Comparison
Claude vs ChatGPT for cold email
Short version: the model is not the variable. Both write the same recognisable cold email out of the box, and what moves the reply rate is what you hand them before they start.
What both do by default
Ask either one cold for a cold email and you get a draft with the same three habits:
- Around 200 words, where 50–125 is the range that gets read in a preview pane.
- An opening that describes your business. The arc is backwards — it has to name the reader's problem first, in the reader's words, before it says what you do about it.
- A CTA asking for 15 minutes, usually with a calendar link. A meeting is a request to spend a scarce resource on a stranger; a question they can answer in five words is not.
Neither model is being careless. Both learned cold email from the open internet, which is overwhelmingly made of bad cold email and advice about sending more of it. The default output is an accurate average of the training material, and the average is poor.
Where they actually differ
Having run the same briefs through both, the differences worth naming are small and none of them is "writes better copy":
| Claude | ChatGPT | |
|---|---|---|
| Holding a constraint | Keeps a word ceiling and a no-link rule across a whole sequence more reliably | Drifts back toward a link and a meeting ask by the third touch |
| Tone out of the box | Flatter, less salesy — closer to sendable | Warmer and more enthusiastic, which reads as marketing |
| Carrying a method | Skills load automatically when the task matches | Knowledge files in a Custom GPT or Project; must be set up once |
| Portability of your method | A folder of markdown you own and can move | Configuration inside one vendor account |
We distribute a Claude skill, so treat the first two rows with appropriate suspicion — they are an impression from our own use, not a measurement, and anybody's ranking of two models on tone is mostly a ranking of their own taste. The last two rows are structural and would hold whoever wrote them.
The comparison that actually matters
Not Claude against ChatGPT. Either model with a method, against either model without one. That difference is large and visible in a single answer.
Ask any model "should the CTA have a link in it?" cold and it will say yes, make it easy for them. Ask it with an outreach method loaded and you get no, with the reason: a real campaign measured 31% opens, 15% clicks and a 0.3% reply rate on a CTA that offered a link alongside a question. The link was the easier option so it won every time, and the replies — the only outcome anyone could act on — never arrived. A link is not a second option, it is a replacement for the first.
No amount of model preference gets you that answer. It is not a reasoning failure, it is a missing fact, and the only fix is supplying it.
So what to actually do
- Use whichever you already pay for. Switching models to improve cold email is optimising the wrong term.
- Keep your method in a plain file, not in a vendor's configuration. Markdown works as a Claude skill, a ChatGPT knowledge file, a Cursor rules file and a Gemini Gem, and you can read and edit it.
- Give it real constraints. Word ceiling, one ask, no link, nothing invented. Six prompts that do this.
Our method is free to download in both formats — .zip packaged as a Claude skill, .md for everything else. No email address, and you can change it and pass it on. It also runs the funnel arithmetic and tells most readers to do their outreach themselves, which is the only reason the cases where it says otherwise mean anything.
Questions
Which AI is best for writing cold emails?
For the writing itself the difference between current frontier models is small enough that it is not the thing to optimise. What changes the output far more is whether the model has a method to work from. A model with a good outreach method beats a better model without one, every time, and the gap is not close.
Does ChatGPT or Claude write better cold emails by default?
By default both write a recognisable cold email: too long, opening with a description of your own business, and closing by asking for a 15-minute call. Those are the three habits that cost the most replies, and both models have them because both learned from the same internet full of bad cold email.
Can I use the same material in both?
Yes, and that is the argument for keeping your method in a plain file rather than inside a configured assistant. The Outreach Skill ships as a .zip packaged for Claude and a .md that works as a ChatGPT knowledge file, a Cursor rules file or a Gemini Gem. Same content, so you are not re-writing it when you change tools.
What running this yourself actually takes
The method is the part people expect to be hard, and it is the part you now have for nothing. The work is everything around it — and almost all of it is a fixed cost you pay whether you send 200 emails a month or 2,000.
| What | To stand it up | Then, forever |
|---|---|---|
| Sending domains | Buy a separate domain, never the one carrying your real mail | Replace any that burn |
| Authentication | SPF, DKIM and DMARC, correct on every sending domain | Re-check after any DNS change |
| Inbox warm-up | Three to four weeks of ramping before a single real send | Re-warm anything that sat idle |
| Lists | Source the companies, find the people, verify the addresses | Rebuilt continuously — lists decay about 2% a month |
| Suppression | One list that holds across email, SMS and calling | Every opt-out, every channel, immediately |
| Placement monitoring | Seed accounts, so you find out before the replies stop | Weekly, and after every copy change |
| Calling or SMS | A2P 10DLC brand and campaign registration, numbers, a dialler | DNC scrubbing, calling windows, spam-flag rotation |
| Writing and sending | The method — which you now have in full | 20–40 hours a month at any real volume |
Below a few thousand sends a month that overhead is the job. And the failure mode is almost never a bad email — it is three good weeks followed by five silent ones, because sequences only produce anything when they actually run, and outbound is the task that slips first when a busy week arrives.
Run it yourself when you have 5–10 hours a week that are genuinely free every week, you are willing to spend the first month warming a domain before a single real send, and somebody will still be triaging replies in month four when it has stopped being novel. Plenty of people meet that. It is completely learnable and nothing is held back.
Hand it off when those hours are worth more spent elsewhere. For most owners of a working service business they are: 20–40 hours a month is $1,500–3,000 of your own time, and the same hours put into delivery or sales calls usually return more than they cost.
Or we run the whole thing
The Outreach Platform sources the leads in your niche, writes and sends the email, SMS, voice and social outreach, owns the deliverability, and forwards replies straight to your inbox. There is no dashboard you have to operate — and because it exposes an MCP server, the same assistant you just installed the skill into can run the account from the conversation you are already in.
| Plan | What runs | Month |
|---|---|---|
| Free | 10 leads and a written pitch for one — nothing sent | $0 |
| Sourcing, writing, sending, deliverability | $29 | |
| + Calling | Adds voice, registration and DNC handling | $59 |
| Full volume | Every channel at full send | $99 |
Set $29 against $1,500–3,000 of your own time and the comparison is the whole argument — run it with your own hourly rate and see where it lands. No contract. And the free tier means you can see the output on your own market before deciding anything.
No credit card for the free tier · Nothing sends until you say so