Market data showing why consumption-based billing has become mainstream across SaaS, AI, and cloud infrastructure companies
The usage-based pricing market is undergoing a structural shift. MarketIntelo estimates the global usage-based pricing platforms market at $7.8 billion in 2025, while DataIntelo values the broader usage-based billing market at $9.4 billion in 2025 and projects it will reach $28.6 billion by 2034. Behind those numbers is a change in how software companies monetize: a move away from rigid seat-based models toward consumption-aligned pricing that scales with the value customers actually realize. Our view at Orb is that once a company makes that move, a billing engine becomes core revenue infrastructure rather than a back-office afterthought.
Key takeaways
- Market growth is measurable: DataIntelo values the usage-based billing market at $9.4 billion in 2025, projects it will reach $28.6 billion by 2034, and states a 13.2% compound annual growth rate for 2026 to 2034. Separately, the 2025 and 2034 endpoints imply approximately 13.2% annualized growth across nine yearly intervals
- Usage-based elements are widespread: Benchmarkit reports that 67% of SaaS companies say they have introduced at least one element of usage-based pricing
- Platform fees with usage included are common: SBI's narrative summary reports 37% using platform fees with usage included, while an adjacent N=321 pricing-structure chart reports 34.0% for platform fees; both representations rank platform fees as the most prevalent structure
- Pricing-model growth varies by cohort: in Benchmarkit's N=149 pricing-model cohort, primarily usage-based companies posted 44% median 2024 growth, compared with 25% for subscription and 26% for subscription plus usage; Benchmarkit notes that cohort composition may bias the result
- Billing accuracy is a revenue issue, not an admin issue: DataIntelo cites industry estimates that organizations using inadequate billing systems can lose 3% to 7% of potential revenue to metering inaccuracies and manual reconciliation errors
- Buyers are feeling the volatility: 78% of 218 IT leaders surveyed by Zylo reported unexpected charges tied to consumption-based or AI pricing models in the prior 12 months
Market size and growth projections
The usage-based pricing infrastructure market is drawing substantial investment from both software vendors and traditional consumption-billing industries. The four statistics below are market-sizing estimates from two research firms.
1. MarketIntelo estimates the usage-based pricing platforms market at $7.8 billion in 2025
MarketIntelo estimates the global usage-based pricing platforms market reached $7.8 billion in 2025, reflecting the infrastructure investment required to support consumption-based business models across industries.
2. MarketIntelo projects the market will reach $18.4 billion by 2034
MarketIntelo projects the usage-based pricing platforms market will grow to $18.4 billion by 2034, more than doubling its 2025 estimate over the following nine years.
Source-quality note. MarketIntelo's stated overall CAGR is internally inconsistent with its displayed endpoints. Its $9.1 billion 2026 and $18.4 billion 2034 values imply approximately 9.2% CAGR, while its $7.8 billion 2025 and $18.4 billion 2034 endpoints imply approximately 10.0%. For that reason, this article uses MarketIntelo's endpoint estimates only and does not reproduce or rely on its stated overall CAGR.
3. DataIntelo values the usage-based billing market at $9.4 billion in 2025
The broader usage-based billing market, which includes telecommunications and utilities alongside SaaS, was valued at $9.4 billion in 2025 by DataIntelo.
4. DataIntelo projects $28.6 billion by 2034 and states a 13.2% CAGR for 2026 to 2034
DataIntelo projects the usage-based billing market will reach $28.6 billion by 2034 and states a 13.2% compound annual growth rate for 2026 to 2034. Separately, its $9.4 billion 2025 base and $28.6 billion 2034 endpoint imply approximately 13.2% annualized growth across the nine yearly intervals from 2025 to 2034.
Supporting context on pricing pressure. SaaS list prices have been climbing far faster than general inflation, which is part of why buyers are pushing for consumption alignment. Vertice reports that as of January 2025, SaaS pricing was 11.4% higher year over year, against an average G7 market inflation rate of 2.7%. This is a SaaS pricing statistic rather than a usage-based pricing statistic, so it sits outside the numbered list.
Pricing preference and market penetration
Enterprise buyer preference provides one direct signal of where consumption pricing is gaining traction. L.E.K. Consulting reproduces a 2025 a16z survey of 100 enterprise CIOs across 15 industries that asked which pricing model they prefer when purchasing an AI application.
