Recurring revenue is attractive for almost any business. The subscription model question is not whether it is attractive. It is whether your product, your pricing, and your systems can sustain it once customers say yes.
A subscription business model works when value is delivered continuously, when usage or outcomes can be measured, and when the underlying systems can price, bill, and recognize revenue in step with how customers behave. When any one of those is missing, a subscription model does not fail loudly. It fails slowly, through discounting, churn, and a finance team that never quite trusts the numbers.
The direction of travel is not really in question. Grand View Research puts the global subscription economy at roughly 492 billion dollars in 2024, growing toward 628 billion dollars in 2026, with B2B accounting for much of that revenue. What is in question, for any specific business, is fit, not trend.
What Makes a Business a Good Fit
Three things tend to separate businesses where a subscription model works from businesses where it becomes a permanent source of friction.
- The product delivers value on an ongoing basis, not just at the point of sale.
- Usage, adoption, or outcomes can be tracked well enough to justify the price, whether that price is flat, tiered, or usage-based.
- The business is willing to treat pricing as something that evolves, not something set once at launch.
This is part of why SaaS solutions were early and natural adopters of the subscription business model. Software is inherently ongoing. Usage is inherently trackable. Pricing was never expected to be static.
When Usage-Based and IoT Models Change the Calculus
For companies building connected products, the fit question gets more layered. IoT monetization means turning device signals, telemetry, and usage events into billable revenue, not just attaching a subscription fee to a piece of hardware.
That requires an IoT billing architecture that can ingest device data, translate it into rated usage, and connect it to a contract and an invoice without someone manually reconciling spreadsheets every month. Without that architecture, IoT monetization tends to stall exactly where it should be accelerating, at the point where usage data should be turning into revenue.
In one widely cited estimate, Gartner has projected that roughly 80 percent of IoT implementations fail to capture their full value. Our experience matches that: the shortfall is rarely because the data lacks value. It is because nothing connects the data to a billing event.
What Happens to Pricing and Quoting as You Grow
A subscription model with three pricing tiers is simple to quote. A subscription model with usage components, multi-year contracts, and enterprise-specific terms is not.
This is where CPQ, configure, price, quote, tools start to matter. Platforms like Conga CPQ exist because manual quoting cannot keep up with a pricing model that changes by customer, by contract term, and by usage tier. CPQ quote automation is not a nice-to-have at that point. It is the difference between a sales team that can close a deal in days and one that waits weeks for finance to confirm what a contract says.
This is not a niche concern. Grand View Research values the CPQ software market at roughly 3.5 billion dollars in 2025, on pace to more than triple by 2033. The growth is a symptom as much as a market opportunity: enterprises are hitting a pricing complexity ceiling that manual quoting cannot support.
Not every company solving this problem is starting from a blank slate, though. Some already have billing infrastructure in place they just need to know whether it can do the job.
What If You Have a Legacy Platform
Many enterprises already run mature revenue infrastructure, including Oracle's Billing and Revenue Management platform, OBRM. For these companies, the real question is not whether to adopt a subscription model. It is whether the existing OBRM environment can support one without a multi-year re-platforming project.
The answer is usually yes, but only with a clear-eyed assessment of what the platform can already do versus what has simply never been configured to do it.
Payments Are Part of the Fit Question Too
How a business collects payment is easy to overlook and expensive to get wrong. A one-time transaction and a recurring subscription have different failure modes: failed renewals, dunning, and payment retries among them.
This is why companies moving from ecommerce or one-time sales into recurring revenue increasingly look at Stripe payment advisory services early in the process, rather than after the first billing cycle goes wrong.
Industry benchmarks, including Recurly's own subscriber data, put involuntary churn, a subscriber losing access because a payment failed, not because they chose to leave, at roughly 20 to 40 percent of total subscription churn. None of that reflects dissatisfaction with the product. It reflects payment infrastructure that was never built to catch it.
The SaaS Billing Reality Nobody Budgets For
Even companies that check every fit criterion above tend to underestimate SaaS billing complexity once they are live: upgrades and downgrades mid-cycle, proration, trial-to-paid conversion, multi-currency and multi-entity billing, and a revenue recognition process that must keep pace with all of it.
None of this means a subscription model is the wrong choice. It means the systems supporting it need to be designed for change, not just for launch.
The Real Fit Test
The question worth asking is not whether a recurring revenue model fits your business in theory. Almost any business can tell a good story about recurring value.
The real test is whether pricing, contracts, billing, and revenue recognition can move together as fast as the market does. If a pricing change takes a systems project, if usage data does not reliably become an invoice, or if finance cannot trace a number without help, the model is not the problem. The architecture underneath it is.
Grand View Research, Subscription Economy Market Report: https://www.grandviewresearch.com/industry-analysis/subscription-economy-market-report
Gartner IoT data monetization forecast, as cited by GoodData: https://www.gooddata.com/blog/80-percent-of-companies-will-fail-to-monetize-iot-data-according-gartner/
Grand View Research, CPQ Software Market Report: https://www.grandviewresearch.com/industry-analysis/cpq-software-market-report
Recurly, Churn Rate Benchmarks: https://recurly.com/research/churn-rate-benchmarks/