Create Three Pricing Packages Without Racing to the Bottom

Three pricing packages should offer three meaningful ways to solve the customer's problem, not the same service with arbitrary labels. The differences need to reflect scope, support, risk, and delivery economics.

This guide helps you create three differentiated packages with a clear customer fit, outcome, scope, boundaries, economics, and upgrade logic.

What you need

• Your delivery costs, capacity, minimum acceptable economics, and target margin
• Customer segments, desired outcomes, and common scope differences
• Existing prices, win-loss notes, and approved terms

The workflow

1. Protect the floor first

Know the minimum price and scope that produce sustainable delivery. AI cannot set this without accurate costs, capacity, and owner judgment.

2. Differentiate by value and complexity

Packages should solve meaningfully different situations, not hide the same work behind arbitrary feature counts.

3. Make boundaries visible

Each option needs deliverables, support, speed, revisions, customer effort, exclusions, and change rules.

4. Test the choice architecture

The middle package should not be a trick. Each package must be a responsible fit for a real customer segment.

Copy this working prompt

Replace every bracketed field with verified information from your business. If you do not know something, write unknown instead of guessing.

Help me structure three service packages. Do not choose final prices.

Service and customer outcomes:
[DESCRIBE]

Customer segments or situations:
[DESCRIBE REAL DIFFERENCES]

Delivery steps, costs, capacity, and minimum economics:
[PASTE VERIFIED INTERNAL FACTS]

Existing price and sales evidence:
[PASTE WIN-LOSS NOTES, CURRENT PRICES, OR WRITE LIMITED DATA]

Scope variables:
[LIST SPEED, DEPTH, ACCESS, SUPPORT, REVISIONS, CHANNELS, OR OTHER VARIABLES]

Non-negotiable boundaries:
[LIST]

Design three package concepts with:
1. Best-fit customer situation
2. Outcome
3. Deliverables
4. Timeline
5. Support and access
6. Customer responsibilities
7. Included and excluded
8. Cost and capacity inputs required for a final price
9. Upgrade logic
10. Risks of underpricing or over-scoping
11. Questions to validate with customers

Do not invent willingness to pay, market rates, costs, margins, demand, or competitor prices. Mark every financial assumption [VERIFY].

Run a second-pass review

The first output should not be the final answer. Use this challenge prompt to find weak evidence, hidden assumptions, or avoidable risk.

Challenge these packages for fake differentiation, hidden delivery cost, confusing overlap, excessive custom work, and a low tier that cannot be delivered profitably.

What good looks like

• Each package fits a real situation
• Scope and support differ clearly
• Final prices wait for verified economics

Review before you use it

• Did a qualified owner verify costs and margins?
• Can the team deliver every option repeatedly?
• Is the lowest tier still a good customer outcome?

Privacy and judgment guardrails

• Remove passwords, payment details, private health information, and confidential customer data before pasting anything into an AI tool.
• Treat the output as a working draft. A person remains responsible for the decision, promise, price, and final send.
• Do not let AI invent customer quotes, financial figures, legal terms, capabilities, deadlines, or proof.

Your next action

Estimate delivery hours and direct costs for one realistic customer in each package before discussing price language.

If your AI tool still lacks the context to do this well, first Build the context behind your pricing decisions.