5. 39% of enterprise CIOs prefer usage-based pricing for AI applications
In the 100-CIO survey reproduced by L.E.K. Consulting, 39% preferred usage-based pricing tied to measures such as tokens, API calls, or time, making it the most selected model in the sample.
6. 23% of enterprise CIOs prefer hybrid pricing for AI applications
The same survey found that 23% preferred hybrid pricing, defined as a mix of seat, usage, and outcome-based components. Hybrid ranked second behind pure usage-based pricing.
7. 21% of enterprise CIOs prefer seat-based pricing for AI applications
Traditional seat-based pricing was preferred by 21% of the 100 CIOs, placing it behind both usage-based and hybrid models in the survey.
8. 15% of enterprise CIOs prefer outcome-based pricing for AI applications
Outcome-based pricing, such as charging per lead, resolution, or completed task, was preferred by 15% of surveyed CIOs. The figure shows meaningful interest, but materially less than for usage-based or hybrid approaches.
9. 2% of enterprise CIOs selected other or were unsure about AI application pricing
Only 2% of the enterprise-CIO sample selected other or not sure. Together, the 39%, 23%, 21%, 15%, and 2% figures form the complete pricing-preference distribution reported in the survey.
10. More than 61% of publicly traded SaaS companies offer at least one usage-based tier
DataIntelo reports that more than 61% of publicly traded SaaS companies now offer at least one usage-based pricing tier, up from approximately 34% in 2020.
Hybrid pricing model statistics
Pure usage-based pricing is only part of the story. Current pricing research shows usage elements appearing in platform-fee structures, pure usage models, and broader subscription combinations, while true outcome-based pricing remains rare.
11. 67% of SaaS companies have introduced at least one usage-based pricing element
Benchmarkit reports that 67% of SaaS companies say they have introduced at least one element of usage-based pricing. The same source notes that the primary model is still often a per-user subscription or a subscription combined with a usage-based or value-based variable.
12. SBI's narrative reports 37% using platform fees with usage included
SBI's narrative summary reports that 37% used platform fees with usage included, ahead of flat fees with no usage included at 23% and pure usage-based pricing at roughly 21%. An adjacent N=321 pricing-structure chart in the same report shows platform fees at 34.0%, flat fees at 23.4%, and usage-based pricing at 21.2%. The report therefore presents two different platform-fee figures, but both representations rank platform fees first.
13. 21.2% of SaaS respondents use a usage-based pricing structure
The same 321-respondent SBI survey reports that 21.2% use a usage-based pricing structure, underscoring that pure usage is significant but still smaller than platform-fee structures that include usage.
14. Only 0.6% of SaaS respondents use outcome-based pricing
SBI reports that just 2 of 321 respondents, or 0.6%, used an outcomes or performance-based pricing model. The result provides a useful counterweight to the attention outcome pricing receives in AI monetization discussions.
Companies operating in this middle ground need flexible price modeling that supports seats, platform fees, prepaid credits, commits, tiers, and dimensional pricing inside one system rather than across bolted-together tools. Orb’s dimensional price groups support pricing across multiple usage dimensions, such as region, instance type, and environment, using a single pricing configuration for dimension combinations.
Revenue and performance metrics
The financial case for usage-based pricing rests on measurable performance differences. The statistics below identify their publishers explicitly, because the strength of the underlying evidence varies.
15. Primarily usage-based companies posted 44% median 2024 growth in Benchmarkit's cohort
In Benchmarkit's N=149 pricing-model cohort, companies that were primarily usage-based posted 44% median growth in 2024, compared with 25% for traditional subscription and 26% for subscription plus usage. Benchmarkit explicitly notes that the growing concentration of usage-based pricing in SaaS and AI-native companies can bias the comparison.
16. 40% of companies above $50 million ARR report consumption and outcome-based revenue in total ARR
High Alpha reports that among companies with more than $50 million ARR, 40% included consumption and outcome-based revenue in total ARR. The comparable figure was 38% for companies between $20 million and $50 million ARR, indicating that larger SaaS companies are actively incorporating variable monetization into their revenue mix.
17. DataIntelo says usage-based pricing can raise net revenue retention by 15 to 25 percentage points
DataIntelo says usage-based pricing can increase net revenue retention by 15 to 25 percentage points compared with seat-based models. This is a publisher-reported association rather than a demonstrated causal effect, and DataIntelo does not disclose claim-level study provenance.
