pay more when you use more," we positioned it as "only pay for what you actually need." The messaging focused on alignment and fairness rather than cost optimization.
We also had to rethink their onboarding process. With traditional SaaS, you can predict the user journey pretty well. With usage-based pricing, you need to help customers understand their usage patterns and set appropriate expectations about costs. We built a usage calculator that let prospects estimate their monthly bills based on their expected workload.
The backend changes were minimal - mainly adding usage tracking and billing integration. But the customer education piece was huge. We created detailed documentation about how billing worked, video tutorials showing the usage dashboard, and even a Slack channel where customers could ask billing questions in real-time.
One thing that surprised me was how much customers appreciated the transparency. Even if their bills ended up being higher than the old flat rate, they felt like they were getting fair value because they could see exactly what they were paying for. It's like the difference between an all-you-can-eat buffet and ordering à la carte - sometimes the buffet is cheaper, but people feel better about paying for exactly what they want.
Pricing Psychology
Usage-based pricing isn't just about cost alignment - it reduces the psychological barrier to trying your product because customers don't feel locked into paying for features they might not use.
Infrastructure Reality
Your biggest users are probably subsidized by your smallest ones with flat-rate pricing. Usage-based models ensure infrastructure costs align with revenue, improving unit economics.
Customer Segmentation
Different customer segments have vastly different usage patterns. Pay-as-you-go naturally segments customers by value delivered rather than arbitrary feature tiers.
Cash Flow Management
The key to successful usage-based pricing is helping customers predict and control their spending through usage alerts, budgets, and detailed real-time dashboards.
So here's what actually happened after we rolled this out. Within three months, about 60% of new signups chose either the pure pay-as-you-go or hybrid options. But the really interesting part wasn't the split - it was how customer behavior changed.
The pure pay-as-you-go customers ended up being our most engaged users. They'd start small, get comfortable with the platform, then gradually increase usage as they saw value. Average customer lifetime went from 8 months to over 18 months, and their usage patterns were much more organic.
Revenue per customer actually increased across all segments. The heavy users who were getting subsidized before now paid proportionally more, while light users paid less but stuck around longer because they didn't feel ripped off.
The hybrid model customers were the most predictable - they loved having a base amount included but appreciated the flexibility to scale up during busy periods without jumping to a whole new tier.
What really surprised us was the sales cycle. Traditional subscription sales took an average of 6 weeks because prospects had to justify a recurring expense and figure out which tier made sense. Pay-as-you-go customers were signing up and starting to use the product within days because the barrier to entry was so much lower.
What I've learned and the mistakes I've made.
Sharing so you don't make them.
This experiment taught me five key lessons that completely changed how I think about SaaS pricing:
Predictability matters more than total cost - Customers will pay more if they feel in control of their spending. The usage dashboard and spending alerts were more important than the actual rates.
Fair doesn't always mean equal - Heavy users were actually happier paying more because they felt like they were getting proportional value. Light users appreciated not subsidizing power users.
Billing transparency builds trust - Showing exactly what customers were paying for eliminated most billing disputes and actually increased satisfaction even when bills were higher.
Lower barriers increase experimentation - When customers don't have to commit to a monthly fee, they're more willing to try new features and push the platform's limits.
Usage patterns reveal product-market fit - Pay-as-you-go pricing gives you incredible insights into which features actually create value versus which ones are just nice-to-have.
The biggest mistake I see founders make is thinking usage-based pricing is just about the billing model. It's actually about aligning your revenue with the value you deliver. When customers pay based on outcomes rather than access, both sides are incentivized to maximize the actual value creation.
If I were implementing this again, I'd focus even more on the customer education piece upfront. The usage calculator and cost prediction tools were game-changers for conversion, but we should have built them earlier in the process.
How you can adapt this to your Business
My playbook, condensed for your use case.
For your SaaS / Startup
For SaaS startups considering usage-based pricing:
Start with a hybrid model to test customer appetite
Build usage tracking and billing transparency from day one
Focus on cost predictability tools, not just usage metrics
Test different usage thresholds to find optimal pricing points
For your Ecommerce store
For Ecommerce businesses exploring usage models:
Consider transaction-based pricing for payment or shipping tools
Implement volume discounts that scale with actual usage
Offer seasonal pricing that aligns with peak business periods
Track customer lifetime value based on transaction volume, not time