Great insights, and I love the idea of moving to outcome based pricing one step at a time. For outcome based pricing to work three conditions need to be met. (i) The outcome can be clearly defined. (ii) Attribution of what caused the outcome can be agreed on (causalML will help with this). (iii) The outcomes can be at least somewhat predicted. Value models help will companies meet all thee of these conditions.
Intercom FinAI is a good example. The outcome is successful resolution of the ticket. The attribution is to Fin AI as it is an agent and does the task. There is a lot of data in most customer success systems that makes it easy to build predictive models. Agents are good candidates for outcome based pricing as it is often easier to meet these three conditions, especially attribution.
Great insights, and I love the idea of moving to outcome based pricing one step at a time. For outcome based pricing to work three conditions need to be met. (i) The outcome can be clearly defined. (ii) Attribution of what caused the outcome can be agreed on (causalML will help with this). (iii) The outcomes can be at least somewhat predicted. Value models help will companies meet all thee of these conditions.
Thanks Steven. I like these 3 conditions!
Intercom FinAI is a good example. The outcome is successful resolution of the ticket. The attribution is to Fin AI as it is an agent and does the task. There is a lot of data in most customer success systems that makes it easy to build predictive models. Agents are good candidates for outcome based pricing as it is often easier to meet these three conditions, especially attribution.