Software may be eating the world, but capturing its true value depends on pricing. In years gone by, perpetual licences were standard for B2B software. Then there was a sea change towards recurring subscriptions – the SaaS revolution. But now, we’re seeing increasing deployment of usage-based pricing (UBP) within the SaaS space.
This is often linked to outstanding performance. SaaS businesses with UBP have experienced 29.9% year-on-year revenue growth compared to 21.7% for the wider SaaS ecosystem, along with net revenue retention (NRR) of over 120% compared to 110% across the rest of the industry. And seven out of the nine SaaS IPOs in the last few years with the best NRR – companies like Datadog and Snowflake – operated usage-based pricing models.
Source: OpenView 2021 Financial & Operating Benchmarks Survey
As a result of this growth and best-in-class NRR, usage-based public SaaS companies are valued at a substantial premium compared with the broader SaaS index, with average revenue multiples at 21.6x vs. 14.4x, according to OpenView Partners.
What’s going on here? In this short primer, we’ll:
Describe what usage-based pricing is
Highlight trends that are driving its adoption
Explain its advantages
Review common challenges
With usage-based pricing, the cost of a service is based on the customer’s consumption. Rather than paying for expected need (i.e. capacity) the customer pays only for what they actually consume (usage).
If this sounds familiar, that’s because it’s the standard way of pricing in verticals like utilities, telecommunications, and logistics. What's new is its application to B2B software.
More ‘pure’ examples are easy to spot. AWS and Snowflake charge based on resources consumed. HubSpot’s pricing is based on the number of leads their customers generate. Zapier charges by task. Twilio by API call.
But it’s applied more subtly, too. Pricing models that primarily have feature-based tiers or ‘seat’ fees but also allowances for usage with overage charges are deploying UBP.
As with all market trends, it’s partly imitation: pioneering companies have success and act as pathfinders, with others following. But there are also fundamental shifts that create increasingly favourable conditions for UBP.
Firstly, the rise of the 3 A’s: Automation, APIs, and AI. Increasingly ‘service users’ are machines rather than people. This is true not just in the infrastructure and middleware layers of the stack, but at the application layer too. In this context, services have to scale their value by usage and impact, rather than the number of people.
Secondly, the rise of Product-Led Growth (PLG). Key to this approach is low-friction, self-service adoption, where the buyer is the end user. In a B2B context, this means initial purchasing decisions can be decentralized and made absent of sales contact - a single person can find a product they like using, creating a beachhead that can eventually result in a company-wide engagement. UBP works well in this context, as it minimizes barriers standing in the way of initial adoption and provides a scaling path that is also independent of Sales.
In summary, usage-based pricing works because it enables value-based pricing and directly scales as a customer gets more successful. But it’s worth breaking out the elements.
There are few barriers to UBP adoption. If costs scale with usage, they’ll be trifling at first use. There’s also no need for a customer to estimate what their needs might be (i.e. what capacity they need), avoiding mental ‘work’ and fear of loss. This makes it easier for individuals or companies to adopt your service, encouraging evaluation and experimentation, and expanding your addressable market.
You can grow revenues from your customers without additional sales effort. As a customer uses more, they pay more, with no intervention required from Sales. This increases the efficiency and profitability of your go-to-market.
For the avoidance of doubt, Sales still very much has a role in UBP. But it can focus on genuine value-adding activities (facilitating adoption, securing commitments, upselling) rather than gatekeeping busywork.
With usage-based pricing, your customers won’t be concerned about shelfware, waste, or failing to glean the full value from their purchase. They just scale their usage and spend up or down depending on their needs.
But more importantly, if you’ve chosen the right pricing metric that aligns with the customer’s target outcomes (more on this below), their cost will only increase if they are successful themselves. And that makes them tolerant of spend increases, just as they are with COGS – it’s the cost of winning.
If you are a software company that has significant costs driven by your customers’ usage (e.g. cloud infrastructure costs or third party APIs), UBP allows you to keep tighter control of margins. With the right pricing metric, you can link both your revenues and your costs to usage, delivering more consistent unit economics per customer.
Usage-based pricing isn’t right for all software companies. For many, the more traditional licensing or subscription approaches might be a better fit. And even if it does suit your service and operating model, there are challenges and pitfalls to be aware of.
You need to attach pricing to a usage vector that aligns with how your customers derive value from your service and how they see success. That ensures their spend with you is associated with positive business outcomes. If you get this wrong, your fees can get out-of-step with their KPIs, and you become a cost item to be managed downwards.
Your fees also need to be simple to understand and easy to predict. If not, how their spend would scale becomes opaque, and that creates adoption (or additional commitment) friction.
To provide an example, let’s say you offer a backend-as-a-service to mobile games. If you price based on the number of players they attract, this overlaps well with their own metrics for success - it’s ‘good’ spend that is easy to understand, and forecasting is simple.
Some customers value predictability. They like to budget spend with confidence, and feel uncomfortable with the uncertainties of UBP – the ‘taxi meter effect’. The same is true of particular buying personas, such as Procurement teams.
Other customers might be fine with usage-based pricing in principle, but if they underestimate their usage or have an unexpected spike, they may get a nasty surprise in their monthly bill. ‘Sticker shock’ is a risky moment that could trigger reappraisal.
The good news is that there are common sense mitigation strategies. You can deploy hybrid models that combine subscription elements with allowances and overages rates, as Zapier does. You can provide customers with an option to trade commitments (which sets a floor) for discounts on variable rates (limiting the potential for runaway costs), as AWS does. You can ignore infrequent usage spikes, as Datadog does. Or you can proactively reach out to customers who show a-typical usage patterns to help them manage their spend.
Companies who deploy UBP need to be usage and pricing data centric. It’s the lifeblood of the organization, needing to be captured and delivered in the right form to other systems. Unfortunately, there’s a gap in the stack – so this generally requires bespoke development and maintenance overhead. [Full disclosure - m³ter was founded to address this gap.]
Billing operations is a challenge in UBP scenarios, particularly for companies with sales-led motions that result in bespoke deals for customers. Usage data needs to be brought together with commercial deal terms in order to calculate the amounts to be passed to billing systems. It’s not uncommon for even large organisations to have manual spreadsheet-based systems to achieve this.
There’s a customer experience (CX) challenge because pricing becomes part of the product - customers need up-to-date information about their usage and how it is converting to spend. That means a ‘live’ dashboard and granular reporting, not just one bill per month.
Similarly, Sales teams need up-to-date information about customer usage to inform conversations and proactively identify opportunities or risks associated with changes in usage patterns. And FP&A (Financial Planning & Analysis) teams need to understand customer usage and how it converts to revenues and cost in order to manage the business effectively.
Usage-based pricing has less predictable revenues than traditional SaaS because it depends on the vagaries of usage. It can also introduce working capital challenges because it is more likely to involve payments in arrears (i.e., after usage occurs) rather than upfront. Both effects can be mitigated to an extent by trading commitments for discounts, but the inherent uncertainties make it harder to make investment decisions or provide guidance to investors.
Software companies are increasingly turning to usage-based pricing to capture their true value, driven in particular by trends in automation and Product-Led Growth. It works because it enables value-based pricing that scales easily with a customer’s success, but it needs to be designed well, and it also requires new operational and GTM capabilities.
Our goal at m3ter is to help customers with these challenges so they can take full advantage of the opportunities of usage-based pricing. Want to discuss how our metering and pricing engine for SaaS companies can work for you? Talk to our team for a demo, answers to your questions, or to learn our best practices 1:1.
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