How Quartile-Based Pricing Doubled This SaaS Company’s Monthly Recurring Revenue Growth

Broadly speaking, you can grow your SaaS three ways: acquire more customers, retain more customers or charge more per customer. At Planio, we focused heavily on acquiring new customers via content marketing and retaining those customers via investing in product development and customer success.

And it worked. In January 2015 our monthly customer account churn rate averaged 2.49% and in January 2017 averaged 2.1%, a 20% reduction. While a lower churn rate is always better, it wasn’t clear that we could get any more big wins by reducing churn. Acquisition was steadily growing as our content efforts started paying off. The last lever—pricing—was one we hadn’t touched in seven years since Planio started, so it made sense to us that it might be the lowest hanging fruit.

Below, I’ll bring you through the process we took in analyzing data on our customer behavior. We’ll go into how we chose our new pricing model, and we’ll show you the exact impact on our monthly recurring revenue (MRR) growth with real figures.

The Importance of Pricing for SaaS Products

Particularly if you are a bootstrapped startup without VC funding, pricing will determine how much you can afford to spend on product development, customer success and product marketing. Wondering whether you can afford to build out an inside sales team for your SaaS? Jason Lemkin says you need to charge at least $299/mo as a rough rule of thumb.

Price Intelligently point out the paradox that, despite its importance, SaaS startups spend very little time at all on their pricing – they cite 6 hours. They also comment that “your pricing is the exchange rate on the value you’re creating in the world.”

This number of 6 hours made us think that we should dig into our pricing. We spent probably even less back then when we first started by simply copying the prices of a few similar tools back then.

Sources of Data on Our Pricing

When you have lots of competition, it’s easy to get trapped into analyzing what the others are doing. The reason this can be a mistake is that competitors’ approaches might not be a good fit for you. For example, their sales and marketing model might be very different to yours and this is reflected in their pricing. Once you reached a certain stage in your growth, you can also analyze how your own customers are using your product.

In Planio’s case, we have about 1,500 paying customers. That gave us a lot of data on how our customers were using our plans. We started analyzing the distributions across the various criteria that make up the plans: number of users, number of projects and storage space. Box plots are a handy way to get a quick sense of the distribution of the number of users each account is using:


The box plot above can give you a quick sense of how many users our customers typically had.

You can see that the median is at 9 users, whereas the highest amount (excluding outliers) is at about 48 users. At the same time, our pricing plans at the time ranged from 6 users at the bottom end to 100 users at the top end.


When we compared the box plot above to our pricing plans, there was a clear disconnect:

  • 75% of our customers has 30 users or less, so they fit within the bottom two plans;
  • 40% of our customers had less than 6 users, so they fit within our bottom 9 euro/month plan.

The result of this disconnect was that a customer with a team of 7 was paying the same as a customer with a team of 30. At the same time, we had almost no customers with more than 48 users.

Our conclusion was that our pricing scale was not calibrated to our customers’ behavior. It was time to make some changes.

Paralysis by Analysis

At the time Planio’s founder, Jan, and I were staring at endless Excel sheets. A big question in our mind was whether we should increase the price on all our customers at once, or whether we should grandfather older customers and just have the new pricing model for newer customers.

Obviously, giving all customers an ultimatum of “pay an increased price or leave” might result in a lot of customers leaving – maybe even angrily. I recommend this approach anyways if you want to see exactly who values your product by sticking with it at the higher price. I think this approach might work if you have a limited amount of time to find product/market fit before you run out of funding runway. The reason is that your current customer base will just be a tiny fraction of your future customer base if your startup is successful.

But we’re bootstrapped, so there wasn’t an intense pressure for future rounds of funding. It also didn’t feel fair on our customers to give them this ultimatum. Then, we stumbled on a very simple solution that seemed the most fair to us.

The Quartile-Based Approach We Took

Going back to the quartiles from the box plot, we noticed that we could segment our customer base into four quarters taking the 25th, 50th and 75th quartiles as the boundaries between the plans.

quartile-based-plansThis shows how our new pricing plans line up with the four quarters.

We then created four quarters based on these points in the data, which would become the new plans. We also increased the pricing of our lowest plan on the basis that charging any business about 9 dollars a month for software core to their business is ranking it lower in value than the air freshener they use in the bathroom.

De-Risking the Pricing Experiment

Honestly, I found it stressful to change our pricing model. You’re tweaking with the revenue engine of an entire business. If things go wrong, the impact can be quite serious.

In our case, we reduced the risk of this pricing experiment by grandfathering existing customers, meaning that they could keep their existing plan. That meant that if the new pricing model turned out to be a fiasco, we could just roll-back a small number of new customers to the old model.

At the same time, we obviously limited our upside: if all our existing customers moved over to our new pricing model without a significant amount of cancellations, we’d stand to increase our monthly recurring revenue overnight by a significant amount.

I think if your SaaS has only been around for a couple of months, you can afford to be more aggressive with testing out new pricing models without grandfathering existing customers. Whether people stay with the new model or not is important data as you grow. In our case, we felt that we didn’t need or have to take that risk, because Planio is a bootstrapped company with 7 years of happy customers and we actually value growing slowly and steadily.

The second way we reduced the risk was to add more value to our existing plans. Previously, we had charged extra for our Team Chat and Customer Helpdesk features. We felt that these features added significant value, but customers were hesitant to pay extra for them, so we rolled them into the standard plans.

With these changes made, we deployed the new pricing changes on February 1, 2016:

planio-pricing-page-2We changed the amount of users for each plan according to the quarters shown in the chart above.

The Results of the Pricing Experiment

After we switched over to the new pricing model, we waited for the emails and phone calls to roll in. I imagined hordes of discontented customers pounding down our doors.

But what really happened?


Just for the sake of comparison, we once changed the colors in Planio for default avatars to a selection of pastels, including a range of pink. That change unleashed two phone calls within an hour from (male) CEO’s fearful of suffering the stigma of a pink Avatar.

The impact of the change in pricing on our growth was, however, immediate.

An important metric for us is the average monthly recurring revenue we get per new customer. It tells us that in a certain month, a new customer bought a subscription worth, say 30 euro, on average.

As you can see below, the introduction of the new pricing model significantly increased the average monthly recurring revenue per new customer. Whereas the average MRR per new customer was €24.71 over the previous five years, it went up by over 100% to an average of €50.68 for the 12 month period after the pricing change.


Did this increase our churn rate?

Well in Planio’s case, churn went from 2.49% in January 2015 before the pricing change to an average of 2.1% as of January 2017.

There were some issues for customers who’d considered Planio before the pricing changes but then only signed up after February 1, 2016. We resolved those complaints by just giving them the old plans.

Analyze Your Pricing and Test New Approaches

Our new pricing model at Planio means that we are better at segmenting our customer value based on our customer needs. A small dev shop with 7 people is no longer paying the same as a division of a multinational with 30 people.

Once you’ve reached a certain level of customers, you can start using tools such as Kissmetrics to see whether your pricing segments are matching your customers and how they use your product. The impact on your growth rate will be significant for the business.

It’s also an ongoing process. In our case, we’ve evolved our pricing pricing several times since the experiment above. For instance, we now accept US dollars and Japanese Yen in addition to Euro, so time will tell how those experiments plays out.

In terms of leverage, a few hours a month spent on analyzing and reviewing your pricing may have outsized results.

About the Author: Thomas Carney works on growth at Planio, a task tracking tool for keeping product development and customer support in sync. You can read about productivity, getting more done, and work hacks over at the Planio blog.

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