With stage criteria and a deliberately crude model, then replace the assumptions as real data arrives.
With too little history for a model, what the buyer is doing is the best signal available. Kaypo reads it per deal rather than relying on an average you do not have.
That company had no revenue operations function and no conversion history at all. The first forecast ran on deliberately crude assumptions, published as assumptions, and each one was replaced with real data as it arrived.
Write exit criteria so staging is consistent, forecast activity you can count, apply crude conversion assumptions, and publish the assumptions alongside the number.
Around four quarters of closed opportunities with stage history. Below that, state the sample size beside the rate rather than implying precision you do not have.
As a placeholder, labelled as such, with a date for replacing them. Benchmarks describe other companies, not your motion.
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