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Gabor-Granger Pricing Test

Get the revenue-maximizing price and the context to build a strategy around it.

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Capabilities

Find the price that earns the most revenue and understand why buyers are willing to pay.

Turn your price test into your pricing strategy

Buyers tell you why a price was too high or too low, so you know what to change, what to charge for it, and which buyers will pay more.

Understand the mental models behind buyers' price decisions

Buyers explain their choices in plain language and Listen codes the themes, so you can measure and report reasoning that used to be anecdotal.

Build a defensible narrative, not just a chart

Every point on the curve traces back to a real interview, so a challenge gets answered with buyer clips instead of your methodology.

Features

A conversational price ladder, in the studies your team is already running

Adaptive price ladder

Each buyer starts with a description of your product and decides whether they would purchase it at a particular price. Depending on their answer, they see higher or lower price points until you find the maximum price each person would pay.

Contextual follow up questions

Each person explains why the price they landed on felt worth it, and the AI interviewer keeps digging to separate "I can’t afford it" from "it is not worth that much." Listen then codes those answers into themes so you can turn anecdotes into data.

Demand and revenue curves

The demand curve shows how many buyers you keep at each price. The revenue curve points to the price that earns the most. Filter by segment to understand key groups on their own, without fielding a new study.

Messy answers are handled

Some answers can mess up the math. People who wouldn't buy at all stay in the count, so demand isn’t artificially inflated. Buyers who say yes to high prices and no to lower ones are counted separately. Half-finished ladders are dropped.