Design pricing strategy around customer value, segments, willingness to pay, value metric, competitive context, unit economics, adoption friction, and long-term positioning rather than copying market price points.
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---
name: pricing-strategy
description: Design pricing strategy around customer value, segments, willingness to pay, value metric, competitive context, unit economics, adoption friction, and long-term positioning rather than copying market price points.
---
# Pricing Strategy
Use when deciding what a product should charge, how price should scale, or how an existing model should change.
## Procedure
1. Define target segments, customer value or outcomes, alternatives, budget owner, purchase context, and the strategic role of price.
2. Review current pricing research, willingness-to-pay evidence, win-loss, usage, cost structure, and competitive context.
3. Choose a value metric that scales reasonably with customer value and can be measured, explained, billed, and forecast without perverse incentives.
4. Define candidate price levels and fences by segment or package while keeping the model understandable enough for customers and operations.
5. Model conversion, expansion, gross margin, revenue, support burden, and customer behavior across realistic usage scenarios.
6. Consider free trial, free tier, discounting, annual commitment, minimums, overage, grandfathering, and migration only where they support the strategy.
7. Identify risks such as bill shock, gaming, under-monetized heavy use, price cliffs, sales friction, or incentives that discourage desired usage.
8. Validate through controlled experiments, sales evidence, or phased rollout and set trigger conditions for revisiting the strategy.
## Decision rules
- Competitor price is context, not the answer.
- The value metric can matter as much as the headline price.
- Pricing should reinforce desired customer behavior, not punish product adoption accidentally.
- Do not claim willingness to pay without customer evidence.
## Quality gate
The strategy is ready when price and value metric connect to customer value, segment and unit-economic effects are modeled, migration and behavioral risks are visible, evidence supports the proposed range, and the team knows how the decision will be validated after rollout.
