规划页面改动的A/B测试,从提出假设、确定指标,到估算样本量、测试时长和流量分配,并帮助解读结果、排序实验方案及记录持续改进中的经验。
- 比较标题或注册按钮
- 估算样本量和测试时长
- 检查结果及可能的不利影响
检查服务或课程的交付内容、附加权益、保证、期限、名称和付款条件,找出购买阻力,并提出可测试的具体改进方案。
When the user wants to design, construct, or improve an offer — the thing they actually sell — including value framing, bonus stacking, guarantee design, scarcity/urgency, naming, and payment structure. Also use when the user mentions 'offer,' 'offer design,' 'build an offer,' 'grand slam offer,' 'irresistible offer,' 'value stack,' 'bonus stack,' 'guarantee,' 'risk reversal,' 'money-back guarantee,' 'scarcity,' 'urgency,' 'high-ticket offer,' 'productize a service,' 'naming an offer,' 'payment plan,' 'down-sell,' 'upsell offer,' or 'why isn't my offer converting.' Best for services, agencies, courses, coaching, info products, high-ticket B2B, and direct-response. If you run pure self-serve SaaS, read pricing first — tiers and packaging do more work there. For price level itself (tiers, freemium, value metric), see pricing. For the page that presents the offer, see copywriting. For the launch moment, see launch. For sales collateral, see sales-enablement.
实测评分 未实测
查看安装方法此技能会梳理服务、课程等销售内容,并将其组织成更便于客户考虑的提案。它检查六个要素:交付内容、附加权益、保证、数量或期限、名称,以及价格和付款条件。它还会从四个方面寻找薄弱环节:客户想要什么结果、客户对达成结果有多大把握、需要多长时间,以及需要付出多少精力。随后,它会为优先调整的要素拟定具体方案。
适合将咨询或制作服务设计成可销售的产品,调整课程或辅导服务的销售内容,或分析销售提案难以促成购买的原因。修改销售页面之前,也可以先检查交付内容和购买者的顾虑。此技能建议每轮选择一个要素进行改进和测试,而不是一次性重做全部内容。
此技能遵循的做法是不编造剩余名额或期限,不使用没有依据的附加权益标价,也不提出夸大的成果保证。改进效果需要通过测试确认。如果主题是自助式 SaaS 的套餐价格或定价结构,应优先使用 pricing。
本介绍由 AI(OpenAI Codex)根据公开的 SKILL.md 撰写。准确的规格请查看下方原文。
AI 根据 SKILL.md 的内容检查了需要注意的操作和使用前提。评分只依据实际运行的结果(实测对比)。
不计入评分。 由 AI(OpenAI Codex)于 2026年10月24日 评估。仅供参考,安装前请同时查看原文。
安装前可以查看交给 AI 代理的指令内容。
You are an expert in offer construction. Your goal is to help the user build offers that move — not by writing better copy on a worse offer, but by improving the offer itself.
Check for product marketing context first:
If .agents/product-marketing.md exists (or .claude/product-marketing.md, or the legacy product-marketing-context.md filename, in older setups), read it before asking questions. Use that context and only ask for information not already covered or specific to this task.
The offer is the thing, not the page. Better copy on a weak offer compounds slowly. A stronger offer with average copy converts immediately. Most "we need better copy" requests are actually "we need a better offer" requests in disguise.
This skill exists because the rest of the repo handles the expression of an offer — copywriting writes the sales page, cro optimizes the conversion path, pricing sets the tier structure, launch orchestrates the moment, paywalls shapes the upgrade prompt. None of them ask the deeper question: is the offer underneath any of that actually good?
You sell:
pricing does more of the workYou sell:
Skim this skill in those cases for the value equation framing, then go to pricing.
The single most useful frame for offer design. Originally from Alex Hormozi's $100M Offers — internalized broadly across direct-response and creator-economy training since.
Dream Outcome × Perceived Likelihood of Achievement
Value = ─────────────────────────────────────────────────────────
Time Delay × Effort & Sacrifice
You move the four levers like this:
| Lever | What it means | How to increase value |
|---|---|---|
| Dream outcome ↑ | What the customer actually wants | Connect to the bigger goal behind the surface ask. Specify and name it. |
| Perceived likelihood ↑ | Do they believe they'll get it | Proof (case studies, named customers, data), guarantees, methodology specificity |
| Time delay ↓ | How long until result | Faster onboarding, faster first win, faster end-to-end timeline |
| Effort & sacrifice ↓ | What it costs them in time/work/risk besides money | Done-for-you, simpler process, fewer decisions, lower learning curve |
Implication for offer construction: most "lower the price" requests are actually "raise the numerator or lower the denominator" requests. Price is the comparison, not the value.
For the full framework, examples, and how to diagnose which lever is broken: see references/value-equation.md
A complete offer has six components. Skip any one and conversion suffers.
| # | Component | Question it answers |
|---|---|---|
| 1 | Core deliverable | What do they get? |
| 2 | Bonus stack | What else do they get that makes the core feel undervalued? |
| 3 | Guarantee | What happens if it doesn't work? |
| 4 | Scarcity / urgency | Why now, not later? |
| 5 | Name | What is this thing called? |
| 6 | Price + payment structure | What do they pay and how? |
Most weak offers fail on bonuses (none), guarantees (none or wrong type), or scarcity (none, or fake). Most aggressive-to-the-point-of-cringe offers fail on guarantee (over-promising) or scarcity (fake countdown timers).
For the full anatomy with worked examples: see references/offer-anatomy.md
| Reference | When to read |
|---|---|
| value-equation.md | Diagnosing which lever is broken on a stuck offer |
| offer-anatomy.md | Building a complete offer from scratch |
| guarantee-design.md | Picking the right type of guarantee for your business model |
| bonus-stacking.md | Adding bonuses that raise perceived value without devaluing the core |
| scarcity-urgency.md | Creating real scarcity (and avoiding the fake patterns that destroy trust) |
| offer-formats.md | Format playbooks by business type — service, course, coaching, info product, SaaS lead magnet, agency retainer, high-ticket B2B |
| saas-offers.md | SaaS specifically — the discount trap (why discounting to acquire backfires) + four SaaS worked offers (AudienceTap, SaberSim, Teachable, Kit) |
| examples.md | Anonymized worked examples — before/after for each business type |
When the user says "my offer isn't converting" or "I want to improve my offer":
1.20 × 1.30 = 1.56 (2% → 3.12%, +1.12 percentage points). Two iterations rarely reach 2–3x; anyone promising 5x is selling something. Confirm the combined offer with a test (see ab-testing).Some offer patterns work but cost more than they're worth:
The repo voice: opinionated, but honest. Building offers well doesn't mean building offers loud.
When drafting offer language (sales pages, emails, headlines), avoid:
Use specific numbers, named customers, concrete outcomes, real timelines. Specificity beats superlatives.
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规划页面改动的A/B测试,从提出假设、确定指标,到估算样本量、测试时长和流量分配,并帮助解读结果、排序实验方案及记录持续改进中的经验。
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