Home › Blog › Cold email reply rates by industry (2026): our data from 91,209 emails
Human reply rates by recipient industry and step from 91,209 cold emails we sent in 2026, plus what interested prospects asked first. Free CSV.
By Moe Alhosni · Published 30 October 2026 · 11 min read
Short answer: As of October 2026, in our own 2026 campaigns, hotel, resort and travel brands replied at 0.80% per email sent (423 human replies on 52,955 emails sent). US employment brands replied at 0.32% (123 human replies on 38,254 emails sent), so the gap is 2.5 times. Counted per contact it widens to 4.2 times: 4.4 human replies per 100 hotel contacts against 1.1 per 100. Of the replies that were positive, 15% to 23% opened by asking the price, depending on who received the email.
I'm Moe Alhosni, founder of ROI Maximizer. We run cold email for clients and get paid per qualified meeting, so I have an interest in these numbers looking good. Read the caveats before you quote any of them. The full aggregate data is a free CSV: cold-email-reply-study-2026.csv. You can reuse it under CC BY 4.0. Credit ROI Maximizer and link this page.
This study sits beside two pages that already use the same data. Cold email statistics puts our numbers next to the published benchmarks. Cold email positive reply rate benchmark breaks interested leads down by our clients' markets. This page asks a different question: who received the email, and how did that change the replies?
| Finding | Figure | Denominator |
|---|---|---|
| Human reply rate, hotel and travel brands | 0.80% (95% interval 0.73–0.88%) | 423 human replies on 52,955 emails sent, three campaigns |
| Human reply rate, US employment brands | 0.32% (95% interval 0.27–0.38%) | 123 human replies on 38,254 emails sent, one campaign |
| Positive replies that asked the price first | 15% to 23% | Positive-reply events (one client excluded), read in full, three groups of 366 to 1,364 |
A human reply is any reply a person wrote: yes, no, or "remove me". Auto-replies and out-of-office messages are excluded. The first two rows are not positive-reply rates, and nothing on this page gives a positive-reply rate by industry. The data for that does not exist in a form I can check, and the method section explains why.
Three datasets, each from ROI Maximizer's own Instantly workspace. I never add them together, and every table says which one it uses.
Rules I applied:
The computation is one script that reads the source files and writes only aggregates. No name, email address, company or reply text leaves it.
| Recipient industry | Campaigns | Emails sent | Human replies | Per email sent | Contacts | Replies per 100 contacts | First email's share of replies |
|---|---|---|---|---|---|---|---|
| Hotels, resorts and travel brands | 3 (P1 Communications) | 52,955 | 423 | 0.80% | 9,539 | 4.4 | 25% |
| US employment and skills-first brands | 1 (PR Noir) | 38,254 | 123 | 0.32% | 11,551 | 1.1 | 32% |
Per email sent, hotels and travel brands replied 2.5 times as often. Per contact the gap is 4.2 times, because the hotel sequences ran seven or eight emails and the employment sequence four. Each extra follow-up gave hotel contacts another chance to reply. That is the denominator problem from the statistics page in miniature: the same campaigns, two honest rates, and a different gap.
Why hotels replied more, I cannot fully say. One thing I know: most of the hotel campaigns' positive replies came off subject lines naming a travel outlet the client pitches to, and the body offers to get the prospect covered there. The rest I cannot separate. Each industry here is one client, one offer and one list, so industry, offer and list quality all move together.
So treat 2.5 times as what happened in these campaigns, not as a law about hotels.
Each step's rate is human replies divided by the emails sent at that step.
| Step | Hotels: emails sent | Hotels: human replies | Hotels: per email | Employment: emails sent | Employment: human replies | Employment: per email |
|---|---|---|---|---|---|---|
| First email | 9,539 | 107 | 1.12% | 11,551 | 39 | 0.34% |
| Follow-up 1 | 7,974 | 82 | 1.03% | 9,615 | 32 | 0.33% |
| Follow-up 2 | 7,745 | 60 | 0.77% | 8,854 | 29 (under 30) | 0.33% |
| Follow-up 3 | 6,994 | 48 | 0.69% | 8,234 | 23 (under 30) | 0.28% |
| Follow-up 4 | 6,865 | 51 | 0.74% | |||
| Follow-up 5 | 6,742 | 47 | 0.70% | |||
| Follow-up 6 | 6,605 | 28 (under 30) | 0.42% | |||
| Follow-up 7 | 491 | 0 (one campaign) | 0.00% |
Counts under 30 are marked: read those with care. Follow-up 7 ran in one campaign only.
Two patterns. In the hotel campaigns the rate fell from 1.12% on the first email to around 0.7% by follow-ups 3 to 5, then dropped at follow-up 6. In the employment campaign it hardly moved, 0.34% to 0.28%, so every follow-up was worth about as much as the first email. The first email produced a quarter to a third of all replies in both. Most replies came from follow-ups. How long to make a sequence is in how many follow-ups a cold email sequence needs.
| Campaign | Recipients | Steps | Emails sent | Human replies | Per email sent |
|---|---|---|---|---|---|
| A | Hotels and travel brands, Europe and Turkey | 7 | 46,201 | 360 | 0.78% |
| B | Hotels and travel brands, Caribbean | 7 | 2,196 | 22 (under 30) | 1.00% |
| C | Employment and skills-first brands, United States | 4 | 38,254 | 123 | 0.32% |
| D | Hotels and travel brands, Indian Ocean | 8 | 4,558 | 41 | 0.90% |
Every non-US campaign here is hotels and the only US campaign is employment brands. So this table cannot tell you whether Europe beats the US. All it shows is that the three hotel regions sat close together, 0.78% to 1.00%. A separate snapshot taken on 26 July 2026 found about three times as many positive replies per contact in Europe as in the US on the same offer. That snapshot did not keep its contact counts, so I have not recomputed it here. It stays on the statistics page as published.
