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The Evolution of SaaS Pricing in the AI Era

๐ŸŒˆ Abstract

The article discusses the impact of AI on the traditional seat-based pricing model in the SaaS industry. It explores emerging pricing models, such as work/usage-based pricing and outcomes-based pricing, as alternatives to the seat-based approach.

๐Ÿ™‹ Q&A

[01] The Seat-Based Pricing Model and AI

1. How is the seat-based pricing model being challenged by the integration of AI into SaaS platforms?

  • The article explains that AI's ability to automate tasks traditionally performed by humans reduces the need for multiple user licenses, making the seat-based model less practical.
  • Examples are provided, such as AI-driven customer support systems reducing the number of seats needed, and Salesforce sales engineers noting a 10% reduction in seats due to the use of Einstein AI.

2. What are the key reasons why the seat-based pricing model may become less relevant?

  • The value derived from the software is less about the number of users and more about the amount of work being accomplished by the AI.
  • AI can automate many tasks that once required human intervention, reducing the need for multiple user licenses.

[02] Emerging Pricing Models

1. What are the two main emerging pricing models discussed in the article?

  • Work/usage-based pricing: Charging customers based on the amount of "work" the software performs or the usage of the software/AI agents.
  • Outcomes-based pricing: Tying the cost of the software to the outcomes achieved using the software, focusing on measuring the value provided to the customer.

2. What are some examples of companies implementing these new pricing models?

  • Work-based pricing:
    • Clay: Charges based on the number of automation credits used
    • Heygen and Synthesia: Charge based on the number of minutes of AI-generated videos
    • AirOps: Charges based on the number of tasks performed
  • Outcomes-based pricing:
    • Customer support AI agents: Charge per successful ticket resolution
    • Vendr and Chargeflow: Charge a percentage of the savings or chargebacks they generate for customers

3. What are some potential concerns with work-based pricing models?

  • The article notes that work-based models can provide a high level of uncertainty to the end customer, as they are not truly recurring revenue. To address this, startups may find it beneficial to tier their pricing with a mix of stable monthly amounts and volume-based tiers.

[03] Hybrid Pricing Approaches

1. How are some incumbent companies approaching the transition to new pricing models?

  • Many incumbent companies will still rely on seat-based pricing, particularly if the core of the software is still based on user seats (e.g., CRMs, Docs).
  • However, they are adding work-based components, such as treating AI as an add-on per seat that users pay extra for (e.g., Notion, Salesforce).
  • This hybrid approach allows them to transition gradually while still leveraging AI's capabilities and capturing some of the potential benefit of the AI features they launch.

2. How can startups leverage new pricing models to their advantage?

  • Startups, particularly AI-agentic ones rather than copilots, can adopt closer to work-based or outcomes-based pricing models to differentiate themselves from incumbents, who may find it harder to overturn their seat-based models.
  • The pricing model itself can help startups counterposition themselves against incumbents.

[04] The Opportunity in Transitioning Pricing Models

1. How did NICE's AI solution impact their customer's seat usage and overall costs?

  • NICE's client reduced the number of seats they needed from 1,000 to 750, a 25% reduction, due to the AI solution.
  • However, NICE was able to grow their ACV in the account from $3M to $4.5M, while the customer's aggregate cost for customer support went down from $50M to $37.5M, resulting in a win-win scenario.

2. What does this example suggest about the potential opportunities in transitioning pricing models?

  • Even though seats may decline due to AI automation, companies can still grow their revenue by offering AI-based solutions and transitioning to new pricing models that capture the value of the AI.
  • This can lead to a win-win situation where the vendor increases revenue, and the customer reduces their overall costs.
Shared by Daniel Chen ยท
ยฉ 2024 NewMotor Inc.