Insights · 2 Jun 2026 · 6 min read · Iordanis Passas

How to price friction in your own currency

In three points

A friction finding becomes fundable when it is stated in the currency the business already counts.
Three conversion formulas cover most products: lost completions, support cost, and time burned.
Multiply by confidence before you present — a priced guess ranks below a smaller priced observation.

“Users struggle with the date picker” is an observation. “The date picker costs us roughly €340,000 a year in abandoned renewals” is a decision waiting for a signature. Same finding — the difference is a unit conversion, and the conversion is arithmetic anyone can do in an afternoon.

RUCF calls this recoverable cost, and it is the numerator of the priority formula: priority = recoverable cost × confidence ÷ effort. Here is how to compute it for the three product shapes that cover almost everyone.

Revenue products: lost completions

recoverable cost = abandonment at the step
                 × traffic reaching the step
                 × value per completion
                 × recoverable share

The last factor is the honest one. Not every abandonment is friction — some visitors were never going to buy. Estimate the recoverable share from a comparable step you have already improved, or default to a conservative third. A number built on “all abandonment is our fault” gets taken apart in the meeting, and deserves to be.

Support-heavy products: contact cost

recoverable cost = contacts attributable to the surface
                 × fully loaded cost per contact

Read the last fifty tickets and count how many are questions the interface should have answered — that share is your attribution, and it doubles as the behaviour reading for the content clarity signal. Cost per contact, fully loaded, is a figure your support lead already has.

Internal tools: time burned

recoverable cost = seconds lost per session
                 × sessions per year
                 × loaded cost per employee-second

This is the formula that turns fourteen seconds of date-picker theatre at 40,000 sessions a month into a number with commas in it. Internal tools accumulate silent friction faster than anything else you own, because their users are paid to endure them and have nowhere to churn to.

Then multiply by what you actually know

The step most pricing exercises skip: multiply the cost by the confidence of the evidence behind it. A €500,000 cost supported by a guess (0.30) enters the ranking at 150,000; a €200,000 cost you observed (1.00) enters at 200,000 and correctly outranks it. This is the mechanism that stops the biggest number in the room from automatically winning — and it is why every prioritisation model that omits confidence eventually gets used to justify expensive work on a hunch.

Signals this affects

Pricing runs on top of any signal, but starts easiest with task completion, content clarity and trust signals, where the counting is already native.

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