When you're writing a cold outreach email or replying to a trade inquiry, should you use ChatGPT or Claude? This isn't a contest of specs and benchmark scores. It looks at one specific job, B2B trade email, and covers how the two actually differ in use and how to choose between them.
The short answer
- Quick everyday inquiry replies and quotation emails: both can do the job and the difference is small, so pick whichever your team finds easier to use
- Longer formal correspondence that needs to quote a product manual or contract terms: Claude is usually the more reassuring choice for staying reliable on long documents
- You already use ChatGPT for customer service, copywriting and other work, and want everything to build up in one workspace: just use ChatGPT. There's no need to bring in another tool just for outreach emails and add to what your team has to learn
How they compare
Tone control
The biggest risk with a trade email is a tone that sounds too "AI": a pile of exclamation marks and overexcited adjectives right from the first line. With either model, asking explicitly in the prompt for "a professional, restrained tone, no exclamation marks" makes a clear difference. Without that extra instruction, Claude's default tone tends to be a little more reserved.
Quoting long documents
If an outreach email needs to draw on lengthy background material, such as a product spec sheet or an email history, Claude supports pasting or uploading longer content and keeps things consistent from start to finish, which makes the job less of a worry. ChatGPT can handle it too, but with very long documents it is more likely to miss details from one part or another.
Ecosystem and habit costs
If your company already uses ChatGPT for other things (product copy, say, or customer service scripts), your team already has muscle memory for how to write prompts there. Forcing a switch to Claude just for outreach emails adds extra steps and more to remember. In that situation, "good enough" matters more than "which one is stronger".
How we reached these conclusions
We ran the same outreach and inquiry scenarios, with the same prompts, once in each tool, then checked what we saw against the feature descriptions both companies publish on their official websites to arrive at the judgements above. This was not a large-scale comparison test. With your company's products and customers the results may be different, so the safest approach is to take one real email and try a round in each tool.
A simple way to choose
- First pin down which kind of email you write most often (everyday quotations or formal correspondence)
- Sign up for each tool's free tier, and have both generate a reply to the same real inquiry
- Pick the one whose output needed the fewest changes and sounds closest to your company's style, and make it the team default
Prompt templates for B2B outreach emails and inquiry replies
The three prompts below are split by email type and work as they are in both tools. When you run a comparison, paste the same prompt unchanged into both; only then does the comparison mean anything.
Everyday inquiry replies and quotation emails
You are an export sales rep at [COMPANY NAME]. Your tone is professional, concise and restrained: no exclamation marks, no overly enthusiastic adjectives.
Based on the customer inquiry below, draft a reply email in English.
Customer inquiry: [PASTE INQUIRY]
What we can confirm:
- Product model: [MODEL]
- Quotation: [PRICE, CURRENCY, TRADE TERMS, QUOTE VALIDITY]
- MOQ: [MOQ]
- Lead time: [LEAD TIME]
- Sample policy: [SAMPLE POLICY]
Requirements:
1. Only answer the questions the customer asked. Don't invent anything that isn't provided above; where something still needs confirming, write [TO CONFIRM];
2. Keep the body under 150 words, and make the first sentence respond directly to the customer's question;
3. End with one specific next step, such as confirming the quantity or arranging samples.Cold outreach emails
You are an export sales rep at [COMPANY NAME]. Write a cold outreach email in English to the prospective customer below.
Customer details: [THEIR COMPANY NAME, COUNTRY, MAIN PRODUCTS, AND WHERE YOU CAME ACROSS THEM]
Our product: [PRODUCT]
One point relevant to their business: [E.G. THEIR WEBSITE SELLS SIMILAR PRODUCTS, AND WE CAN OFFER A PARTICULAR CUSTOMISATION]
Facts we can mention: [FACTORY, CERTIFICATIONS, TRACK RECORD; ONLY THINGS THAT ARE TRUE]
Requirements:
1. Keep the body under 120 words. The first sentence should say why you're contacting them; don't open with stock phrases like "Hope this email finds you well";
2. Don't exaggerate, and don't commit to prices or lead times. End with just one question that's easy for them to answer;
3. Also give 3 alternative subject lines.Formal correspondence that needs to quote a spec sheet or earlier emails
Below are the product spec sheet and our previous emails with this customer. Using this material, draft a reply in English that answers the questions in the customer's latest email.
Requirements:
1. After each technical parameter, note in brackets which section of the spec sheet it comes from;
2. List separately any questions the material doesn't answer; don't guess;
3. Keep the tone formal and restrained, and address the customer the same way as in the earlier emails.
Spec sheet: [PASTE OR UPLOAD]
Previous emails: [PASTE IN DATE ORDER]
Customer's latest email: [PASTE]The three templates have one thing in common: you fill in the information that can be confirmed, and the AI only handles the wording. Once you let the AI "make a reasonable guess" at prices, MOQs and lead times, the cost of getting one wrong is far higher than the few extra minutes it takes to fill in the template. The third template asks for the source of each parameter so that whoever checks the email by hand can go straight to the right part of the spec sheet instead of rereading the whole thing.