This table counts unique people (all clients), each counted once, by the sector of the person who received the email. It is a share, not a rate. A sector's share mostly reflects how much we sent to it, so a large share does not mean that sector replies more.
| Recipient sector | People who replied positively | Share |
|---|---|---|
| Marketing, PR and creative agencies | 360 | 23.3% |
| Hotels, resorts and travel brands | 245 | 15.9% |
| Mixed B2B companies | 197 | 12.8% |
| B2B and tech companies (PR offer) | 185 | 12.0% |
| Italian companies (SMEs and SaaS startups) | 153 | 9.9% |
| Web3 and crypto startups | 123 | 8.0% |
| Finance, fintech and investment firms | 84 | 5.4% |
| US brands in six PR Noir target markets | 64 | 4.1% |
| Local home services (roofing, plumbing, moving) | 44 | 2.9% |
| Other sectors, each under 30 people | 19 | 1.2% |
| Unclassified | 69 | 4.5% |
| Total | 1,543 | 100% |
The Italian row comes from one client that our other headline figures leave out. The 64 PR Noir people are spread over six target markets, from nonprofits to consumer brands, and none of those markets reaches 30 on its own. That is why there is no row for each. Unclassified people came from campaigns stored only as an ID, where the subject line did not show the market.
The positive reply rate benchmark shows the same people split by the client's market instead. Use that page for what the replies said by client vertical. Use this one for who received the email.
These shares are positive-reply events (one client excluded), each classified from the full reply text, not a preview.
| Recipients | Replies | Asked for a call | Asked the price | Asked for proof | Asked for examples | Asked about scope | Price or proof first |
|---|---|---|---|---|---|---|---|
| Hotels, resorts and travel brands (P1 Communications) | 397 | 34% | 15% | 4% | 7% | 8% | 19% |
| B2B and tech companies (a B2B PR client) | 366 | 34% | 23% | 3% | 12% | 10% | 26% |
| Agencies, Web3, finance and mixed B2B (our own campaigns) | 1,364 | 50% | 15% | 20% | 6% | 4% | 35% |
The difference is in what people asked first. B2B and tech companies asked the price more than anyone: 23%. The recipients of our own pay-per-result offer asked for proof far more: 20%, against 3% to 4% elsewhere. My reading, which the data does not prove: an offer where you pay only for results sounds too good, so people want evidence before they book. Hotels asked about price and proof least, 19% combined.
In practice: if you sell to B2B and tech companies, have a written price answer ready before the first reply arrives. If your offer is unusual, put one proof point in the follow-up. How to answer each kind of reply is in how to reply to interested cold email replies.
One check that failed: Instantly's lead-level interest flags in our October 2026 archive looked like a ready-made denominator. In several copied campaigns more leads were flagged interested than had replied at all, so I dropped them.
Download cold-email-reply-study-2026.csv. It holds every aggregate on this page, with numerators, denominators, units and 95% intervals for the rates. It contains no personal data. It is free to reuse under CC BY 4.0: credit "ROI Maximizer (roimaxi.com)" and link this page. Never add rows from different tables; their units differ.
Citation: ROI Maximizer (roimaxi.com), Cold email reply rates by industry (2026), October 2026. https://roimaxi.com/blog/cold-email-reply-rates-by-industry-2026
The figures will be re-run each quarter with the same rules, alongside the statistics page. A figure that cannot be recounted the same way keeps its old value and its old date.
ROI Maximizer is a B2B lead generation agency founded and run by Moe Alhosni. We run cold email outbound and charge for qualified meetings that take place: a one-off setup of $1,000–$3,000, then $200–$500 per meeting, or a flat $5,000 a month. There is no minimum term and nothing is charged for a no-show. To turn a reply rate into a cost per meeting, use the cost per meeting calculator.
There is no reliable cross-industry table, because published studies count different things. In our 2026 campaigns, hotel and travel brands gave 0.80% human replies per email sent (423 on 52,955 emails sent), and US employment brands 0.32% (123 on 38,254). Compare your own rate only with figures counted the same way: per email sent, auto-replies removed.
Of the two industries we can measure with send counts, hotels and travel brands replied 2.5 times as often per email sent as US employment brands. Each industry was one client with one offer, so part of that gap is the offer and the list, not the industry.
Not in our data. For hotels and travel brands the per-email rate fell from 1.12% on the first email to about 0.7% by follow-ups 3 to 5. For US employment brands it stayed between 0.28% and 0.34% across all four emails. In both, most replies came from follow-ups.
Between 15% and 23% of positive replies asked the price first, read from the full reply text. B2B and tech companies asked most often (23% of 366). Our own pay-per-result campaigns drew the most requests for proof (20% of 1,364).
Yes. The aggregate CSV is free under CC BY 4.0. Credit ROI Maximizer (roimaxi.com) and link this page. Keep each figure's label and denominator with it, and do not add rows from different tables together.
Ask any agency quoting you a reply rate for the numerator, the denominator, how auto-replies were handled, the recipient industry and the dates. Get the definition of a qualified meeting in writing before outreach starts; ours is in what counts as a qualified meeting. Then run your deal size through the ROI calculator. If you want to talk it through, book 30 minutes or email moe@roimaxi.com.
About the author: Moe Alhosni, founder of ROI Maximizer. Before that he spent four and a half years in sales at Moody's in London, most recently as Assistant Director, Sales, working with banks, asset managers and private equity firms. He runs the campaigns behind the first-hand data on this site. LinkedIn
After Moody's he was Sales Director at Coinshift, a Web3 treasury management company (2024). Before Moody's he worked at BLOM Bank France in London on settlements and customer service, including AML/KYC record updates. Full career
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