Implementing Usage-Based Pricing: What Your Financial Teams Need to Know
I joined Datadog as VP Finance back in 2015 when the company was still very small. Back then, the company had about 100 employees, was making around $20 million ARR, and only had one product—Datadog’s flagship infrastructure monitoring service.
By the time I departed from the company in September 2020— just one year post-IPO—Datadog, an OpenView portfolio company, had around 3,000 employees and was approaching $1 billion in ARR, with a growing line of nearly 25 products.
Usage-based pricing (UBP) has been a part of Datadog’s business since the beginning. Even today, the infrastructure monitoring product is priced on a “price per host monitored” basis, and the pricing model also accounts for discounts based on annual commitment, volume, and tier.
The impact of UBP was reflected in the company’s success. Customers saw a lot of value in the product and could start using it very quickly. The pricing model incentivized them to use more of our product, allowing Datadog’s top line to really take off.
Strategize to allow for maximum flexibility and transparency
One reason Datadog was able to see market success so quickly is because usage-based pricing removed a lot of friction for adoption. For customers, getting started was easy and with an emphasis on flexible usage, staying with Datadog was a no-brainer.
A lot of customers were starting with x number of EC2 instances on AWS that they wanted to monitor. Many of these customers were part of rapidly growing companies where new applications were being built every day. With Datadog, they found that they could easily increase their usage to monitor these additional applications as their overall infrastructure needs increased.
Datadog’s pricing also accommodated natural ebbs and flows within the customers’ businesses. Say a game development company released a hit game and suddenly required more host monitors to ensure that it was performing with optimal uptime and latency. They could ramp up their host usage for a period, but like most online games, when the popularity eventually trailed off, they could easily dial down the hosts they monitor.
Pricing transparency was also a huge selling point. We had our prices listed directly on our website and had a whole FAQ section on pricing. With most of our early competitors, potential customers had to talk to somebody for a quote.
Manage expectations for predictability
Although it’s true that UBP can make for an excellent customer experience, from a purely financial perspective, it isn’t all roses. Predictability is something every company strives for—especially in the finance department. Answering questions about what the top line is going to grow to as new logos are added, or as existing logos expand, can be a lot more challenging with UBP.
If we consider the game development company example from earlier, the question arises of how could the finance department know if this company will have a hit game—or zero? Or five? Or ten? This lack of predictability is largely out of the hands of the finance teams.
Datadog implemented a drawdown model option that allows customers to adapt their usage pace according to the needs of their business. This helps to balance the business’s need for predictability with the customer’s need for flexibility.
With this drawdown model, customers can commit a certain sum, say $1 million, pick a term, and “draw down” on their sum over that time period. They have the freedom to use zero dollars in the first six months of their three-year term to account for business delays that have nothing to do with Datadog. And as soon as they’re up and ready, they can go as fast as they want.
Having commitment built into the pricing model can certainly mitigate some of these concerns around predictability, but it’s far from perfect. First of all, not all customers elect this type of plan. Second, relying exclusively on monthly commitments in your calculations will lead to pretty inaccurate numbers.
I think of it kind of like your cellular data plan. You might commit to paying for a certain amount of data a month, but if you exceed this amount, you incur additional costs. Your mobile provider can count on the recurring revenue of the cost of your monthly plan, but they can’t predict whether or not there will be overages or how big these overages will be.
Sell your investors on UBP
How does this dynamic of unpredictability impact investor relations? Generally, investor relations tend to be more contentious when you’re giving guidance or forecasting. Your projections might be based on sales capacity, number of new logos, or expansion deals, but UBP companies tend to either haircut that or be more conservative.
When you’re chatting with investors in a boardroom, though, they just want to know realistically—or even optimistically—what these numbers could be. Responding with “I don’t know” or “I can really only estimate” can lead to some tough conversations, especially when so many SaaS companies are prone to overestimating.
But predictability aside, Datadog’s investors actually saw the usage-based revenue model as a highlight. As it turned out, they loved the opportunity to talk about the ubiquitous nature of a metric that has nothing to do with pricing but everything to do with adoption, performance, and virality.
Your product and platform’s intrinsic virality gives your investors confidence in continual top-line growth. And the ability to not only win new logos but to keep customers using your product, speaks volumes.
Datadog’s net dollar retention rates are off the charts—and that’s a metric that every high-growth SaaS company evaluates. Datadog publicly discloses that they are north of 130% each quarter, which keeps investors pretty happy.
