# Explore a Pricing Decision

> Investigate price objections and packaging before testing real purchasing behavior.

Source: https://imario.ai/docs/playbooks/pricing-study

A pricing study can reveal perceived value, objections and comparison logic. It does not establish what people will pay when money is at stake.

## Start with the buyer

Choose an audience matching the purchase decision, not merely the product user. Inspect category familiarity and source coverage. If comparing segments, keep the offer and questions identical.

Use **New Task → Interview** to explore the reasons first. Draft a guide that moves from current practice to the proposed price:

- What do you currently use to solve this problem?
- How do you decide whether a solution is worth paying for?
- At this price, what would make you hesitate?
- What evidence would justify the purchase?

Present the product and billing unit clearly. A monthly price without whether it is per seat or per team is ambiguous.

## Quantify a specific hypothesis

After inspecting interviews, use a [Survey](https://imario.ai/docs/research/survey) for structured reactions to defined packages, or a [Preference test](https://imario.ai/docs/research/preference-test) for alternatives. Avoid turning a leading question into an apparent measure of demand.

## Read by segment

Use [Explorer](https://imario.ai/docs/run-and-analyze/explorer) to separate price resistance from low product relevance. Check whether the strongest objection comes from people who would never be buyers in the first place.

Budget interviews by their actual question types and count; [reports](https://imario.ai/docs/run-and-analyze/reports) are separate. See [Pricing & credits](https://imario.ai/docs/workspace/pricing).

Confirm a final price through observed purchasing behavior or appropriately designed real research. Report synthetic answers as directional evidence about the offer, not revenue forecasts.