Webinar
Untangling the Software Monetization Stack in a Usage-Based Economy
Discover how to make the most of your software monetization stack in a usage-based economy. Hear from guest speaker Lily Varon of Forrester.
Original Air Date: June 17, 2025
Overview
Usage-based monetization models aren't new, but they are all the rage again. As AI moves closer to our products and how we deliver them, more firms are incorporating usage or consumption-based offerings into their product portfolios. In response, business application vendors across a diverse range of categories are modifying their solutions to support them. The result is a cluttered and confusing technology landscape. Michael Goff, Principal Product Marketer at Revenera and guest speaker Lily Varon, Principal Analyst at Forrester Research, host this webinar that help software producers:
- Define the roles business applications like CRM, CPQ, Entitlements & Provisioning, Billing, Payments, Mediation, Revenue Recognition and ERP play in supporting usage-based businesses
- Identify overlap in functionality between the options from solutions in separate tech categories.
- Analyze what those solutions purpose-built for usage-based businesses will do well, and what problems will indicate to you that it's time to make changes.
Recap
Key Themes and Takeaways
The Rise of Usage-Based Monetization
Usage-based models are gaining traction as AI-driven products shift away from traditional subscriptions. Monetization is evolving from per-seat pricing to models based on actions, outcomes, and real-time usage.
AI’s Role in Product Transformation
Generative AI is now widely embedded in software offerings, with 91% of large enterprises reporting AI integration. The next frontier—agentic systems—promises autonomous decision-making and cross-platform orchestration, requiring new monetization strategies.
From Seats to Outcomes
Companies like Salesforce are pioneering action-based pricing. Instead of charging per user, they now assign credit values to actions (e.g., updating records, resolving cases), deducted from prepaid credit packs. This shift reflects a broader move toward monetizing outcomes rather than access.
The Messy Middle: Tech Stack Complexity
Monetizing usage involves multiple layers:
- Capturing usage events and enforcing entitlements in real time.
- Transforming raw data into actionable insights.
- Applying dynamic rate tables to assign value.
- Integrating billing, payments, tax, and revenue recognition systems.
Customer and Product Data Challenges
CRMs, CDPs, billing systems, and entitlement platforms all hold critical customer data—but integration and real-time adaptability remain challenges. Product catalogs must support flexible bundling and dynamic pricing to align with evolving monetization models.
Strategic Recommendations
- Start where you have influence—whether in product, billing, or entitlements.
- Audit existing tech for usage-friendly capabilities.
- Build a roadmap aligned with business problems and organizational readiness.
- Embrace hybrid models that combine subscriptions, usage, and outcome-based pricing.
Quantified Impact
A Forrester Total Economic Impact study commissioned by Revenera found:
- 426% ROI over three years.
- Payback period under six months.
- 90% reduction in time to launch new monetization models.
- Improved global compliance and customer experience.
Why It Matters
As AI capabilities accelerate, software companies must align pricing with real value. Flexible, dynamic monetization models are essential to remain competitive, support innovation, and meet evolving customer expectations.
Speakers
Lily Varon
Principal Analyst
Forrester
Michael Goff
Principal Product Marketer
Revenera
Frequently Asked Questions
AI monetization refers to the strategies software companies use to generate revenue from AI-powered features and products. As AI becomes embedded in more offerings, aligning pricing with the value delivered—especially in usage-based and outcome-driven models—is critical to profitability and customer satisfaction.
Unlike subscriptions that charge a flat fee over time, usage-based pricing bills customers based on actual product engagement—such as API calls, actions taken, or outcomes achieved. This model better reflects the value delivered, especially in AI-driven environments where usage can vary widely.
Generative AI enhances personalization, task automation, and data insights. As these capabilities grow, software companies are shifting toward monetizing specific actions or outcomes enabled by AI, rather than just access or features.
Agentic systems are advanced AI agents capable of autonomous decision-making and collaboration across platforms. Their ability to perform tasks independently necessitates new monetization models that focus on outcomes rather than user-driven interactions.
Companies can adopt credit-based systems where each AI-driven action (e.g., resolving a case or updating a record) is assigned a value. Salesforce’s model, for example, uses prepaid credits to monetize actions, offering a scalable and flexible approach to pricing.
Key challenges include capturing and transforming usage data, enforcing entitlements in real time, integrating billing and revenue systems, and maintaining compliance. A fragmented tech stack can complicate these processes, making strategic planning essential.
Usage data reveals how customers interact with products, helping companies identify high-value features, optimize pricing, and reduce revenue leakage. Clean, actionable data enables dynamic monetization and supports better product investment decisions.
Critical technologies include entitlement management systems, billing platforms, customer data platforms (CDPs), and data lakes. These tools must work together to capture, rate, and monetize usage events while supporting compliance and scalability.
Yes. Many companies combine subscriptions, usage-based pricing, and outcome-based models depending on the product and customer needs. Hybrid approaches allow flexibility and help align pricing with value across diverse offerings.
Begin by auditing your current tech stack, identifying gaps, and prioritizing areas where you have influence. Build a roadmap that aligns with customer outcomes and business goals, and leverage existing tools that are evolving to support usage-based models.
Resources
Case Study
a.i. solutions® Launch Flexible Licensing to Accelerate Growth
See how they saved two years in development time, reduced support tickets by 500%, and continue to grow.
Industry Report
Forrester Total Economic Impact Study
Learn More About 426% ROI and Operational Efficiencies Enabled by Revenera
Case Study
Toon Boom Drives Double-Digit Growth with Streamlined Monetization Processes
The implementation of the new licensing and entitlement management solution resulted in several tangible benefits for Toon Boom.
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