---
name: pricing-packaging-hypothesis
description: Create a pricing and packaging hypothesis, research plan, and low-risk validation path tied to customer value and unit economics.
argument-hint: [product-or-pricing-problem]
---

# Pricing and Packaging Hypothesis

Use this skill when the user wants to rethink pricing, packaging, value metrics, or monetization experiments.

## What this skill must produce

Always produce:

1. **Pricing problem statement**
2. **ICP / segment framing**
3. **Value metric options**
4. **Packaging hypothesis**
5. **Pricing hypothesis**
6. **Validation plan**
7. **Unit-economics implications**
8. **Risks / anti-patterns**
9. **Recommendation**

## Inputs to gather

If available, extract:
- current pricing page or model
- plan structure
- value metric
- target segments
- ACV / ARPU / churn / LTV / CAC
- upgrade patterns
- objections or sales feedback
- self-serve vs enterprise mix
- evidence of segment mismatch

If hard data is missing, create a research-driven first pass.

## Working rules

- Pricing, packaging, and positioning must be treated together.
- Start from customer value, not arbitrary competitor copying.
- Prefer a value metric that is understandable, aligns with customer needs, and grows with the customer.
- Explicitly segment by customer type where needed.
- Do not recommend naive pricing A/B tests when sample size or fairness makes them untrustworthy.
- Connect recommendations back to churn, ARPU, LTV, and CAC.

## Step-by-step method

### Step 1: define the pricing problem
Examples:
- low conversion
- high churn
- weak upsell path
- poor enterprise capture
- too much value given away
- segment mismatch
- no coherent value metric

### Step 2: define segments
State the most relevant segments and how their needs differ.

### Step 3: define value metric options
For each option evaluate:
- is it easy to understand?
- does it align with customer needs?
- does it scale with the customer?

### Step 4: define packaging
Sketch possible plan packaging and who each plan is for.

### Step 5: define pricing hypotheses
State clear hypotheses such as:
- a higher enterprise entry point will better match high-value buyers
- a usage-based value metric will align expansion with realized value
- a clearer middle plan will reduce decision paralysis

### Step 6: define validation path
Offer the safest realistic way to test:
- customer interviews
- willingness-to-pay research
- segmented sales validation
- concierge or manual quoting
- minimum viable pricing tests
- selected rollout

### Step 7: model implications
Qualitatively explain likely effects on:
- acquisition
- retention
- ARPU
- LTV
- CAC
- expansion

## Output structure

### Pricing problem statement
- What seems wrong:
- Evidence:
- Segment most affected:

### ICP / segment framing
| Segment | Need profile | Price sensitivity | Growth potential |
|---|---|---|---|

### Value metric options
| Option | Easy to understand? | Aligns to customer value? | Scales with customer? | Main risk |
|---|---|---|---|---|

### Packaging hypothesis
Describe:
- proposed plans
- who each plan is for
- included capabilities / thresholds
- upgrade logic

### Pricing hypothesis
Describe:
- proposed pricing direction
- why it may improve value alignment
- what it should improve operationally

### Validation plan
| Validation step | Goal | Evidence produced |
|---|---|---|

### Unit-economics implications
- Expected effect on acquisition:
- Expected effect on churn:
- Expected effect on ARPU:
- Expected effect on LTV:
- Expected effect on CAC:
- Expected effect on LTV:CAC:

### Risks / anti-patterns
- using the wrong value metric
- copying competitor pricing blindly
- underpricing premium segments
- overcomplicating plan design
- trying to A/B test pricing without power
- changing too much at once

### Recommendation
- Best current direction:
- What to validate next:
- What not to do yet:

## Special instructions

If the current model is clearly segment-mismatched, say so directly.

If enterprise demand exists but top-end packaging is capped, evaluate a contact-sales / custom plan path.

If the user asks for a pricing experiment, state whether:
- it is suitable for experimentation,
- what kind of experiment is realistic,
- and what research should precede it.