'''# I A/B Tested 10 Different SaaS Pricing Models: The Surprising Winner
Your pricing page is lying to you.
There, I said it. It’s probably the most neglected, yet most critical, page on your entire site. We spend months building a product, weeks designing a landing page, but when it comes to pricing? We slap on a few tiers, copy our competitors, and call it a day. I know, because I’ve done it. And it cost me. Big time.
Back at RemoteTeam, before the acquisition by Gusto, we hit a plateau. A nasty one. Our growth stalled, churn was creeping up, and our CAC was heading in the wrong direction. We had a great product, a solid team, and happy customers. But the engine wasn’t firing on all cylinders. The problem wasn't the product; it was the packaging. It was the price.
So we decided to do something radical. We decided to stop guessing and start testing. We launched a six-month-long A/B testing marathon, pitting 10 different SaaS pricing models against each other. The results were not what we expected. Not even close. The model that won, the one that broke our plateau and kicked off our next phase of hyper-growth, was one we almost didn’t even test.
I’m going to walk you through the entire experiment. The good, the bad, and the ugly. I’m sharing our methodology, the data, and the hard-won lessons. No fluff. Just the real story of how we found our pricing sweet spot. '''
The Setup: Our Growth Engine Was Sputtering
Let me paint you a picture. It was Q3 2021. RemoteTeam had solid Product-Market Fit. Our platform for managing remote employees was getting rave reviews. We had just crossed the 1,000-customer mark. On the surface, everything looked great. But when I looked at the dashboard, the numbers told a different story. A scary one.
Our Monthly Recurring Revenue (MRR) growth had slowed to a crawl. We were stuck at around 2% month-over-month growth. For a venture-backed startup, that’s a death sentence. Our churn rate, which had been a healthy 3%, was now creeping towards 5%. And our Lifetime Value (LTV) to Customer Acquisition Cost (CAC) ratio, the holy grail of SaaS metrics, had dipped below 3:1. We were spending more to acquire customers who were leaving faster and paying us less over time. Not a good look.
We were stuck in the classic "good-not-great" SaaS trap. Our pricing was a simple three-tiered system based on the number of seats. It was easy to understand, easy to implement, and it had worked well for us in the early days. But it wasn ''' was no longer aligned with the value our customers were getting from the product.
Our biggest customers, the ones using our platform to manage hundreds of employees across the globe, were paying the same as a small startup with 10 people. We were leaving a ton of money on the table. At the same time, our pricing was a barrier for smaller teams who only needed a subset of our features. They were churning because they were paying for things they didn’t need. The model was broken at both ends of the market.
We knew we had to make a change. But to what? A quick search for "SaaS pricing models" gives you a million different options. Everyone has an opinion, but very few have data. We decided we needed data. Our data.
The Contenders: 10 Pricing Models Enter, One Leaves
We assembled a small tiger team: a product manager, an engineer, and a data analyst. The mission: to design and run a definitive pricing experiment. We chose 10 models to test. It was a mix of common models, a few variations, and one wild card. We ran the experiment over six months, using a combination of multivariate testing on our pricing page and direct outreach to new customers.
Here’s the lineup:
- The Control: Classic Per-Seat. Our existing model. A simple price per user, per month. Predictable, but as we saw, flawed.
- The Competitor: Feature-Gated Tiers. The classic Good, Better, Best. We re-packaged our features into three distinct tiers, hoping to drive upsells.
- The Meter Reader: Pure Usage-Based. No more seats. We priced based on a core value metric. For us, it was the number of "actions" completed in the platform (e.g., payroll run, new hire onboarded).
- The Active User. A twist on per-seat. You only pay for users who log in and use the product in a given month. This seemed fairer, but I was worried about revenue predictability.
- The Foot-in-the-Door: Freemium. A generous free plan with limited features, designed to capture a wide top-of-funnel and convert them later. A classic product-led growth (PLG) play.
