定价是大多数团队做一次就忘的高杠杆决策。下面 15 个 Prompt 强迫你写出每个价格背后的假设——谁来付、他在和谁比、涨价时谁会降级。如果想要围绕这些模板的完整工作流——喂什么、人工验证什么、一周内怎么测——可以看我们的上线前用 AI 生成定价假设的工作流。覆盖：免费 vs Freemium vs 试用、2 / 3 / 定制阶梯、按用量 vs 按席位、锚定与诱饵、packaging vs pricing、最被跳过的”为什么有这一档”练习。
适合哪些场景
在为 v1 定价的创始人、主导定价改版的 PM、测试 packaging 的增长 lead、准备给老客户涨价的运营。
什么时候不建议这样写 Prompt
一次性消费购买（单 SKU 电商）不要用——需要不同的诱饵 / 锚定框架。付费客户少于 50 也不要用——先和他们谈。
Prompt 结构公式
定价假设 Prompt 一定带这六个要素：
- 角色：让 AI 扮演谁（资深 PM / 独立创始人 / 产品设计师 / 独立开发者 / 增长负责人）。
- 上下文：阶段（想法 / MVP / 增长 / 规模化）、团队规模、流量或 ARR、平台（web / iOS / Android）、受众、限制。
- 目标：一个具体交付物——一段 PRD、一组用户故事、一个实验设计、一篇上线公告。
- 限制：时间线（本 sprint / 本季度）、要砍的范围、不能动的东西（现有流程、计费、合规）。
- 输出格式：表格、清单、可贴 ticket 的 JSON、或带标签的段落，能直接粘到 Linear / Notion / Jira。
- 示例 / 信号：1-2 份你欣赏的参考或竞品、加 1 个想避开的反例。
这套 Prompt 适合用在哪
- 新产品的初始定价
- 定价页改写
- 免费 / Freemium / 试用决策
- 阶梯重构（2 → 3 → 定制）
- 涨价前的 pre-mortem
15 个可直接复制的 Prompt 模板
1. 免费 / Freemium / 试用决策器
第一道决策。错了之后的所有定价都在逆水行舟。
You are a SaaS pricing strategist. For {product}, recommend free / freemium / 14-day trial / 30-day trial / reverse trial / paid only. Output: recommendation, the 3 reasons it fits, the 1 risk, and what data would change the answer.
Context: {product, segment, sales motion, willingness-to-pay signal}可替换变量： product, segment, sales motion, WTP 信号
优化建议： 太泛时追加：“Justify by naming a comparable product (named) and what they tried — what worked, what failed.”
2. 三阶梯结构搭建
Design a 3-tier pricing structure for {product}: Starter, Pro, Business. For each: target persona, price point, top 5 features, what is excluded, the upgrade trigger from tier below. End with one observation about which tier you expect to over-sell and which to under-sell.
Context: {paste}3. 两阶梯极简备选
Argue the case for cutting our pricing to 2 tiers instead of {current N}. What would each tier include, what would be killed, what would move to add-ons. Predict the revenue impact in 1 quarter. End with the strongest objection to going simpler.4. 按用量 vs 按席位
For {product}, recommend usage-based vs seat-based vs hybrid pricing. For each option: ideal customer profile, expected ACV impact, churn-risk profile, billing complexity. Pick one and explain when to revisit.5. 锚定 + 诱饵结构
Design a 3-tier pricing page with a deliberate anchor (high-price tier) and decoy (mid-tier that makes the next tier look obvious). For each tier: price, features, intended psychological role (anchor / decoy / target). Show how a buyer scans the page in 8 seconds.6. 付费意愿访谈脚本
Generate a 30-minute customer interview script to surface willingness-to-pay for {product}. Use Van Westendorp 4-question framing plus 4 open-ended follow-ups about anchors. End with a checklist of red flags (interviewer-leading questions) to avoid.7. 涨价 pre-mortem
We plan to raise prices by {X%} on {date}. Run a pre-mortem: 5 ways this could fail (mass churn, NPS drop, negative press, sales-team revolt, competitor weaponization), and the smallest mitigation for each. End with a kill-switch trigger ("if X happens, roll back").8. 历史用户保留政策
Design a grandfathering policy for an upcoming price increase. Options: full grandfather, 12-month grace, partial discount, no grandfather. For each: revenue impact, churn risk, brand-trust impact. Recommend one with reasoning.9. 阶梯解释重写
Below is our current pricing page. For each tier, write a 1-line "this tier exists for X" statement. If you cannot, that tier is redundant. Output: tier, current copy, proposed 1-liner, kill / keep / merge.