Redefine metrics to fit the UBP model
What everyone loves about SaaS companies is that they all operate off a similar set of KPIs. Datadog is no different from a topline perspective. And like other companies, ARR is the metric that communicates how Datadog is performing today.
But with a usage-based revenue model, what ARR means for Datadog was a philosophical discussion that we had all the time. On one hand, it’s not necessarily true recurring revenue —committed contracts might be, but if someone pays in arrears for overage or isn’t in a committed plan, the definition gets a little foggier.
These are the metrics Datadog used to measure ARR given their UBP model:
- Contracted annual recurring revenue (CARR): This accounts for the commitment and drawdown plans
- Usage-based annual recurring revenue (UARR): This measures usage growth over time with any vertical customer.
Churn was also a top metric that ended up being hard to define given the revenue model. From a gross retention rate, how much churn is happening is an important metric for determining the health of the business itself. But what constitutes churn? Is it churn if a customer is monitoring 1,000 hosts and for whatever reason, they go down to five?
You can’t always tell if it’s because they don’t like the product from a value perspective, or because they completely scrapped a bunch of their product roadmap plans and pulled things out of production. Customers who go from 1,000 to zero might be easy to report, but finding a system to account for all other cases was definitely more challenging.
Automate financial processes to scale
As Datadog’s product line expanded, quotes became a greater challenge to create, track, and account for. They need to clearly present different commitment and drawdown plans and track customer-specific contract terms. If this isn’t done accurately, it will severely impact the company’s ability to recognize revenue.
Whereas seat-based models can implement a third-party customer billing platform with relative ease, these billing platforms couldn’t readily account for all the features and elements of Datadog’s usage-based model.
We started off by managing our accounting and revenue reporting in-house, which worked well enough for a while. The positives were that it allowed us to be nimble and change things around, and not having to manage a third-party system meant we didn’t have to try to fit a square peg in a round hole.
For a long time, we relied on a bunch of really smart people putting together a lot of very complicated spreadsheets. As the company grew and had aspirations of going public, the need to automate these processes became harder to ignore. Datadog eventually decided to run with Salesforce Steelbrick CPQ and spent a lot of time implementing it. This top-tier platform provided the capabilities to tweak pricing, introduce new SKUs, or bundle products.
Besides exponentially decreasing the amount of manual labor for the finance department, it helped sales, as well. Potential customer deals were no longer stalled because sales team members couldn’t get out a quote.
This change is part of the normal evolution of any company— you start with cobbled-together systems and manual processes and when you reach a certain size and stage, investing in a third-party system just makes sense.
Source insight from across the org
Regardless of your qualifications, you will need a lot of help from outside teams.
Don’t underestimate the tremendous part the customer success department plays in the forecasting process—they’ve got their finger on the pulse of your customer base and should be your go-to for predictions for churn. Sure, your finance team can look at historical results or usage patterns, but CS is where you get the real story.
It’s not just customer success, either. You should be working closely with any team that is closer to what’s going on. Pricing will change with a UBP model—that’s a guarantee. And usually finance is the last in the business to know how everything is evolving.
There are just so many ways a customer can purchase products within the Datadog platform. Whether it’s bundling or buying one product a la carte, the question of how to price each product, or how to price new products, remains.
Finding an answer requires a lot of discovery that isn’t within the realm of expertise of finance teams. But this discovery is constantly changing, and so the price for the new product can change based on different ways of evaluating the usage. From a product side, whether it’s the product marketers or the R&D department, you can benefit even just from being a fly on the wall in their discussions.
The finance team has to be able to adapt and move as these new insights arrive. You can’t tell sales that you won’t be able to invoice a new deal because your systems aren’t ready to accommodate the pricing change. Take proactive measures to understand potential changes and prepare your teams for them.
Top five takeaways for your financial team
- When implementing a UBP model, prioritize allowing for maximum usage flexibility and pricing transparency for your customer—trust me, they’ll notice.
- Create the option for customers to commit to your product for an extended time period for a pricing discount. It will help your ARR prediction accuracy.
- Emphasize the benefits of UBP to your investors and get them excited about usage-based metrics.
- Don’t hesitate to automate financial processes when you are ready to scale. The investment is worth it in the long run.
- Don’t let your financial team exist in a vacuum. Collaborating with outside teams will help your team do their job more accurately and be prepared for change.
Disclaimer: This document is for informational purposes only. The information contained in this document shall not constitute an offer, solicitation, or recommendation to sell or offer to purchase any investment products or investment advisory services.
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