- The All-You-Can-Eat: Flat-Rate. One price. All features. Unlimited everything. Simple and bold. I liked the clarity, but it felt like we’d be leaving money on the table again.
- The Hybrid: Base Fee + Usage. A fixed platform fee each month, plus a variable component based on usage. This seemed like a good way to balance predictability for us and fairness for the customer.
- The Value Prop: Value-Based. This one was tricky. We tried to tie the price directly to the ROI the customer got. For example, we calculated how much they saved on compliance costs and charged a percentage of that.
- The No-Commitment: Pay-As-You-Go. No monthly subscription at all. Just a pure transactional model. Customers buy credits and use them for different actions.
- The Wildcard: Reverse Tiered. This was our crazy idea. The more seats a customer added, the cheaper the price per seat became. The goal was to incentivize massive adoption within a company. Total land-grab strategy.
We had our contenders. We set up the tracking, built the different pricing pages, and held our breath. The next few months were a rollercoaster. '''
The Results Are In: And We Were Wrong About Everything
Every week, our little tiger team would huddle around the dashboard. At first, the numbers were all over the place. Some models got a lot of sign-ups but low revenue. Others had high Average Revenue Per Account (ARPA) but a terrible conversion rate.
Freemium, for example, was a lead-generation machine. Our top-of-funnel exploded. But the conversion rate to paid was abysmal, less than 1%. It was a classic case of attracting freebie-seekers, not serious customers. The support load was also a nightmare. A total failure.
Pure Usage-Based was another interesting one. Our power users loved it. Their bills went up, but they didn't mind because the value was so clear. But for smaller customers, the unpredictability was a huge issue. They couldn't budget properly. Our conversion rate for smaller companies dropped by 50%. Another dead end.
As the months went on, a clear loser emerged: our old Per-Seat model. It was consistently outperformed by almost every other model on the key metrics of conversion rate and expansion revenue. That alone was a huge validation for the whole experiment.
But the winner? It shocked us all.
And The Winner Is... The Hybrid Model
The winning model, by a long shot, was the Hybrid: Base Fee + Usage. It wasn't the sexiest. It wasn't the simplest. But it worked. And it worked beautifully.
Here’s how we structured it:
- A modest base platform fee. This gave us predictable revenue and ensured that customers had some skin in the game. We had three tiers for the base fee, which unlocked different sets of features (similar to a feature-gated model).
- A usage-based component. This was tied to our core value metric: the number of active employees managed on the platform.
This model gave us the best of all worlds. The base fee provided a stable, predictable revenue stream. The usage component meant that as our customers grew, our revenue grew with them. It aligned our success with our customers' success.
The results were staggering. Compared to our old per-seat model, the new hybrid model resulted in:
- A 35% increase in ARPA. We were finally capturing the value our larger customers were getting.
- A 20% increase in conversion rate. The lower base fee made it easier for smaller companies to get started.
- A 50% reduction in churn. Customers were no longer churning because they were paying for things they didn't need. The pricing felt fair.
- A 150% increase in Net Revenue Retention (NRR). This was the big one. Our existing customers were spending more and more with us over time. That’s the holy grail of SaaS.
We had found our growth engine. The plateau was broken. In the quarter after we rolled out the new pricing, our MRR growth jumped from 2% to 8%. It was the start of a whole new chapter for RemoteTeam, and it was a direct result of this experiment. It was the confidence from this success that eventually led to our acquisition by Gusto.
Why Did The Hybrid Model Crush It?
Looking back, it seems obvious. But at the time, we were so focused on the extremes – pure usage-based, pure per-seat – that we missed the power of the middle ground. The hybrid model worked because it solved the core tension in SaaS pricing: the need for predictability on the vendor's side and the desire for fairness on the customer's side.