Worked example: replying to an inquiry
Take a fictional hardware factory, "Hengtuo Hardware", as an example. A German retailer sends an inquiry: they want 5,000 stainless steel hooks, and ask about the unit price, the lead time, and whether custom packaging is possible. The draft below is an illustration written to explain the process, not an actual generated result.
Input: the sales rep uses the first template above and fills in the model, the price and terms from the quotation sheet, the MOQ and the lead time. Nobody has asked the factory about custom packaging yet, so it goes into the template as [TO CONFIRM].
AI draft (illustrative):
Dear Mr. Weber,
Thank you so much for your interest in our products! We are truly delighted to hear from you. Please find our best price below... Custom packaging is also available upon request.
What the sales rep changed:
- Cut the two opening pleasantries and replaced them with a direct response: Thank you for your inquiry about our stainless steel hooks. Our quotation is below.
- Cut "our best price", checked the price, currency, trade terms and validity line by line against the quotation sheet, and added the quotation number to the email so the customer can refer to it when replying
- The template clearly said [TO CONFIRM] for custom packaging, yet the draft said it was "available". This is the most dangerous line in the whole email. Changed it to say we'll confirm with the factory and reply separately, with a note of roughly when that reply will come
- Checked the spelling of the customer's name and the form of address against the signature on their email
- Read it through once more and removed the extra exclamation marks
Whether you use ChatGPT or Claude, you can't skip these checks. While you compare the two tools, jot down how many changes each draft needed and what they were. That's more reliable than judging by feel which one "writes better", and it maps directly onto the "fewest changes" step in the selection process above.
Common pitfalls when using AI for trade emails
- Letting the AI fill in prices and lead times: for any number you left blank in the template, the AI may well write one that looks plausible. For price, MOQ, lead time and payment terms, use only what you filled in yourself
- An overheated tone and stock openings: a string of exclamation marks and "we are delighted", and the customer can tell at a glance it's a template. Spell out the tone you want in the prompt, and read the email again before sending
- Pasting only the latest email from a long thread: the AI doesn't know what was discussed before, so the reply can easily contradict promises from the previous round. For formal correspondence, give it the relevant earlier emails too, in date order
- Misspelt names, company names and model numbers: AI sometimes "helpfully" changes a customer's name or a model number to a more common spelling. Check each one before sending
- Mass-sending outreach emails from one template: if the first sentence has nothing to do with the recipient's business, the reply rate will naturally be low. Write at least one sentence in each email that only applies to that customer
- Letting AI send emails automatically: a sales rep should read every draft before it goes out, the same point made in how to auto-reply to B2B sales enquiries with AI
- Pasting in sensitive material without thinking: handle contracts, floor prices, customer contact details and the like according to company rules, and if necessary strip out the sensitive information before giving anything to the AI
Pre-send checklist for trade emails
- Price, currency, trade terms and validity match the quotation sheet
- MOQ, lead time and sample policy are the current versions, not old rules
- Customer name, company name and product model are spelt correctly
- No promises that the AI added on its own
- Every [TO CONFIRM] has been dealt with or removed
- No stacked exclamation marks or stock openings
- Every attachment mentioned in the body is actually attached
FAQ
Is ChatGPT or Claude better for B2B cold outreach emails? For everyday inquiry replies and quotation emails, both are up to the job, so pick the one your team finds easier. For long, formal correspondence that quotes product manuals or contract terms, Claude is usually the more reassuring choice for staying reliable on long documents. The safest approach is to take one real email and try a round in each tool with the same prompt.
Will customers be able to tell an outreach email was written with AI? What customers usually notice isn't "written by AI" but "written from a template": a stock opening, too much enthusiasm, nothing to do with their business. Make the first sentence say clearly why you're contacting them, and keep the content accurate and the tone restrained. What customers care about is whether the email itself is worth reading.
How do I make AI-written inquiry replies sound less like AI? Ask explicitly in the prompt for a professional, restrained tone with no exclamation marks, and set a word limit. Then give it one or two of your company's best past replies as a reference, so it imitates the way your team actually writes.
How do I stop AI making mistakes when it quotes a very long product spec sheet? Give it the spec sheet together with the relevant earlier emails, ask it to cite the source of every parameter, and have it list separately any questions it can't find an answer to. If the document is especially long, paste only the sections relevant to this email, which also makes the manual check quicker.
Is the free tier enough for a small company just starting to use AI for trade emails? The free tier is enough for a comparison test: generate a reply to the same real inquiry in each tool and see which one needs the fewest edits. Each vendor changes its free-tier and paid-plan rules from time to time, so check their official websites for the current details, and decide whether to pay based on how many emails your team actually writes.
If you want to automate the whole inquiry-handling process, see how to auto-reply to B2B sales enquiries with AI. The same ChatGPT vs Claude comparison plays out a little differently for advertising; see ChatGPT or Claude for batch-testing ad copy.
Further reading: detailed tool profiles for ChatGPT and Claude.
