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Why Consumption Pricing Makes Forecasting Harder with Devavrat Shah

Why Consumption Pricing Makes Forecasting Harder with Devavrat Shah

Revenue Builders vor 4 Monaten

In this replay segment, Devavrat Shah explains how AI can help teams learn across cohorts, spot patterns in uneven data, and create more trust in a forecast that would otherwise depend on isolated judgment calls.

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Consumption pricing puts pressure on the forecast in places
traditional SaaS models rarely exposed. Total usage may be easier
to model from the CFO’s seat, but the field still has to answer
harder questions: which customer, which channel, which rep, and
when. In this replay segment, Devavrat Shah explains how AI can
help teams learn across cohorts, spot patterns in uneven data,
and create more trust in a forecast that would otherwise depend
on isolated judgment calls.

Devavrat Shah is an MIT professor, director of MIT’s Statistics
and Data Science Center, and co-founder and CEO of Ikigai Labs.
He brings a data science and operator’s perspective to
forecasting, consumption pricing, and enterprise AI.

Connect with Devavrat:

LinkedIn

Listen to the full episode here:

Understanding AI Through History and Practical Application
with Devavrat Shah

Hosted by five-time CRO John McMahon and Force Management
Co-Founder John Kaplan, the Revenue Builders podcast goes behind
the scenes with the sales leaders who have been there, done that,
and seen the results.

This show is brought to you by Force Management. We help
companies improve sales performance, executing their growth
strategy at the point of sale.

Connect with Us:

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Force Management