Practical insights on striking the right balance between predictability and flexibility in enterprise sales, strategies for effectively tracking customer usage, and key considerations before shifting to a usage-based pricing model.
Since 2003, Splunk has provided tools that help companies understand their data and strengthen security. Their tools help detect and address issues in infrastructure and applications before they lead to major disruptions. Cisco recognized Splunk's value, purchasing the company for $28 billion in 2023—one of the biggest deals in the technology sector. Splunk continues to help businesses adapt to digital changes worldwide.
Splunk's growth reveals an interesting pricing story. While charging based on usage isn't new, making it work for large companies means solving real problems with budgeting and sales approaches. Some software providers champion pure pay-as-you-go pricing, while others maintain fixed fees. Splunk's approach shows how companies can balance reliable revenue predictability with fair customer costs.
Federico Gonzales serves as Splunk's Director of Pricing Strategy. With experience at Intel, Box, and ServiceNow, Federico manages how Splunk prices and sells its products. He works with product teams on new offerings while ensuring that Splunk’s operational systems, from quote-to-cash to usage monitoring, can handle complex enterprise pricing at scale.
In this episode of Pricing Labs, we provide an insider’s look at Splunk’s pricing strategy and share key lessons for companies already selling to enterprises or looking to break into the enterprise market.
Initially, Splunk charged based on how much data customers processed daily. "It worked well. It was super simple. How much data are you bringing in? Boom. Customers loved it!" explains Federico.
Customers appreciated being able to predict their costs based on data volume. Sales teams found it easy to price deals by measuring how much data a customer needed to process.
The situation changed when customers started using Splunk for more than just processing data. They began using it for compliance, storage, reporting, investigations, and monitoring. Federico points out, "We had customers with diverse use cases that say, 'Hey, some data is more valuable than other data.'" The value wasn't just about data volume anymore but what customers could do with that data. They wanted to process different types of information—some critical to their business, some less important—without paying the same rate for everything.
To solve these challenges, Splunk changed its pricing approach. Instead of charging for data volume, they began charging for computing resources. With this model, customers pay for the Splunk Virtual Compute (SVC) they use, based on:
"The way our workload pricing is built out is you have a commit, and you max out at that commit," he explains. "If you go close to that, there's no overage. You come to us, or we get a notification saying, 'Hey, we probably need to have a conversation around increasing the number of compute resources.'"
This approach also lets customers save money by scheduling tasks during quieter periods, helping them stay within budget while getting the performance they need.
While Splunk charges based on usage, it doesn't use a pure pay-as-you-go approach. Instead, it offers upfront commitments that work better for large companies. Federico explains, "Everything is still on an upfront commit basis, rather than a pure pay-as-you-go model."
This approach meets the budgeting needs of big businesses, which need predictable costs. "Customers often have a set budget and want to avoid surprises, like receiving a bill for an unexpected $100,000," he notes. "There's value in the additional usage, but many enterprises aren't fully adapted to a 'pay for what you use' model. They prefer the predictability of committing to a set amount, with flexibility to discuss any additional needs as they arise."
While predictable usage-based pricing sounds simple, it requires strong systems to execute well. At Splunk, this means connecting several systems to work together:
The sales process starts in Salesforce, where sales teams assess customer needs and create quotes. After deals are signed, orders move to SAP for billing and provisioning. This connection ensures customers quickly get access to what they purchased with the correct usage limits.
Since customers' resource use and planning depend on their usage, good monitoring tools are essential. "You have to make sure that customers can see what they're using," Federico emphasizes.
His advice to companies implementing usage-based pricing: "The telemetry piece is critical. You need complete visibility into how customers use your product to deliver a good experience."
The success of usage-based pricing depends on teamwork between sales, customer success, and product groups. Splunk does this by creating clear processes for tracking accounts, finding upsell opportunities, and ensuring customers get value from their usage.
For companies thinking about usage-based pricing in a sales-driven environment, Splunk's experience offers important lessons:
First, study how your current customers use your product. Federico warns about a common mistake: "Say you have a large segment of customers on a seat pricing who engage with your product but aren't power users. They might be perfectly content with their current per-user pricing. But if you switch them to usage-based pricing, you'll face a psychological hurdle -- to maintain the same revenue, you need to set such a high per-unit price that customers would question the perceived value, even though they'd be paying the same amount."
Second, make sure your systems can handle usage-based pricing. This means having robust tools for quote-to-cash workflows, usage tracking, automated billing, and real-time usage monitoring.
Third, understand that enterprise companies value predictable costs over pure pay-as-you-go pricing. Consider a commitment model that provides usage-based benefits while maintaining budget predictability.
Finally, support your sales teams. Give them the tools and data they need to help customers choose the right size commitments during purchases and renewals.