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Offers

Corey HainesCommunityCreated by Corey Haines

  • Skill
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  • Business and productivity
  • MIT
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From the author

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.
— the description by Corey Haines

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

  1. Download the skill as a ZIP:

    https://mp-staging.autogineer.com/agent-skills/coreyhaines31/offers/download
  2. Unzip 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 & Sacrifice

You move the four levers like this:

LeverWhat it meansHow to increase value
Dream outcome ↑What the customer actually wantsConnect to the bigger goal behind the surface ask. Specify and name it.
Perceived likelihood ↑Do they believe they'll get itProof (case studies, named customers, data), guarantees, methodology specificity
Time delay ↓How long until resultFaster onboarding, faster first win, faster end-to-end timeline
Effort & sacrifice ↓What it costs them in time/work/risk besides moneyDone-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.

#ComponentQuestion it answers
1Core deliverableWhat do they get?
2Bonus stackWhat else do they get that makes the core feel undervalued?
3GuaranteeWhat happens if it doesn't work?
4Scarcity / urgencyWhy now, not later?
5NameWhat is this thing called?
6Price + payment structureWhat 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

ReferenceWhen to read
value-equation.mdDiagnosing which lever is broken on a stuck offer
offer-anatomy.mdBuilding a complete offer from scratch
guarantee-design.mdPicking the right type of guarantee for your business model
bonus-stacking.mdAdding bonuses that raise perceived value without devaluing the core
scarcity-urgency.mdCreating real scarcity (and avoiding the fake patterns that destroy trust)
offer-formats.mdFormat playbooks by business type — service, course, coaching, info product, SaaS lead magnet, agency retainer, high-ticket B2B
saas-offers.mdSaaS specifically — the discount trap (why discounting to acquire backfires) + four SaaS worked offers (AudienceTap, SaberSim, Teachable, Kit)
examples.mdAnonymized 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":

  1. Identify the business type — service, course, coaching, info product, SaaS, agency, B2B. The right playbook is type-specific.

  2. 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.

  3. Run the value equation — score each of the four levers 1–10. The lowest is the binding constraint.

  4. Audit the anatomy — which of the six components is missing or weak?

  5. Pick one lever to fix this iteration — don't rebuild everything. The biggest lever is usually the one currently scoring lowest.

  6. Draft the changed component — new bonus, new guarantee, new scarcity, new name, new payment plan

  7. 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.


  • 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

references/value-equation.md

The Value Equation

The single most useful frame for offer design. Originated in Alex Hormozi's $100M Offers; the underlying idea (multiply benefits, divide costs) is much older — direct-response copywriters have been doing it for a century.

The formula

              Dream Outcome  ×  Perceived Likelihood of Achievement
  Value  =  ─────────────────────────────────────────────────────────
              Time Delay     ×   Effort & Sacrifice

The customer compares the Value score to the Price. If Value > Price, they buy. If not, they don't, no matter how good the copy is.

Price is the comparison, not the value. Most "lower the price" requests are actually "raise the numerator or lower the denominator" requests.


Lever 1: Dream Outcome (numerator)

What the customer actually wants — usually one or two levels above the surface ask.

Surface ask → dream outcome
Surface askDream outcome
"I want a website""I want more qualified leads I can close"
"I want to learn copywriting""I want to write copy clients pay me $5K+ per project for"
"I want a meal plan""I want to feel confident in a swimsuit on a beach in 12 weeks"
"I want fitness coaching""I want my back pain gone so I can pick up my kids without thinking about it"
"I want a Notion template""I want to feel in control of my work for the first time in years"
"I want to lower CAC""I want a marketing engine I can step away from for two weeks without things breaking"
How to increase
  • Name it specifically. "Feel confident in a swimsuit" beats "lose weight." The specific name is the offer.

  • Connect to the bigger goal. The dream outcome behind the surface ask is almost always emotional or identity-based.

  • Show the future state in concrete sensory terms. What does the morning of day one after they have it actually look like?

Common mistake

Pitching the surface ask. ("Get a website" instead of "get a website that brings you 5 qualified leads a week.") The bigger the buyer's pain, the more important this is — they're not buying a deliverable, they're buying a future.


Lever 2: Perceived Likelihood of Achievement (numerator)

Do they actually believe they'll get the dream outcome? This is the single most underweighted lever — most offers are perfectly fine on the dream outcome side but the buyer just doesn't think it'll work for them.

How to increase
  • Proof — case studies with names, numbers, before/after metrics, photos. Specific > glossy.

