pricing-packaging-hypothesis

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.