How To Launch Your First Action-Based Pricing Model
A Guide for High-Growth AI SaaS Companies
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Introduction
The AI industry is evolving rapidly, and monetizing AI-driven value effectively depends on having the right pricing strategy. Many high-growth AI SaaS companies—especially those in the early to mid-stages, with revenue between $2M to $50M—have relied on seat-based or plat- form-based pricing models. But as AI adoption accelerates and customer demands shift, it’s time to rethink how you monetize your product.
Action-based pricing—also called usage-based or pay-per-use pricing—has become a powerful strategy, particularly for AI companies delivering real-time value or continuous data processing. This model directly aligns revenue with product usage, providing a more scalable and flexible way to grow alongside your customers.
One of the best examples of this transformation happening in real time, was SalesForce’s September launch of AgentForce. These AI Agents were built to automate support conversations and tasks. The pricing strategy? It costs $2 every time the agent has a conversation. Pure action and usage based monetization. (See Figure 1)
This guide will explore why action-based pricing is essential for AI SaaS companies and walk you through how to implement it successfully. Whether you’re a product leader, CEO, or CFO, you’ll gain insights to help you deploy your first action-based pricing model and position your company for long-term success.
Figure 1: Revenue Model (Credit: Salesforce)
Why Action-Based Pricing Is Key To Growth in AI
The Evolution of AI SaaS Pricing
Traditional SaaS pricing models—like per-seat or feature-based pricing—are often poorly suited for AI products. AI solutions deliver value based on data volume, predictions generated, or model training frequency. These actions define the AI’s utility, making it crucial to align your pricing with usage rather than static licenses or platform access fees.
The Shift to Action-Based Pricing
Action-based pricing directly links revenue to customer outcomes. This model charges customers based on usage metrics like API calls, processed data, or AI models deployed—key actions that reflect the value delivered. It ensures customers pay for what they use while your revenue scales naturally with their growth.
Here are some real-life examples of AI companies leveraging action-based pricing:
OpenAI: Charges customers based on the number of tokens processed via its API, allowing revenue to grow in proportion to usage. This ensures seamless scaling whether customers send a few requests or thousands per second.
Clarifai: An AI-powered image and video recognition platform that charges by API calls or operations per- formed. This model captures revenue from enterprises processing millions of images while offering affordable entry points for startups.
Sift: A fraud detection platform that prices its service based on the number of events processed. This flexibility allows customers to scale without fear of overpaying during periods of low activity, appealing to businesses of all sizes.
Four Benefits of Action-Based Pricing for AI Companies
1
Flexibility for Customers: AI usage fluctuates based on customer needs or business cycles. Action-based pricing ensures customers only pay for what they use, reducing barriers to entry and allowing them to scale over time.
2
Revenue Growth and Predictability: Revenue grows proportionally as customer usage increases—whether through more API calls or larger data sets—creating a predictable and scalable revenue stream.
3
Low Friction for Adoption: Action-based pricing makes it easier for new customers to start small and grow over time, minimizing churn and fostering long-term relationships.
4
Aligned with AI’s Value Proposition: AI provides continuous insights or automation based on data. This model ensures customers pay in line with the outcomes they receive—whether through predictions, classifications, or fraud detection.
Steps To Implement An Action-Based Pricing Model for AI SaaS
Transitioning to action-based pricing requires thoughtful planning. Even early-stage AI companies can deploy it successfully by following these steps:
Step 1: Identify The Right Usage Metric
Choose the metric that aligns with your product's value. Key metrics might include:
- API calls
- Data processed
- Models trained or deployed
- Inferences generated
Pro Tip: Use metrics that are easy to track and clearly communicate value. For example, a predictive maintenance solution might charge based on the number of predictions generated or machines monitored.
Step 2: Design Packages to Support Your Pricing Plans
While action-based pricing provides flexibility, packaging options make it easier for customers to adopt the new model. Here are a few examples:
OpenAI
Offers API access to its models with pricing based on usage, measured in tokens (e.g., characters processed).
Source: openai.com - October 17, 2024
Algolia
A search API that employs a usage-based model based on the number of records indexed and search requests.
Source: aws.amazon.com - October 17, 2024
Databricks
Uses a pricing model based on compute usage for its machine learning and data analytics services.
Source: runonatlas.com - October 17, 2024
Step 3: Prepare Your Tech Stack
Make sure your platform can track and bill based on your usage metric. Early-stage companies can use lightweight, scalable tools.
- Billing Software - Platforms like Stripe, Chargebee, or Atlas can automate your usage-based billing.
- Analytics - Use tools like Mixpanel or Amplitude to track user behavior and key metrics.
- Infrastructure - Ensure your API can scale with customer demand.
Step 4: Roll Out Gradually with Customer Feedback
Launch your new pricing model with a pilot program. Start small, gather feedback, and iterate.
- A/B Testing - Test different usage metrics or tiers to find the best fit.
- Customer Feedback - Use surveys and interviews to refine your pricing before full rollout.
Step 5: Transparent Communication is Critical
Explain your new pricing clearly and highlight its benefits to your customers. Transparency helps build trust and minimizes friction.
Price Calculator
Provide customers with tools to monitor usage in real-time and avoid surprises.
Onboarding
Offer an FAQ or training session to walk customers through the new pricing structure.
Why Action-Based Pricing Is The Future for AI SaaS
AI products deliver immense value through automation, insights, and data-driven decisions. Action-based pricing is the ideal model to capture that value and align it with your customers’ success.
By transitioning to this model, your company can achieve scalable, predictable revenue growth. Whether you’re a young AI startup or scaling rapidly, adopting action-based pricing will position you to lead in the evolving AI market.
Looking for billing infrastructure to power your usage-based pricing model? Explore Atlas, where you can build and launch pricing models without code. Start scaling with a flexible platform designed for AI companies on the rise.
Learn more at Atlas.