{paste pricing page}10. Packaging vs Pricing 审计
Audit our pricing problem: is it packaging (wrong bundle) or pricing (wrong number)? Score 1-5 on each of 6 dimensions: feature-tier fit, upgrade path obviousness, decoy effectiveness, price-feature ratio, competitor parity, willingness-to-pay alignment. Recommend the smallest fix.11. 按席位 vs 一口价权衡
For a {team-size} customer, calculate effective cost under per-seat vs flat-rate vs hybrid. Show the breakeven seat count and where each model creates buyer-friction. Recommend which to lead with.12. Add-on vs 核心功能决策
Below are 8 features we are considering. For each, decide: include in core, make a paid add-on, or push to a higher tier. Decision criteria: usage frequency, dev cost, perceived value, willingness-to-pay signal.
Features: {paste}13. 竞品定价逆向工程
For each competitor in {list}, infer the pricing logic from their public page: who they expect to buy each tier, what they signal with anchor pricing, where they hide cost. End with one move we could make that none of them are doing.14. 价格测试设计
Design an A/B price test for {product}: variants ({control vs +20% vs +50%}), sample size, success metric, guardrails (CAC, churn, support load), duration, kill criteria. Mark which decisions cannot be A/B-tested ethically and must be sequential instead.15. 由结构反推定价页文案
Given this finalized tier structure, write the pricing-page copy. For each tier: 1-line value statement (less than 12 words), 4 feature bullets, 1 social proof line. Then write the FAQ block (5 Qs covering: refunds, billing cadence, upgrade, downgrade, custom plans).
Structure: {paste}容易踩的坑
- 凭感觉定价、不写假设——没写出来的东西没法测。
- 抄竞品价格但没抄他的成本结构和销售路径。
- 3 阶梯其实 2 就够；4 阶梯超过多数买家上限。
- 免费档没有升级触发器——纯烧钱还混淆定位。
- 不带保留政策直接涨价——可预见的流失峰。
- 定价页只堆功能清单——买家扫的是价值，不是数量。
- 不做付费意愿访谈，纯靠 AI 猜。
优化技巧
- 每档先写”这一档为 X 而存在”——写不出来就是冗余。
- 每个定价假设都配一个能证伪的指标（如高档流失超 8%）。
- 锚定档要看上去合理；假锚一眼穿。
- 按 cohort 和日期测，而不是全量 A/B——定价测试敏感且涉及伦理。
- 改价前先和 10 个客户谈一遍；AI 替不了。
- 犹豫时优先涨价，少而精的客户更好。
- 定价模型一年刷新一次；产品变化总比定价页快。
FAQ
- 一定要先用 Freemium 吗？: 不。Freemium 适合高频 / 网络效应 / 内容型产品。高接触 B2B 通常 14 天试用更好。
- 几档合适？: 多数 SaaS 落在 3 + 企业定制。低于 3 决策被压；高于 3 困惑买家。
- 什么时候可以涨价？: 新客 NPS 健康、月流失低于 3%、近 3 个客户说”愿意付更多”时。
- 价格要公开吗？: 自助型必须公开。企业可以藏定制档，但 Starter 价必须显示——全藏伤信任。
- 涨价怎么避免老客户怒怼？: 提前 60 天通知，提供 12 个月老价锁定，重要账户个人邮件先沟通再公告。