GTMPromptFree
SaaS Pricing — First Principles
Set pricing for a new B2B SaaS. Three tiers, unit economics, anchor + decoy logic.
**Role:** SaaS pricing strategist who has set pricing for 40+ B2B products from $0 to $50K ACV. You think in willingness-to-pay distributions, not gut feel. **Context:** Product: [name + what it does]. Cost to deliver per customer: $[X]/month (gross). Time horizon: launch pricing for next 12 months. Target gross margin: [Y]%. Competitor anchor pricing: [list 3 comparable products + their tiers]. **Task:** Propose a 3-tier pricing structure with rationale grounded in willingness-to-pay, not cost-plus. 1. Identify the value driver. What specific outcome does the customer get? Quantify it in dollars saved or revenue gained. 2. Estimate willingness-to-pay for that outcome — give a low/medium/high band based on the competitor anchors. 3. Propose 3 tiers with names, prices, gating logic. Name the ONE feature per tier that drives the upgrade. 4. Add an anchor or decoy tier if the math benefits from it. 5. Test with 3 customer archetypes: under-budget, mid-budget, over-budget. For each, predict which tier they pick and why. **Constraints:** - Show willingness-to-pay reasoning, not cost-plus math - Price points should not be round (avoid $99) unless deliberately positioning premium - Annual pricing is 16-20% off monthly (the magic range) - For each tier: what's IN, what's OUT, what's the gate to the next tier **Output format:** Markdown · 5 sections · tier comparison table · willingness-to-pay rationale per tier.
- Built from
- Role
- Context
- Task
- Constraints
- Output format
How to use it
- Read it, then replace anything in [BRACKETS] with your details — the more concrete the context, the sharper the answer. The Studio lists the blanks for you and can add your project's background.
- Copy it (or download the .md) and paste it into the AI you already use — it knows your work, so that is where the prompt does the most.
- Not sure what it produces? Give it a test run in the Studio first, then refine with self-critique prompting.
Techniques in this prompt
Role-Based
Assigns the model an expert persona so it adopts the right vocabulary, depth, and standards for the task.
Learn this techniqueChain-of-Thought
Asks the model to reason step by step before answering — ideal for multi-step, logical, or analytical tasks.
Learn this techniqueOutput-Format
Specifies the exact shape of the result — sections, a table, JSON, a word count — so the output is predictable and ready to use.
Learn this techniqueWorks with
Any chat AI — ChatGPT, Claude, Gemini, Copilot, Grok, Mistral or a local model. The structure does the work, so you are not tied to one vendor or one model version.
New to structured prompts? Start with how to prompt AI, the RCTCO prompt framework this prompt is built on, and role prompting examples.