18. DataIntelo reports 22% to 40% faster time-to-conversion
DataIntelo reports 22% to 40% faster time-to-conversion for usage-tiered plans than for flat-rate plans. The figure is a reported difference between plan types, not a measured causal effect of the pricing model itself.
19. MarketIntelo reports churn rates 30% to 40% lower with usage-based models
MarketIntelo reports churn rates 30% to 40% lower under usage-based models than under fixed subscription models in comparative studies. The underlying study details are not disclosed, so this should be read as a publisher-reported figure.
Billing accuracy and revenue leakage
The complexity of usage-based pricing creates real accuracy exposure. Without robust metering, the losses land directly on the income statement.
20. DataIntelo cites industry estimates that inadequate billing systems can cost 3% to 7% of potential revenue
DataIntelo cites industry estimates that organizations using inadequate billing systems can lose between 3% and 7% of potential revenue to metering inaccuracies and manual reconciliation errors. For a $50 million ARR company, that range works out to $1.5 million to $3.5 million in annual revenue leakage.
21. DataIntelo reports 74% of finance leaders prioritize real-time billing intelligence
DataIntelo reports that among finance leaders at companies with revenues above $100 million, 74% rank real-time billing intelligence among their top three technology investment priorities.
22. 78% of surveyed IT leaders experienced unexpected charges from consumption-based or AI pricing
Zylo's 2026 SaaS Management Index reports that, across a survey of 218 IT leaders, 78% hit charges they had not anticipated from consumption-based or AI pricing over the preceding year, and 61% were forced to cut projects because of unplanned SaaS cost increases. Zylo's broader dataset covers more than 40 million SaaS licenses and $75 billion in spend under management. Bill shock at that scale is exactly what spend controls exist to prevent, through real-time spend monitoring, alerts, and automated threshold responses.
Accurate billing also depends on retaining granular usage data instead of discarding detail after aggregation. Orb's accuracy approach addresses this by continually storing and referencing raw usage events, and by supporting backfills and corrections that flow through to invoices and downstream data.
Regional market distribution
The regional statistics below measure market revenue share, not adoption rates. North America accounts for the largest share of market revenue, while Asia Pacific has the fastest projected growth.
23. North America holds 42.3% of the pricing platforms market
MarketIntelo reports North America led the usage-based pricing platforms market with a 42.3% revenue share in 2025, reflecting the region's concentration of SaaS and cloud infrastructure companies.
24. North America accounts for $3.6 billion in billing market revenue
DataIntelo reports North America accounted for $3.6 billion, or 38.4%, of the global usage-based billing market in 2025.
25. Europe represents 26.7% of global billing market revenue
DataIntelo reports Europe represented approximately 26.7% of global usage-based billing market revenue in 2025, and forecasts a 12.4% CAGR through 2034.
26. Asia Pacific is the fastest-growing region at a 16.1% CAGR
DataIntelo forecasts Asia Pacific as the fastest-growing region, expanding at a 16.1% CAGR through 2034 from approximately 22.8% of global revenues in 2025.
Deployment and infrastructure trends
Cloud-based billing platforms dominate the market, and DataIntelo reports materially shorter implementation timelines for cloud deployments than for on-premises equivalents.
27. Cloud deployment captures 67.8% of the billing market
DataIntelo reports cloud deployment led the usage-based billing market at 67.8% of market revenue in 2025.
28. Cloud-based platforms capture 78.2% of the pricing platforms market
MarketIntelo reports cloud-based usage-based pricing platforms captured $6.1 billion, or 78.2%, of total revenues in 2025, growing at a 17.8% CAGR.
29. DataIntelo reports cloud deployments achieved average implementation timelines 40% shorter than comparable on-premises deployments in 2025
DataIntelo reports that in 2025, cloud deployments achieved average implementation timelines approximately 40% shorter than comparable on-premises deployments.
30. Enterprise implementations typically range from 6 to 18 months
DataIntelo reports that implementation timelines for enterprise usage-based billing deployments typically range from 6 to 18 months depending on complexity. Platform choice affects where a given project lands in that range. Orb provides ERP, accounting, and CRM integrations alongside finance workflow tooling for revenue recognition, AR aging, dunning, and contract-to-cash, all designed to streamline implementation and ongoing operations.
