Channel Offer
by
Offer design for ecommerce teams: work out what each channel's audience needs to convert and what it costs, then map the right offer to each one.
Most stores run one offer everywhere, because one offer is easier to manage and because nobody has priced the alternative. The result is that the email list, which would have bought anyway, gets the same discount as a cold prospecting audience that needs a reason to try you. The first group costs you margin for nothing and the second may need more than you are giving. This skill works out what each channel's audience actually needs to convert and what it costs, then maps the right offer to each one.
What It Does
- Estimates what each channel's audience needs to convert, from its own history.
- Prices the margin each candidate offer gives up in that channel.
- Separates an audience that needs a discount from one that needs a reason.
- Checks that the offers cannot be discovered and arbitraged across channels.
- Sizes the non-discount offers that work where price is not the barrier.
- Generates the offer map across channels, with the cost of each.
Use Cases
- Stop giving your email list a discount it did not need.
- Give a cold audience enough of a reason to try you.
- Replace a discount with a non-price offer where that works better.
- Check that a channel-specific code cannot leak to everyone.
Example Session
We run 15% off everywhere. What should each channel actually get?
Two channels need nothing. One needs more than 15%.
- Channel | Current | Needs | Recommended offer | Margin cost change
- Email, engaged | 15% off | Nothing | Early access, no discount | -$28,000
- Organic and direct | 15% off | Nothing | Free shipping over $85 | -$19,000
- Paid social, cold | 15% off | Risk reversal | 15% plus free returns | +$4,000
- Retargeting, cart | 15% off | Urgency | 10% for 48 hours | -$7,000
Your engaged email list converts at the same rate with early access as with a discount, because the barrier there is timing rather than price. That alone stops $28,000 of margin leaving. The cold audience is the opposite: price is not what is stopping them, risk is, and adding free returns for $4,000 converts better than deepening the discount would.
Why This Beats Prompting It Yourself
One Offer Everywhere vs What Each Audience Needs: The Hidden Risk
A generic prompt optimizes the offer, singular, because the question is usually asked that way. A single offer has to be generous enough for the hardest audience and is therefore wasted on the easiest. The email list taking 15% off things it was going to buy is the largest silent margin leak in most stores.
When You Still Need The Arbitrage Checked
Channel-specific offers work until someone posts the code. This skill checks that each offer is enforceable, through audience gating or a mechanism that cannot be copied, before recommending it. An offer map that leaks becomes the deepest discount applied to everyone, which is worse than the single offer it replaced.
Known Limitations
What an audience needs is estimated from your own offer history per channel, so a channel that has only ever seen one offer returns a wider estimate the output labels. Non-price offers like early access depend on having something worth early access to. It generates the offer map and does not configure discounts or audiences in any platform.
Install It
- Download the ZIP.
It is free and there is no account to create. - Unzip it into your agent's skills folder.
Claude Code reads ~/.claude/skills/, which is hidden by default: the command in the folder block opens it. Other agents scan their own directory, so drop the same folder there instead. - Ask your agent to use it.
Restart the agent if it was already running, then it picks the skill up with no config.
skills folder
Copy
~/.claude/skills/channel-offer/
SKILL.md
references/offer-library.md
maps/
# one map per period, with the cost per channel
# macOS: create the folder and open it in Finder
mkdir -p ~/.claude/skills && open ~/.claude/skills
# Windows: paste in the Explorer address bar
%USERPROFILE%\.claude\skills\Frequently asked questions
How is this different from optimizing my discount?
Optimizing a discount assumes price is the barrier in every channel, which it is not. This asks what is actually stopping each audience, which is timing for your email list and risk for cold traffic, and matches the offer to that. Two of four channels usually need no discount at all.
Which agents does the skill run in?
Any agent that supports the open SKILL.md format: Claude Code, Cursor, Codex CLI, GitHub Copilot, Gemini CLI, Manus, Grok and others load it unmodified. The format is portable, the location is not. Each agent scans its own skills directory, so you drop the same folder into whichever one yours uses. There is no config file to edit and no API key to provision.
What does it need connected to work?
Orders with channel attribution, your offer and promotion history by channel, and product margin. History of non-discount offers helps and is rarely available, so the skill is explicit about which recommendations rest on thinner evidence.
Will my email list really convert without a discount?
The engaged part usually will, on early access or a genuine first look, because they were going to buy and the discount only changed when. The skill sizes that group specifically rather than treating the whole list as one audience.
How do you stop channel offers leaking?
By gating on audience rather than on a code where the platform allows it, and by flagging any recommendation that relies on a shareable code. An offer map with one leakable code in it is a single deep discount waiting to happen.
What is included with the skill?
The skill itself, the offer library reference, the map format, and the enforceability checks. It is free and security scanned. We re-publish the ZIP when the library changes, so download it again if your maps start shifting.
One offer map, or one per platform's version of revenue.
Polar puts every channel on the same net revenue and CAC, so the offer you assign to each is comparable rather than platform-flattering.
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