How Monte Carlo's Daily Revenue Model Rewrote Their Strategy

May 30, 2025 / pricing, AI

Pricing changes are hard.

Fundamental shifts in go-to-market strategy tied to pricing? Monumentally difficult.

We recently dove deep into one such transformation with Barr Moses, CEO of Monte Carlo, during a Theory Ventures Office Hours. Monte Carlo, a data & AI observability pioneer, moved from traditional annual contracts to a daily revenue model.

These were the three most important takeaways for me from the conversation:

Monte Carlo customers were used to buying usage-based rather than contract-based & the alignment was an important & critical evolution. Ali Ghodsi said the annual contract is “selling like Oracle in the 1980s.”
The shift to daily revenue was a fundamental cultural change. First Barr asked every functional leader to pick who should own pricing. Ultimately, everybody but product decided it should be product. That settled, the go-to-market team “redefined the job functions for everyone in the go-to-market starting from scratch.”
Last, the company evolved through a cultural change, pursuing one key metric that everybody could align with : daily revenue. It was clear from our conversation that this is more than just a pivot. It’s a fundamental reimagining of the core operations of the company. The company embarked on an internal rebrand including “MCCC - The Monte Carlo Consumption Company.”

This involved “changing the language both inside of the company & with the board around one key metric.” As a VC, I felt 15 years of education about at ARR & ACV had been rightly thrown out the window. This daily figure brought “tremendous simplicity” & was crucial for optimizing for learning in the early days. It became, as Barr termed it, the “ultimate bet on yourself & your team.”

https://www.youtube.com/watch?v=list=PLWyXqNxVbHP2qY4BL40Kst473-kF3TBPN&index=16

This move has had profound effects on the company :

True Customer Alignment wiht Shared Risk, Shared Success: The model “forces the company to take part in the customer success.”
Deeper Customer Insight: Success demands understanding customer roadmaps.
Product Clarity: Usage focus drove insights, like fixing default permissions that inhibited adoption which wouldn’t have been obvious otherwise.
Enterprise Predictability: Commitment models (RPOs) still offer budget predictability for larger clients particularly with longitudinal data.

Monte Carlo’s journey is a powerful testament: pricing reflects your entire GTM philosophy & commitment to customer value. It’s a dare few take so comprehensively, but the rewards in alignment & customer-centricity are immense.