
Consumption Forecasting: What It Is & How to Do It
Consumption forecasting is no longer a niche strategy, it’s a necessity for SaaS, IaaS, and digital service companies adopting usage-based…
Consumption forecasting is no longer a niche strategy, it’s a necessity for SaaS, IaaS, and digital service companies adopting usage-based…
Revenue forecasting sits at the core of any growing SaaS or IaaS business. It’s how leadership plans investments, how teams prioritize resources, and how companies communicate confidence to investors. But for all its importance, revenue forecasting is often stitched together from disconnected spreadsheets, rigid CRM reports, and models that fail to adapt as the business evolves.
As businesses move deeper into the world of usage-based pricing, one of the most transformative changes is the shift in how revenue is forecasted. Gone are the days when revenue was purely driven by upfront contracts and renewals. In today’s environment, a significant portion of revenue comes from the ongoing consumption of products and services, which grows over time, especially through expansions.
As more companies adopt usage-based pricing models, managing renewals and forecasting consumption has become increasingly complex. These changes demand that organizations evolve how they track and manage revenue, shifting from traditional pipeline and booked deal management to focusing on usage and associated revenue. This shift is reshaping how businesses forecast renewals and plan for the future.
Usage-based billing is quickly becoming the dominant revenue model for companies. From cloud infrastructure to SaaS, media, and AI platforms, companies are increasingly adopting pricing strategies that tie revenue directly to customer usage.
Across the SaaS industry, one of the most significant shifts in recent years has been the move away from fixed-fee subscription models and toward consumption pricing models. These usage-based pricing structures are changing how companies generate revenue, how customers adopt software, and how success is measured.
As more businesses transition to consumption or usage-based revenue models, the comparison of Actuals vs. Forecasts needs to become a central focus. This analysis is key to navigating the variability inherent in these models and ensuring that companies can adapt quickly to changing customer behavior and market conditions.
Consumption-based revenue models introduce a layer of complexity that traditional forecasting methods struggle to handle. Unlike fixed revenue contracts, consumption revenue is dynamic—fluctuating based on customer behavior, seasonality, product adoption, and a host of other variables. To get ahead, businesses need to rethink their approach to forecasting.
As businesses shift to consumption-based go-to-market strategies, forecasting revenue has become increasingly complex. Whether it’s API calls, data storage, or platform usage, traditional forecasting methods designed for fixed or subscription pricing models no longer suffice. Organizations need a more dynamic approach to predicting revenue growth—one that accounts for real-time customer usage and adapts to changing consumption patterns.