Price Value Discovery Questions

---
name: price-value-discovery-questions
description: Prepares a value discovery question set for one client call, with open questions on the outcome they want, what it is worth in their own numbers, the cost of doing nothing and their next-best alternative (their own AI included), plus an answer grid left blank for the client's words. Use for "run price-value-discovery-questions", "what is this worth to the client", "value discovery call", "questions before I price on value", "find out what the outcome is worth", "how do I ask about budget without asking about budget", "prep my discovery questions", part of the Pricing Under AI Pressure Pack by Polar Bear.
---

# Value Discovery Questions

## When To Use
You want to price on value and do not know what the work is worth to this client. Run it before the discovery call, so you walk in with a short set of honest questions, and again after it, to sort what the client actually said from what you assumed.

## When Not To Use
If the client has already told you the outcome, its worth and their alternative, go straight to the Value-Based Pricing Worksheet. If the call ahead is about the price itself, use the Price Conversation Prep Sheet instead.

## Inputs
- What you know about the client and the work so far: their message, the brief, your notes from earlier calls.
- Who will be on the call, by role, and how long you have.
- After the call: your notes, with the client's answers as they gave them.
If you have none of this, I start from the six question groups below and mark the set as a first draft.

## Approach
Economic value to the customer, from Forbis and Mehta (Business Horizons, 1981) and summarised by Utpal Dholakia in Harvard Business Review (2016): what the work is worth equals the cost of the client's next-best alternative plus the value that differs between you and it. You cannot compute that without the client's own numbers, so this skill only asks. The failure it prevents: a confident "value price" built on a figure you imagined during the drive to the meeting, which falls apart the first time the client asks where it came from. Today the next-best alternative is often the client's own AI, and the questions ask about it plainly.

## Workflow
1. I ask up to three questions: what the client has asked for so far, in their words; how long the call is; and what you already know about who decides.
2. I draft questions in six groups, in this order, because each one rests on the one before: the outcome and how the client would measure it; what it is worth in their numbers (revenue, cost, risk, time); the cost of doing nothing or of waiting; the next-best alternative (another provider, doing it in house, their own AI) and what that costs them; what differs between you and that alternative, good and bad; who decides and how.
3. Every question is open. I strip out leading and loaded ones ("wouldn't you agree this costs you a lot?") and anything that pushes the client toward a number. A question about their own AI is asked with curiosity, never as a trap.
4. You pick a short set that fits the call, usually one or two per group. A list of twenty questions turns a conversation into an interrogation.
5. I lay out the answer grid with a "client's words" column left blank. I never fill an answer, a number or a quote, not even as a guess.
6. After the call you paste your notes. You mark each value driver "stated by client", "inferred" or "unknown"; I sort the grid and list the gaps worth one follow-up email.

## Output Format
```markdown
# Value Discovery Question Set
Client: [client] | Call: [date, length] | Roles on the call: [roles]
## Questions for this call
| Group | Question | Why we ask |
|---|---|---|
| Outcome and measure | [open question] | [what it tells us] |
| Worth in their numbers | [open question] | [what it tells us] |
| Cost of doing nothing | [open question] | [what it tells us] |
| Next-best alternative (incl. their own AI) | [open question] | [what it tells us] |
| What differs, good and bad | [open question] | [what it tells us] |
| Who decides and how | [open question] | [what it tells us] |
## Answer grid (filled by you after the call)
| Value driver | Client's words | Their number, if given | Status: stated / inferred / unknown |
|---|---|---|---|
| [driver] | [left blank for you] | [left blank for you] | [your mark] |
## Gaps to follow up
1. [question still open]
## Decision
[You decide whether there is enough stated value to price on, or which follow-up to send first, by [date].]
```

## Done When
- Six groups are covered, in order, and every question is open.
- The "client's words" column is blank or filled only from your notes.
- Each value driver carries a status you set.

## Quality Bar
- No question suggests a number or a conclusion to the client.
- The client's own AI is treated as a fair alternative, never mocked.
- Notes record what was said, never a judgment of the person who said it.
- Answers are the client's own words; Claude never fills them in.

## Next
Run price-value-based-pricing (Value-Based Pricing Worksheet) to turn the answers into a price.

## About the makers

This pack is made by Polar Bear, a consultancy built by ex-McKinsey founders with a dream to make AI work for People, not instead of them. We help our clients build people systems and AI-first ways of working, and we run our own company on Claude. If your team has outgrown the self-serve version, message Pauline (linkedin.com/in/paulinebertry).