Offers
Corey HainesCommunityCreated by Corey Haines
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- Business and productivity
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AutoGineer summary
Written by AutoGineer from the skill’s own files, not by the author
This skill provides a structured approach to offer design, emphasizing that conversion issues are often rooted in the offer itself rather than the copy. It utilizes the Value Equation—Dream Outcome, Perceived Likelihood, Time Delay, and Effort & Sacrifice—to diagnose and improve the core components of an offer. The framework guides users through auditing their current offer, identifying the weakest lever, and systematically adding components like bonuses, guarantees, and scarcity to increase perceived value and conversion rates.
What it does
- Diagnoses the binding constraints of an existing offer using the Value Equation.
- Provides a six-part anatomy for building complete, high-converting offers.
- Offers strategies for designing effective guarantees and risk-reversal mechanisms.
- Guides the creation of bonus stacks that address specific customer objections.
- Helps structure pricing and payment plans to maximize conversion.
- Identifies when to use offer-design tactics versus pricing or copywriting strategies.
When to use it
- When an existing offer is failing to convert despite having decent traffic.
- When you need to build a new offer for services, courses, coaching, or high-ticket B2B.
- When you want to increase the perceived value of your product without simply lowering the price.
- When you need to address specific customer objections through strategic bonus stacking.
- When you are transitioning from selling time to selling productized services or outcomes.
Advantages
- Focuses on the structural integrity of the offer rather than just surface-level copy.
- Provides a clear, actionable diagnostic loop to identify the biggest lever for improvement.
- Uses a proven, logic-based framework to increase value perception.
- Helps avoid common pitfalls like manipulative scarcity or over-promising guarantees.
- Standardizes the components of an offer to ensure nothing critical is missing.
Usage examples
- “My agency retainer isn't converting. How do I improve the offer?”
- The agent will guide you through identifying your business type, scoring your current offer against the Value Equation, and pinpointing which of the six offer components is missing or weak.
- “How can I add bonuses to my course without making it look like cheap padding?”
- The agent will help you design a bonus stack where each item specifically targets a known customer objection, such as lack of time or fear of getting stuck.
- “I want to offer a guarantee for my coaching program but I'm afraid of refunds.”
- The agent will help you design a conditional guarantee that provides risk reversal for the client while protecting your business model and reputation.
- “Why is my high-ticket B2B offer not getting any bites?”
- The agent will audit your offer's anatomy, likely focusing on whether your dream outcome is clearly defined and if your perceived likelihood of achievement is supported by sufficient proof.
Install
Download the skill as a ZIP:
https://autogineer.com/agent-skills/coreyhaines31/offers/downloadUnzip it into the cross-client skills folder of your project:
mkdir -p .agents/skills && unzip offers.zip -d .agents/skills
Documentation by Corey Haines
Offer Design
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.
Before Starting
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.
Core Philosophy
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?
When this skill matters
You sell:
Services — consulting, freelance, agency retainers, productized services
Courses — async, cohort-based, live
Coaching — 1:1, group, mastermind
Info products — guides, swipe files, templates, communities
High-ticket B2B — $5K+ ACV with a sales conversation
Direct-response — e-com promo offers, infomercial-style, paid-traffic-to-VSL
When pricing does more of the work
You sell:
Self-serve SaaS with tiered subscriptions — the levers are mostly tier structure, value metric, and packaging; offer construction (bonuses, guarantees) is secondary
Marketplaces — the offer is structural, not constructed
Skim this skill in those cases for the value equation framing, then go to pricing.
The Value Equation
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 & SacrificeYou 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
The Anatomy of a Complete Offer
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 Library
| 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 |
The Diagnostic Loop
When the user says "my offer isn't converting" or "I want to improve my offer":
Identify the business type — service, course, coaching, info product, SaaS, agency, B2B. The right playbook is type-specific.
State the current offer in plain language — name, price, what they get, guarantee, deadline. Write it down even if it lives in scattered places now.
Run the value equation — score each of the four levers 1–10. The lowest is the binding constraint.
Audit the anatomy — which of the six components is missing or weak?
Pick one lever to fix this iteration — don't rebuild everything. The biggest lever is usually the one currently scoring lowest.
Draft the changed component — new bonus, new guarantee, new scarcity, new name, new payment plan
Project the lift, honestly — plan on 10–40% relative lift from one component change. Multiply the lifts, don't add them: +20% then +30% =
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).
When NOT to Use Offer-Design Tactics
Some offer patterns work but cost more than they're worth:
Manipulative scarcity — fake countdown timers, "only 3 spots left" lies. Short-term lift, long-term trust collapse. Don't.
Over-promising guarantees — "double your revenue or refund + $1,000." Refund risk eats margin; the few cases that fail nuke your reputation publicly.
Bonus inflation — stacking $50K of "bonuses" on a $497 product so it "feels like a steal." Sophisticated buyers see this. Treat bonuses as additive, not exaggerated.
