Design product pricing based on customer value, competitor offerings, and willingness to pay. Compare charging models, define plan tiers and included features, and outline experiments to test prices and assumptions before introducing a new pricing structure.
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Analyze and design pricing strategies including pricing models, competitive pricing analysis, willingness-to-pay estimation, and price elasticity. Use when setting prices, evaluating pricing models, preparing for a pricing change, or comparing freemium vs paid approaches.
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Design a pricing strategy grounded in value delivery, competitive positioning, and willingness to pay.
You are developing a pricing strategy for $ARGUMENTS.
If the user provides files (competitor pricing, survey data, financial models, or usage data), read them first. Use web search to research competitor pricing if needed.
Understand the value delivered:
Evaluate pricing models — recommend the best fit:
| Model | Best For | Example |
|---|---|---|
| Flat-rate | Simple products, predictable costs | Basecamp ($99/mo flat) |
| Per-seat | Collaboration tools, team products | Slack, Figma |
| Usage-based | Infrastructure, API products | AWS, Twilio |
| Tiered | Products with distinct user segments | Most SaaS (Free/Pro/Enterprise) |
| Freemium | Products with viral/network effects | Spotify, Notion |
| Freemium + usage | Platform products | Vercel, OpenAI API |
| Value-based | High-impact enterprise tools | Salesforce, Palantir |
Analyze competitive pricing:
Design the pricing structure:
Estimate price sensitivity:
Plan pricing experiments:
Output a pricing recommendation:
Recommended Model: [Model type]
Value Metric: [What you charge on]
| Tier | Price | Target Segment | Key Features | Positioning |
|---|---|---|---|---|
Key Assumptions:
- [Assumption] → [How to test]
Risks:
- [Risk] → [Mitigation]
Think step by step. Save as markdown. Flag any assumptions that need validation before launch.
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Analyze A/B test results to decide whether to launch a change, extend testing, stop, or investigate further. Check sample size, statistical significance, uncertainty ranges, and effects on other important metrics, then summarize the recommendation and next steps.
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Organize customer feature requests into themes and rank the top three against product goals, customer value, effort, and risk. For each recommendation, explain the underlying need, possible alternatives, uncertain assumptions, and simple ways to test them.
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Compare growth options across existing and new products and markets using the Ansoff Matrix, a four-part planning framework. Assess opportunities, resources, competition, and risks, then develop market launch plans and a phased roadmap for priority options.
中文简介正在准备中。当前显示英语简介。
Choose the first customer segment for a product launch by comparing urgent needs, willingness to pay, achievable market share, and referral potential. Get scored recommendations, a priority segment, a 90-day acquisition plan, and expansion options.
中文简介正在准备中。当前显示英语简介。
Plan low-effort experiments to check assumptions about an existing product before building a feature. Compare prototypes, A/B tests, and other methods, with a clear assumption, procedure, metric, and success threshold for each experiment.
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Turn a new product idea into a testable hypothesis and two or three simple experiments. Define target customers, expected actions, measurement methods, and success thresholds to assess demand through behavior such as sign-ups, pre-orders, or paid commitments.
中文简介正在准备中。当前显示英语简介。