Think about it from the customer's perspective. A pure usage-based model can be scary. If you have a big month, your bill can skyrocket unexpectedly. It makes it hard to budget. A pure per-seat model feels unfair if you have a lot of inactive users or if the value isn't tied to the number of users. You end up paying for shelf-ware.
The hybrid model solves both problems. The base fee gives the customer a predictable cost they can budget for. The usage component ensures they only pay more when they are getting more value from the product. It’s a win-win. It builds trust. It makes the customer feel like you are on their side.
From my side of the table, it was a dream. The base fee gave me a floor for my revenue, making my forecasts much more accurate. The usage component gave me a direct share in my customers' success. When they grew, I grew. It turned my pricing model into a growth lever, not just a way to collect money. It also forced us to be laser-focused on our value metric. We had to be sure that the thing we were charging for was the thing that our customers valued the most. That alignment is priceless.
Your Turn: How to Run Your Own Pricing Experiment
I didn’t write this just to tell a story. I wrote this to convince you to stop guessing with your pricing. You don’t have to run a massive, six-month, 10-model experiment like we did. But you have to do something.
Here’s a simple framework to get you started:
Identify Your Value Metric. This is the most important step. What is the one metric that best represents the value your customers get from your product? Is it the number of projects, the amount of data stored, the number of transactions processed? It's probably not the number of seats. You need to have some tough conversations internally and with your customers to nail this. If you get this wrong, nothing else matters.
Pick 3-4 Models to Test. Don’t go crazy like we did. Pick a few contenders. I’d recommend starting with your current model as a control, a feature-gated tier model, and a hybrid model based on your value metric. That’s a great starting point.
Use a Phased Rollout. Don’t just flip a switch and change the pricing for everyone. That’s a recipe for disaster. Start by showing the new pricing models to a small percentage of your new sign-ups. 5-10% is a good starting point. Use a tool like Optimizely or build your own simple A/B testing framework.
Measure Everything. Track not just the conversion rate, but also ARPA, churn, and expansion revenue for each cohort. You need to look at the full picture. A model that has a high conversion rate but high churn is a loser. You need to track these cohorts for at least a few months to see the real impact.
Talk to Your Customers. The numbers will tell you what is happening, but they won’t tell you why. Get on the phone with customers who saw the new pricing. Ask them what they thought. Was it clear? Was it fair? Their qualitative feedback is just as important as the quantitative data.
This isn’t a one-time project. Your pricing should evolve as your product and your market evolve. We didn’t stop with this experiment. We were constantly tweaking and testing. Pricing is a process, not a project.
Stop Guessing, Start Winning
I’ve invested in over 200 companies. I’ve seen hundreds of pitch decks. And the pricing slide is almost always the weakest. It’s an afterthought. A necessary evil. That’s a huge mistake. Your pricing is not just a way to make money. It’s a way to communicate your value. It’s a way to align your success with your customers’ success. It’s one of the most powerful growth levers you have.
We unlocked a new phase of growth at RemoteTeam not by building a new feature, but by changing a few lines of text on our pricing page. It was the highest-leverage project we ever did. Stop leaving money on the table. Stop guessing. Go run the experiment. You might be surprised by what you find.
Frequently Asked Questions
What experience informs this perspective?
This perspective comes from over a decade of building companies in Silicon Valley, two successful exits (RemoteTeam to Gusto, MovieLaLa to Gfycat), and investing in 200+ startups including Anthropic, OpenAI, and Scale AI. I write about what I've lived.
Do all experts agree with this view?
No, and that's fine. The best ideas in business are often contrarian. I share my perspective based on my experience and data, but I encourage you to seek out opposing viewpoints and form your own conclusions.
How has this view evolved over time?
My thinking on most topics has changed significantly over the years. Early in my career, I held many conventional views that experience proved wrong. I try to update my beliefs when the evidence changes.
What's the most common pushback you get on this?
People often push back by citing exceptions or edge cases. And they're usually right that exceptions exist. But building a strategy around exceptions rather than patterns is a losing game for most founders.