The SaaS recipe for usage-based billing and product-led growth
How can usage-based billing models support product-led growth? Here’s a simple recipe for SaaS success.
Product-led growth has become the dream model many SaaS companies aspire to. The idea is to create a flywheel effect built on inbound marketing and UX design that propels the customer’s self-driven buying journey.
Product-led growth is a relatively hands-off approach compared to a sales-led growth strategy. You build the product, market it, and get the customers to sign up for a subscription and onboard themselves.
But for many software businesses, as their portfolio of products increases in both volume and complexity, the added intricacy of customer quotes, contracts, and billing gets in the way of achieving true product-led growth.
Usage-based billing can minimize complexity and scale a #productledgrowth strategy, even for the biggest enterprise accounts. With usage-based billing, there are no tiers and no static mold the customer has to fit in. Everyone gets a customized price that’s just right for them.
Scaling a usage-based product portfolio
Observ8 Data provides IT observability services, helping companies to see what’s going on in their software stack. Growing from a revenue of USD $18 million in 2015 to nearly $1 billion in 2020, the Observ8 journey is one that many companies would love to emulate.
The basic recipe can be divided into four steps:
1. Identify a service and its pricing metric
One reason for Observ8’s impressive growth is that the product is awesome and the users love it. The other big reason is their #usagebasedpricing model.
When they started out, the only product Observ8 offered was server monitoring, billed via a simple pricing metric. If you have one server, you pay to monitor one server. If you have 100 servers, you pay for 100.
That’s a model that lends itself to product-led growth. The product solves one problem that’s easy to understand, easy to sign up for, and relatively easy to integrate.
As they identified other customer needs adjacent to the primary service, Observ8 started adding about three new services per year. Today, they offer 10 different services, each with its unique pricing metric based on usage.
For example, if the service is normal log retention, Observ8 still bills per host. But if they are monitoring serverless applications, there is no server, so they need a different metric such as the number of functions, invocations or security threats.
Then, the customer can mix and match, using only the services they need at a given time. As their needs grow, the customer can add more services.
2. Refine pricing based on real-time feedback
One of the strengths of the usage-based model is that you can tailor it to so many customers, without losing the people who would otherwise be squeezed between tiers. But once you determine which metrics you are billing for, setting the actual price requires a bit of science and a little bit of magic.
With each new service, Observ8 took the time to ask two simple, but crucial, questions:
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#Usagebasedpricing is particularly well-suited to a #SaaS business like Observ8 because it’s very easy to run A/B testing. With usage-based pricing, you’re constantly getting customer feedback, minute by minute, daily, based on consumption.
Observ8 could offer a sample price to a few customers, and track how the price change affects customer adoption. They can then adjust until they find the sweet spot. No customer surveys, no user groups, just data-driven pricing.
3. Upsell and cross-sell based on usage data
Offering purely usage-based pricing, Observ8 reduces the number of decisions the customer needs to make, reducing friction across the entire customer lifetime. This starts with purchasing the first service and continues through loyalty and upselling.
Customers don’t need to decide on a subscription tier or a customized service bundle when they first sign up. They need to know what type of service they want to buy.
Once the customer is onboard and using the service, Observ8 can make accurate recommendations for upselling based on the customer’s usage, positioning new add-ons in relation to the services the customer already uses.
A big advantage here is that upselling requires only minimal human outreach. Observ8 doesn’t need contract negotiations for the customer to consume more services, reducing the sales department's load.
A usage-based model eliminated the need for the IT department to decipher customer agreements, manage the required custom development, sort through all the data related to those contracts, and transcribe that into a monthly bill.
A usage-based model can also help you prevent predicted churn. By leveraging the insights gained from usage data, such as consumption patterns (dates, times, frequency, etc.), plus third-party #analytics, you could determine if a customer has ceased using your service based on their predicted usage pattern, which is a typical indicator of churn.
4. Consider the data integration stack
Deciding whether to “build or buy” a data integration tool is a crucial step in achieving success with usage-based billing. Without a purpose-built solution, starting with #usagebasedbilling usually requires a lot of homemade fixes, including spreadsheets, generic data integration software, data lakes, and so on.
The average data scientist in a company using a homemade solution might spend 60-80% of their time just cleaning and normalizing data. That’s obviously time that could be spent creating more customer value rather than doing grunt work.
That’s the situation Observ8 was in when they came to DigitalRoute. They needed to choose between customizing a generic #ETL data integration tool and buying DigitalRoute’s purpose-built software to move forward.
The first consideration was not just the cost of the software, but also the cost of integration. Building a custom solution on top of a generic data integration tool would take significant time and require hiring a system integrator.
The second factor was revenue leakage. Like many companies we speak with, Observ8 didn’t believe they had a big problem. But in reality, our clients typically recover 3-12% in revenue leakage that they may not have even known they had.
Observ8 realized that if they could lower the integration time with DigitalRoute’s purpose-built solution, their overall spending would be lower. A purpose-built solution would seal the revenue gaps that might occur with a custom build, which meant Observ8 could realize a faster ROI from the #DigitalRoute solution.
Ready to try the DigitalRoute recipe?
Any company that wants to make revenue from usage can create its own version of Observ8’s #quotetocash processes, the same revenue generation process, and the same way to attach billing to usage data.
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