  • Methodology specificity — name your process. "The 5-step VAULT framework" beats "our proprietary system." Even if the substance is the same, naming it raises perceived likelihood.

  • Guarantees — risk reversal directly raises perceived likelihood (more in guarantee-design.md).

  • Reduce sample-of-one objection — show people like them who got results. "Other people get results but I'm different" is the universal objection.

  • Pre-empt the failure path — explicitly address what could go wrong and how you handle it. Builds trust faster than hiding the risk.

Common mistake

Stacking more features ("we also include X, Y, Z") instead of stacking more proof. Features address dream outcome. Proof addresses likelihood. Most stuck offers need proof, not features.


Lever 3: Time Delay (denominator)

How long from purchase to result. The denominator is doing a lot of work here — slow results don't just feel slow, they erode perceived likelihood (the longer it takes, the less the buyer believes it'll work).

How to decrease
  • Faster first win — find the smallest possible early result and engineer it into the first 7 days

  • Onboarding velocity — replace a 60-minute kickoff with a 10-minute async intake + Loom send

  • Front-load the assets — give the templates / swipe files / decks on day 1, not "throughout the program"

  • Faster end-to-end timeline — "in 8 weeks" beats "in 6 months." If you can credibly compress, do.

  • Quick-start path — explicit "first thing to do today" so they don't lose momentum

Common mistake

Promising a faster timeline than you can deliver. The first time you miss it, perceived likelihood for every future buyer drops permanently as the failure story spreads.


Lever 4: Effort & Sacrifice (denominator)

What the buyer pays besides money — time, learning curve, decisions, willpower, social risk, opportunity cost.

How to decrease
  • Done-for-you over do-it-yourself — DFY tiers move the effort to you. Charge accordingly.

  • Fewer decisions — every decision the buyer makes is friction. Bundle, default, recommend.

  • Lower learning curve — pre-built templates, examples, defaults. "We did the thinking, you do the executing."

  • Removed risk — emotional risk (am I dumb if this doesn't work?), social risk (what will my team think?), opportunity cost (what am I not doing while I do this?). Address all three explicitly.

  • Async over live — for many buyers (founders, executives), removing synchronous commitments is huge value

  • Less willpower required — automation, accountability, environmental design

Common mistake

Overestimating how much your buyer enjoys the work. They want the outcome, not the process. (Exception: identity-buyers — fitness, learning, mastery. For those, the process is part of the dream outcome. Read your buyer.)


Diagnostic: scoring the levers

When an offer is stuck, score each lever 1–10 honestly. The lowest is the binding constraint.

Quick scoring prompts
  • Dream outcome (1–10): Can the buyer picture, in concrete sensory terms, the day after this works? Is the outcome named specifically enough that they can repeat it back to a friend?

  • Perceived likelihood (1–10): Do they have at least three named, comparable proof points? Is the methodology specific enough to repeat? Have you addressed the "but my situation is different" objection?

  • Time delay (1–10): What's the first concrete win, and how soon do they get it? What's the end-to-end timeline? Are there any "delay surfaces" (onboarding lag, asset drip, week-1 friction)?

  • Effort & sacrifice (1–10): How much work does the buyer do? How many decisions? How much learning curve? How much synchronous time? How much emotional/social/opportunity-cost risk?

Worked example: a stuck $3K copywriting course

Initial scoring:

  • Dream outcome: 6 (become a better copywriter — too vague)

  • Perceived likelihood: 4 (one testimonial, no methodology name)

  • Time delay: 5 (6-month course, no first-win mechanic)

  • Effort & sacrifice: 4 (lots of homework, live calls, weekly assignments)

Lowest: effort & sacrifice and perceived likelihood are tied. Pick one (perceived likelihood — easier to move and unblocks more downstream work):

  • Name the methodology: "The VAULT framework — 5 angles every winning sales page uses"

  • Add 8 named-customer case studies with before/after copy + revenue numbers

  • Add an "even if you've never written before" cohort with 3 named graduates

After: perceived likelihood goes 4 → 8. Course converts at ~3x baseline. Two months later, attack effort & sacrifice (replace weekly live calls with async + 1 live Q&A).


Key idea to internalize

The price-vs-value comparison happens in the buyer's head, not yours. You only know it's working when the buyer can articulate the dream outcome back to you in their own words, and when they don't need to ask "but does this actually work?"

If they're asking either of those questions, you have a value equation problem, not a copy problem.

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)
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