Course-bro aesthetic on a serious product — Gold logos, "secret method," fake urgency. Pattern-matches to scam. Wrong room.
Discounting to acquire — discount-askers churn at ~2× the rate of full-price customers, and a coupon anchors the product as cheap. Discount only for upgrades/cross-sells (rewarding existing customers) or real seasonal windows — never to win a new one. Raise value with an offer instead. See saas-offers.md.
The repo voice: opinionated, but honest. Building offers well doesn't mean building offers loud.
Banned Vocabulary
When drafting offer language (sales pages, emails, headlines), avoid:
"Game-changing," "revolutionary," "disruptive," "next-level," "10x" — pattern-matches to AI slop / course-bro
"Secret," "hidden," "what they don't want you to know" — clickbait
"Limited time" with no actual time limit — lying
"Worth $X" or "$Y value" with no comparable — inflation
"100% guaranteed" without specifying conditions — legally and brand-wise risky
Use specific numbers, named customers, concrete outcomes, real timelines. Specificity beats superlatives.
Related Skills
pricing — for price levels, tier structure, value metric, packaging, freemium
copywriting — for the page that presents the offer
cro — for optimizing the conversion path the offer travels through
launch — for the moment you ship the offer
paywalls — for in-app upgrade-prompt versions of an offer
sales-enablement — for the deck and one-pager that carry the offer into a sales conversation
emails — for the email sequence that warms up the offer
marketing-psychology — for the cognitive biases that make offers land or bounce
Files
- ATTRIBUTION.mdAdded by AutoGineer873 B
- LICENSELicence file added by AutoGineer1.0 KiB
- SKILL.md9.9 KiB
- evals/evals.json3.1 KiB
- references/bonus-stacking.md7.6 KiB
- references/examples.md10.0 KiB
- references/guarantee-design.md8.0 KiB
- references/offer-anatomy.md8.6 KiB
- references/offer-formats.md10.4 KiB
- references/saas-offers.md7.7 KiB
- references/scarcity-urgency.md6.9 KiB
- references/value-equation.md7.7 KiB
references/guarantee-design.md
Guarantee Design
A guarantee directly raises perceived likelihood of achievement (the buyer thinks: "they'll only offer this if they're confident") and lowers effort & sacrifice (less emotional risk). It's one of the highest-leverage levers in offer design.
The wrong guarantee hurts more than no guarantee. Pick the type that matches your business model.
The eight guarantee types
| Type | What it promises | When it works | When it backfires |
|---|---|---|---|
| 1. Unconditional money-back | "Refund anytime within X days, no questions" | Low-priced info, high-trust audience | High-priced/high-touch; refund risk eats margin |
| 2. Conditional money-back | "Refund if you complete X and still don't see Y" | Courses, programs requiring effort | Sophisticated buyers; harder to honor publicly |
| 3. Better-than-money-back | "If it doesn't work, full refund + $X" | Confident delivery, ample margin | If you fail; the few failures explode publicly |
| 4. Service-level / SLA | "If we don't deliver X by Y, your money back" | Productized services, agency work | Vague SLAs you can't measure |
| 5. Performance-based | "Pay only when X happens" (rev share, results-based) | Sophisticated B2B, high-confidence delivery | Long cycles, hard-to-attribute outcomes |
| 6. Anti-guarantee | "No refunds. Make sure you want it." | Premium audiences, mature buyers | Confused / first-time buyers; reads cold |
| 7. Outcome-or-extension | "If you don't get X by Y, we continue free" | Coaching, services with extendable time | Open-ended cost; choose with care |
| 8. Comparison guarantee | "Beat [competitor]'s result or refund" | When you can credibly compare | When you can't measure the competitor cleanly |
Picking the right one
Decision tree:
What's your buyer's biggest perceived risk?
"What if it doesn't work?" → money-back family (1, 2, 3)
"What if you don't deliver on time?" → SLA (4)
"What if I pay and get no results?" → performance-based (5) or outcome-or-extension (7)
"Is this real or scam?" → comparison or specificity-based (8)
What's your refund tolerance?
Can absorb refunds at scale → unconditional (1)
Need to qualify refunders → conditional (2)
Confident enough to add a bonus on top → better-than-money-back (3)
Can't afford refunds at all → anti-guarantee (6) or no guarantee + strong proof
What's your buyer sophistication?
Premium / mature buyers → anti-guarantee can work; "we don't do refunds" reads as confidence
First-time-in-category buyers → strong refund guarantee; they need permission to try
Sophisticated B2B → SLA or performance-based; they expect commercial terms
How measurable is the outcome?
Clean and measurable → performance-based, comparison, or outcome-or-extension
Fuzzy / subjective → money-back family with a conditional gate (you completed the work)
Examples by business type
Course / cohort
Strong: "Complete all six modules within 60 days, submit the final exercise, and if you haven't [specific outcome] we refund in full." Conditional on effort, clear on outcome.
