For investors evaluating startup software companies, usage-based pricing has become an increasingly common structure worth understanding in depth. While usage-based models can signal strong product-market fit and align a company’s growth with customer success, they also introduce a category of revenue risk that may not be immediately visible in headline metrics. This blog explores how to identify and evaluate those risks as part of a broader due diligence process.
What Is Usage-Based Pricing?
Usage-based pricing, sometimes referred to as consumption-based pricing, is a model in which customers are charged based on how much of a product or service they actually use rather than paying a flat subscription fee. Common examples include cloud infrastructure platforms that bill by compute or storage, application programming interface (API) providers that charge per call, and data tools that price by volume processed. While this structure can lower the barrier to adoption and create natural expansion revenue as customers grow, it also means that a startup’s revenue in any given period is directly tied to customer behavior, which can be difficult to predict and inherently more variable than traditional subscription revenue models.
Revenue Volatility
One of the most significant risks in usage-based models is that revenue can fluctuate meaningfully from period to period, independent of whether the customer relationship itself is healthy. A customer who reduces usage during a slow quarter, pauses a project, or optimizes their workflows may generate substantially less revenue without ever formally churning. This dynamic can make it difficult to assess true retention and may cause gross revenue retention figures to understate the underlying strength or weakness of the business.
Forecasting Challenges
Unlike seat-based subscription models where contracted recurring revenue provides a relatively predictable baseline, usage-based businesses often have limited forward visibility into what customers will consume in future periods. This can complicate financial forecasting, make it harder to manage headcount and infrastructure costs, and introduce meaningful variance between projected and realized revenue. Investors may want to evaluate how the company models its revenue pipeline and whether its forecasting methodology accounts for consumption variability at the cohort level.
Unit Economics Under Pressure
When customer usage declines, the cost of serving that customer does not always decline at the same rate. Support infrastructure, customer success resources, and underlying operational costs may remain relatively fixed even as the revenue associated with a given account shrinks. This mismatch can compress margins during periods of reduced consumption and may be particularly acute for startups that have not yet reached the scale needed to absorb those fluctuations. Understanding how unit economics behave across different usage scenarios is an important part of evaluating the model’s durability.
Customer Success Dependency
Usage-based models tend to place a higher operational burden on customer success functions than traditional subscription models. Because revenue is tied directly to how actively and effectively customers use the product, startups with usage-based pricing often need to invest meaningfully in onboarding, adoption support, and ongoing engagement to sustain and grow revenue. A weak customer success motion can accelerate usage decline and compress net revenue retention, even in cases where the underlying product is strong. Investors may want to assess whether the company has built the infrastructure to support this model at scale.
Key Considerations
Usage-based pricing is not inherently a red flag, and in many categories, it represents a customer-aligned go-to-market structure. Some of the most durable software businesses have been built on usage-based models, and the alignment between customer value and vendor revenue can be a meaningful long-term advantage. What matters for investors is whether the startup has a clear-eyed view of the risks embedded in the model and has taken deliberate steps to manage them.
Key metrics to examine include net revenue retention, cohort-level consumption trends over time, the ratio of expansion revenue to contraction revenue, and the predictability of revenue at the account level. A founding team that can speak fluently about how usage patterns evolve across customer cohorts may be better positioned to scale responsibly. This includes having built the forecasting and customer success infrastructure needed to manage variability, rather than treating revenue growth as purely a function of new customer acquisition.
Final Thoughts
Usage-based pricing can be a compelling model, but it introduces a category of revenue risk that may not be fully visible in top-line metrics alone. For investors, understanding how consumption variability affects retention, forecasting, and unit economics can be an important part of evaluating a startup’s financial health. As with any aspect of due diligence, pressure testing a founder’s assumptions about their pricing model against actual cohort data and customer behavior may provide a more complete picture of the business’s underlying durability.
Want to learn more about investing in startups? Check out the following MicroVentures blogs to learn more:
- Going Public: Direct Listing vs IPO vs SPAC
- Understanding Voting vs Non-Voting Shares
- Developing Your Investment Thesis
- Learning From Failed Startups
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The information presented here is for general informational purposes only and is not intended to be, nor should it be construed or used as, comprehensive offering documentation for any security, investment, tax or legal advice, a recommendation, or an offer to sell, or a solicitation of an offer to buy, an interest, directly or indirectly, in any company. Investing in both early-stage and later-stage companies carries a high degree of risk. A loss of an investor’s entire investment is possible, and no profit may be realized. Investors should be aware that these types of investments are illiquid and should anticipate holding until an exit occurs.
