Guide
A pricing change that has to stand
On paper, a price change is one of the most reversible decisions a company makes. In the market it's one of the least. Customers remember, sales teams build habits around it, and competitors respond. It deserves the same discipline as an acquisition, and it rarely gets it.
The questions a price change must answer
- Who does it apply to: new customers, existing customers, or both?
- What happens to volume? This is usually the biggest unknown.
- What happens to churn at renewal?
- What does it do to ARR and margin, under each answer to 2 and 3?
- Can it be reversed, for whom, and at what cost?
The shape on the desk
Talk the options through in the corridor register. Raise for all, raise for new customers only, add a tier, or do nothing.
Convert to Review. The evidence ledger and an adversary come on. Known figures, such as seat counts and current price, sit on one line. Unknowns, such as volume response and churn, sit on another.
Put it on Quant. Enter ARR₀ and the volume response you're willing to assume. Quant writes the result as an expression of those variables. If churn is missing, the desk names the gap rather than filling it.
Pack the paper. Conclusion, constraints, options, recommendation and counterargument.
Worked shape (fictional)
Known: 1,240 mid-market seats at $49 (billing system). Support cost per seat up 18% (finance pack). Unknown: volume response, since prices have never been raised. Renewal churn after a rise. Assumption: new-customer conversion falls by no more than 10% (sales leader's estimate, labelled as such). Derived: +$10 per seat ≈ +20% revenue per new seat, if conversion holds. Counterargument (adversary): the case rests on an unmeasured assumption. Recommendation: raise for new customers only, measure conversion weekly, and revisit if it falls more than 10% for four weeks.
What you leave with
A recommendation with its conditions attached, and a list of what you'd need to know to remove them. Copy the structure from the decision memo template.
Positioning questions
If the question is less about the number and more about the offer, such as what customers are paying for or how to frame the change, Brandium is the FIA Labs brand desk. Its Model mode prices from the cost stack you type. On an FIA Plan seat, you can send Brandium an FIA Brief.
Questions
Can AI predict how customers will react to a price rise?
Not from nothing. ExecMind won't invent elasticity. It shows the result as an expression of the variables you supply.
Should we raise prices for existing customers too?
It depends on churn risk and contract terms. The desk lays out both options with their unknowns. You decide.
Where do positioning questions go?
To Brandium, the FIA Labs brand desk. With an FIA Plan seat, you can send it an FIA Brief and read the reply.