45ck 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:
- Pricing problem statement
- ICP / segment framing
- Value metric options
- Packaging hypothesis
- Pricing hypothesis
- Validation plan
- Unit-economics implications
- Risks / anti-patterns
- 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.