Value based pricing is the key to sustained growth in B2B SaaS. But having a value model and a value based price is just the beginning. You have to be able to communicate that value in a value story. The form of the value story evolves over the customer journey.

Certain pricing metrics are associated with AI applications. In this year’s PeakSpan Ibbaka Survey of NRR we are seeing pricing metrics associated with AI showing up in multiple verticals, a significant change from last ear.

Generative AI application monetization is still in early days. Michael Mansard from Zuora has done some hard thinking about this. He shares his insights in this Ibbaka interview.

There has been a lot of doom and gloom about trends in Net Revenue Retention. But there are still some companies driving extraordinary performance. We look at one example from the open PeakSpan Ibbaka Survey on Net Revenue Retention in 2024.

Will generative AI apps require generative pricing? And what might generative pricing be? We asked a generative AI to get a recursive perspective on this.

Net Revenue Retention depends on more than churn/retention. There are six factors that determine NRR. Which are you prioritizing? Take the PeakSpan Ibbaka 2024 NRR Survey and we will share out insights.

A recent poll found that 40% of pricing, design and product management leaders believe that generative AI will require new approaches to pricing. What might these new approaches look like? We explore this using concept blending with the help of generative AI.

Peakspan and Ibbaka collaborate each year on a survey to understand how B2B SaaS companies approach Net Revenuer Retention (NRR). The survey results are used to benchmark NRR performance by SaaS vertical and to help SaaS operators improve NRR performance.

The Mark Stiving and Steven Forth webinar attracted about 500 people and there were a lot of questions asked in the chat. This is the third of a series of posts where we answer these questions.

The Mark Stiving and Steven Forth webinar attracted about 500 people and there were a lot of questions asked in the chat. This is the second of a series of posts where we answer these questions.

The Mark Stiving and Steven Forth webinar attracted about 500 people and there were a lot of questions asked in the chat. This is the first of a series of posts where we answer these questions.

There has long been speculation that AI will enable a shift to outcome based pricing, overcoming objections based on attribution, predictability and accountability. Intercom’s pricing of its Fin AI Agent is evidence that this is beginning to happen. Will AI lead to outcome based pricing?

Value models integrate different types of information: about the customer, about the improvement claims, about the industry and economy along with assumptions that are part of the model. Bringing these different types of information together drives insights that are not available when the data is managed in silos.

Last fall Ibbaka research found that the most common pricing metric for AI applications was per user. This was confirmed in a recent survey by Kyle Poyar and Palle Broe for Growth Unhinged. What are the reasons for this?

Many companies focus on cost reduction as the easiest value driver to define. But there often cases where revenue is a more powerful value driver. Why do so many pricing and marketing teams default to cost value drivers? Revenue value drivers are playing a key role in green or sustainable solutions.

Major generative AI vendors are looking for ways to make solutions more compelling, that is to say higher value. What are the emergent strategies? How are they creating value? How will this value get priced?

AI is changing what we price. That is the theme of our April 26 talk at the Professional Pricing Society conference in Chicago. But it is also changing how we price. Let’s open up our thinking and explore different ways we could apply AI to pricing.

Total Cost of Ownership (TCO), Return on Investment (ROI) and Value are ll used in price setting an justification. How are these related? Which approach works best? A value model is at the heart of a successful value program and critical to managing churn.

SaaStr recently had a series of interesting posts on pricing. One of them tells the story of a new CRO justifying price increases because of higher costs. Is this ever a good move for a SaaS company?

Many companies start worrying about pricing when they encounter a symptom that they associate with a pricing problem. A classic example is churn. But pricing is only one of the possible causes of churn. Trying to fix churn by changing pricing will only work in certain circumstances.