31. DataIntelo cites analyst estimates that approximately 22% of enterprise billing transformation projects experience significant delays or cost overruns
DataIntelo cites analyst estimates that approximately 22% of enterprise billing transformation projects experience significant delays or cost overruns. Selecting billing infrastructure with proven implementation patterns helps mitigate that risk.
Industry segment statistics
Usage-based pricing spans multiple industries. Telecommunications still holds the largest revenue share, while SaaS providers are the fastest-growing segment.
32. Telecommunications represents 28.6% of the billing market
DataIntelo reports telecommunications was the largest end-user segment of usage-based billing at 28.6%, or $2.69 billion of total revenues in 2025, reflecting the industry's long history with consumption-based models.
33. SaaS providers are the fastest-growing vertical at a 15.3% CAGR
DataIntelo forecasts the SaaS providers segment as the fastest-growing vertical, expanding at a 15.3% CAGR through 2034 from approximately 22.4% of market revenues in 2025.
34. Subscription management holds 32.5% application share
MarketIntelo reports subscription management held the largest application share at 32.5% of the usage-based pricing platforms market.
35. Software components command 74.4% of the pricing platforms market
MarketIntelo reports software components commanded $5.8 billion, or 74.4%, of the usage-based pricing platforms market in 2025, with professional services making up the remainder.
Customer preferences and buying behavior
Understanding what buyers actually want from a contract helps explain why vendors keep moving toward consumption models.
36. DataIntelo reports 68% of B2B software buyers prefer usage-based contracts
DataIntelo reports that 68% of B2B software buyers now prefer usage-based contracts because they align costs directly with realized value.
Supporting context on software spend and license waste. Two adjacent benchmarks help explain that preference, though neither is a usage-based pricing statistic in itself. Vertice reports that average SaaS spend per employee reached $9,324 in Q2 2026, up from $9,200 in Q1 2026. Zylo, benchmarking against industry-recommended utilization levels, puts average unused SaaS licenses at 36% per organization. Rising spend combined with persistent shelfware is precisely the structural inefficiency that consumption-aligned pricing is meant to remove.
Enterprise adoption statistics
Large enterprises and smaller businesses are both investing in usage-based pricing infrastructure, but at different growth rates.
37. Large enterprises account for 57.7% of platform spending
MarketIntelo reports large enterprises accounted for 57.7%, or $4.5 billion of usage-based pricing platform spending in 2025, reflecting the complexity of enterprise billing requirements.
38. SMEs represent 42.3% of the market, growing at a 17.5% CAGR
MarketIntelo reports small and medium enterprises represented 42.3%, or $3.3 billion of the usage-based pricing market in 2025, growing at a 17.5% CAGR as cloud-based solutions reduce implementation barriers.
For teams managing complex billing scenarios, pricing simulations let you model financial outcomes using real product usage data and run side-by-side pricing experiments without affecting live customers, which reduces the risk of unintended revenue impacts.
AI-era monetization and revenue design
The next wave of consumption pricing is being shaped by AI products, where packaging and monetization choices can directly affect adoption and the economics of new features.
39. 20% of the market monetizes AI-powered features as add-ons in SBI's study
SBI's 2025 State of SaaS Pricing research says companies monetizing AI-powered features as add-ons represent 20% of the market. The report argues that separately priced AI features can constrain adoption, reinforcing the need to design AI packaging around clear customer value rather than novelty alone.
40. SBI estimates only 8% of net new customers ultimately use separately priced AI features
SBI estimates that only 8% of all net new customers ultimately use AI-powered features sold as add-ons. The underlying breakdown says 20% of net new customers purchase the add-on and 38% of those purchasers actually use it, which rounds to the reported 8% overall adoption figure.
What these statistics mean for software companies
Usage-based pricing has become an increasingly important competitive option where consumption closely tracks customer value. Benchmarkit reports that 67% of SaaS companies have introduced at least one usage-based pricing element, while the a16z CIO survey reproduced by L.E.K. shows usage-based pricing as the leading preference for AI applications at 39%. Whether it is right for a given business still depends on whether consumption is a credible proxy for the value delivered.
