Pricing Test — find the price without burning the market

Most prices are archaeology: set once at launch, defended forever. Yet price is the fastest profit lever in the business — a rise flows almost straight to margin — and it goes untested because a botched test torches trust. The fix is not bravery, it is design: small surface, one change, clean read, decided in advance.

Inputs

• Current price and model, what you suspect is wrong with it, and what is being sold: $ARGUMENTS
• From marketing-brief.md if present: the offer (price and its logic), numbers that matter (conversion at the current price, acquisition cost), objections & beliefs (price objections), and any willingness-to-pay evidence — deals lost on price, and deals that closed suspiciously easily. Closing too easily is the under-pricing signal everyone ignores.

Do this

1. Establish the baseline: current price, close rate or conversion at that price, and revenue per prospect. This is the number the test must beat.
2. Write the hypothesis: "We believe [segment] will accept [price or structure] because [evidence]." No because, no live test — run willingness-to-pay research first. A live test is the expensive way to ask what research answers cheaply.
3. Choose ONE structure to change:
   • Band test — the same offer at a higher price, shown to a new cohort only.
   • Anchor test — add a premium tier whose job is to reframe the core price.
   • Packaging test — the same total value re-split so old comparisons break.
4. Design the trust protection: new prospects only — existing customers are never repriced mid-relationship without being told; every quoted price gets honoured; decide up front what test-cohort buyers get if the test price wins or loses. No fictional strikethrough "was" prices.
5. Define the read: enough purchase decisions per cell to believe the result — rough sanity maths, not false precision. Low-volume businesses read sales calls and close-rate shifts, not dashboards. The deciding metric is revenue per prospect, not close rate.
6. Write the decision rule before launch: "If revenue per prospect is at or above X after N decisions, the new price is the price. Below Y, revert. Between the two, extend once, then decide." Put the review date in the calendar.
7. Log it in marketing-brief.md: the test card goes into Learnings & experiments now; when the test decides, update the offer section's price and its logic — the brief's price is the real one.

Output

The pricing-test one-pager: baseline, hypothesis with its evidence, chosen structure and why, trust rules, read plan with the sample logic, decision rule, start and review dates.

Rules

• Never test on existing customers unannounced. One trust breach costs more than a year of price optimisation earns.
• Revenue per prospect decides, not close rate — a lower close at a higher price often makes more money.
• One structural change per test. Price and packaging moved together produce an unreadable result.
• Evidence over invention: if willingness-to-pay evidence is thin, say so and gather it first rather than dressing a guess as a hypothesis.
• Anchor tiers must be real products someone can buy. A decoy you would refuse to sell is a lie with a price tag.