Weak: "100% money-back guarantee." No conditions = refund magnet for buyers who never engaged.
Coaching / consulting
Strong: "After the first two sessions, if you don't think the engagement will deliver, we end it and refund the unused balance." Mid-engagement off-ramp builds trust.
Weak: "Satisfaction guaranteed." Means nothing.
Productized service / agency retainer
Strong: "First month is a paid pilot. At the end, if you don't see [specific milestone], you don't pay for month 2 and we end on good terms." Clear gate, clear out.
Weak: "We'll work until you're happy." Open-ended cost. Don't.
High-ticket info product (community, mastermind)
Strong (premium audience): "No refunds. The application process is rigorous because the value is real. If you're not sure, don't apply yet." Anti-guarantee works here.
Weak (premium audience): Generic 30-day refund. Reads cheap.
Low-ticket info product (template, swipe file)
Strong: "30-day no-questions refund." The transactional bar is "I bought it, looked at it, didn't want it." Unconditional fits.
Weak: No guarantee. The buyer's risk is too high for the price.
SaaS
Strong: Free trial or annual-prepay-with-money-back-in-first-30-days. Reduces friction without locking in unhappy users.
Weak: "Cancel anytime" alone — not a guarantee, just standard SaaS terms.
Direct response / paid traffic
Strong: Double-your-money-back or comparable risk inversion. Direct-response buyers expect risk-reversal-heavy offers.
Weak: Vanilla 30-day refund. Doesn't differentiate from every other ad on the platform.
Writing the guarantee
The guarantee text matters. Patterns that work:
Specific terms:
If, after completing the first 4 weeks of the program, you can't point to one specific business outcome you've achieved, email us and we'll refund 100%.
Confident tone:
We know this works. If it doesn't for you, we don't want your money.
Acknowledge the awkwardness:
Guarantees feel slimy. Here's ours anyway: if you do the work in modules 1–3 and don't see meaningful traction, we refund.
Patterns that don't work:
"100% satisfaction guaranteed!" — generic, low-trust
"Lifetime guarantee" — meaningless without conditions
Multiple stacked guarantees — sophistication-collapsing
Guarantees full of legalese — buyers skim and assume the worst
Common mistakes
Promising more than you can deliver
"Double your revenue or your money back + $1,000." If even 1 in 50 buyers fails and gets the bonus refund + writes a public review, the offer is permanently damaged.
Stress-test: what happens if 10% of buyers invoke the guarantee?
Conditional guarantees with too many conditions
"Refund if you watched all 24 modules, completed the 6 exercises, attended every live call, and posted in the community at least once per week."
Buyers read this as "they made it impossible to actually get a refund." Trust drops.
Two conditions max. Three only if they're closely related (e.g., "completed the course AND submitted the final project AND emailed us a question").
Hiding the guarantee in the fine print
If your guarantee is your strongest perceived-likelihood lever, put it on the sales page in 24pt text. Move it above the buy button.
Forgetting to test it
Re-read your guarantee text every six months. The wording that worked a year ago may now be undermined by something you've changed about your offer.
Treating guarantees as a substitute for proof
Strong proof + weak guarantee > strong guarantee + weak proof. Order matters. Build proof first, then layer on the guarantee.
The honest case for NO guarantee
Anti-guarantees ("no refunds, this is final") work when:
Buyer sophistication is high
Application or qualification process precedes the sale
Price is premium-to-luxury
Brand is established
Proof is overwhelming
What you're saying: "We don't need a guarantee because the work is real, the buyer has self-qualified, and we won't engage in transactional refund games."
The wrong audience reads this as cold or scammy. The right audience reads it as confidence. Know your buyer.
The diagnostic
When auditing an offer with no guarantee (or a weak one), ask:
What's the buyer's actual risk? Make it concrete. ("$2K and I might not get more clients.")
What guarantee structure reverses that specific risk? Match it to one of the eight types.
What's your honest refund tolerance? Calculate refund rate × refund cost; can you sustain it?
Does the guarantee match your audience sophistication? Premium buyers want anti-guarantee; first-time buyers want unconditional.
Most offers don't have the wrong guarantee — they have no guarantee at all. Adding any guarantee is almost always a lift. Adding the right one is the lever.
Requirements and compatibility
Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta
“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.
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Attribution and licence
- Created by
- Corey Haines
- Publisher
- Corey Haines (Community)
- Source
- coreyhaines31/marketingskills · skills/offers · commit 96798cf
- Licence
- MIT License (redistribution allowed)
- LICENSE (added by AutoGineer from LICENSE)
- ATTRIBUTION.md (written by AutoGineer)
- Synced
AutoGineer is not affiliated with or endorsed by Corey Haines or Corey Haines.
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