Hybrid models represent the practical middle ground. SBI's narrative summary puts platform fees with usage included at 37%, while its adjacent N=321 pricing-structure chart shows platform fees at 34.0%; both rank platform fees as the most prevalent structure. Benchmarkit's N=149 performance cohort does not show hybrid as the fastest-growing model: primarily usage-based companies posted 44% median 2024 growth, compared with 26% for subscription plus usage and 25% for subscription. Supporting both a predictable subscription base and variable consumption still requires billing infrastructure that treats them as one unified system, not two.
Billing accuracy directly affects financial performance. DataIntelo's cited industry estimate of 3% to 7% revenue leakage is material at any scale. Companies implementing usage-based pricing need metering infrastructure that maintains a raw data layer, logs usage events, and supports high-volume ingestion.
Implementation choices determine time-to-value. DataIntelo reports that in 2025, cloud deployment implementation timelines were roughly 40% shorter than comparable on-premises deployments and that enterprise projects typically take 6 to 18 months; it also cites analyst estimates that approximately 22% of enterprise billing transformation projects hit significant delays or cost overruns. Platform selection is therefore a schedule decision as much as a feature decision.
Two Orb customers illustrate what strong billing infrastructure delivers in practice. Vercel reduced its need for temporary manual-reconciliation staffing by 50%, launched billing for a new product in three weeks, and cut the time to build and launch billing for new products by 80%. Replit got Orb up and running in one month with one engineer, with support on the user interface and wrap-up tasks, and was able to make last-minute pricing changes ahead of launch. Both case studies document operational efficiency and faster product and pricing launches, results that are specific enough to model directly when you are building an internal business case.
Frequently asked questions
What is usage-based pricing and why is it growing so quickly?
Usage-based pricing charges customers based on actual consumption rather than fixed subscription fees or seat counts. It is growing because it aligns vendor revenue with customer value realization: customers experience less friction at adoption, more flexibility as needs fluctuate, and clearer ROI. In Benchmarkit's N=149 pricing-model cohort, primarily usage-based companies posted 44% median 2024 growth, compared with 25% for subscription and 26% for subscription plus usage, although Benchmarkit notes that cohort composition can bias the comparison.
What is the difference between usage-based pricing and hybrid pricing?
Pure usage-based pricing ties all revenue to consumption metrics such as API calls, compute hours, or data volume. Hybrid pricing combines a subscription base with usage-based components, providing predictable minimum revenue while capturing expansion through consumption. SBI's narrative summary reports platform fees with usage included at 37%, while an adjacent N=321 chart reports 34.0% for platform fees. Both rank platform fees as the most prevalent pricing structure. Hybrid structures typically include a platform fee or minimum commitment alongside variable usage charges.
How does usage-based pricing affect revenue predictability?
Usage-based pricing can reduce month-to-month predictability, which is why forecasting discipline and commercial guardrails matter. On longer-horizon metrics, DataIntelo says usage-based pricing can increase net revenue retention by 15 to 25 percentage points compared with seat-based models, and MarketIntelo reports churn rates 30% to 40% lower than under fixed subscription models. Both are publisher-reported associations rather than demonstrated causal effects. Many companies address predictability directly through hybrid models with minimum commitments or prepaid credits alongside consumption billing.
What infrastructure do companies need to implement usage-based pricing?
Successful usage-based pricing requires metering infrastructure that captures usage events accurately, a billing engine that can apply complex pricing logic, and finance workflows that support usage-based revenue recognition. DataIntelo cites industry estimates that organizations with inadequate billing systems can lose 3% to 7% of potential revenue to metering inaccuracies and manual reconciliation. The key capabilities are real-time event ingestion, dimensional pricing across multiple usage attributes, persistent storage of raw usage events, and the ability to backfill and correct retroactively when errors surface.
How long does it typically take to implement usage-based billing?
Timelines vary with complexity and platform choice. DataIntelo reports that in 2025, cloud deployment implementation timelines were approximately 40% shorter than comparable on-premises deployments and that enterprise implementations typically range from 6 to 18 months. It cites analyst estimates that approximately 22% of enterprise billing transformation projects hit significant delays or cost overruns. Faster is achievable: Replit got Orb up and running in one month with one engineer, with support on the user interface and wrap-up tasks. At Vercel, the team built and launched billing for a new product in three weeks.