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Usage forecasts that flag customers drifting off plan

Forecasts each customer's usage and alerts the team when a customer drifts from it, where closed-won and churn don't have clean definitions

Chris Prinz GTM Engineer, Modal LinkedIn

  1. The problem

    Modal customers can go from zero to hundreds or thousands of GPUs, so workloads are spiky. That makes revenue unpredictable and leaves expansion, contraction and churn loosely defined. Revenue forecasting, spend propensity and churn prediction are hard when you can't easily define "closed won" or "closed lost."

  2. What they built

    With Justin Dignelli, Chris treated the problem as forecasting and anomaly detection. He built an ontology of Modal's business, product and space, applied it to Modal's data, and used it to build a model that tracks and forecasts each customer's usage. When a customer deviates from the forecast, an alert goes out so someone can engage the customer and find out what's going on.

  3. So what

    In a usage business, the warning sign is a change in usage, not a deal stage. This flags customers who drift from their forecast and sends someone to talk to them.

Under the hood

For GTM engineers

The ontology is created automatically rather than by hand-tagging, and can be applied across meeting transcripts, notes, Slack, email and support tickets, with Jev doing the batch classification. The ontology is used to create features in a multivariate time series model that forecasts usage; deviations from the forecast trigger an alert. Built with TypeSafe AI.

Source

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