Home › Blog › Cold email positive reply rate: what 1,543 interested leads said, by vertical
Cold email positive reply rate benchmarks disagree by 10x because they count different things. Our counting rule, and 1,543 interested leads by vertical.
By Moe Alhosni · Published 13 October 2026 · Updated 25 October 2026 · 11 min read
Short answer: There is no single cold email positive reply rate benchmark, because published figures count different things: Belkins reports 0.45% of emails sent get any reply (auto-replies removed); Apollo tells SDRs to aim for 4–6% positive replies. Our defined set: 1,543 people who replied positively to live campaigns between August 2025 and July 2026, counted once each and split by vertical, below.
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I run a pay-per-meeting lead generation agency, so I have an interest in positive replies looking like a solved problem. They are not. Read the section on what this data cannot tell you before you quote any of it.
Belkins' 0.45% and Apollo's 4–6% can both be right, ten times apart. The 1,543 people further down are also classified by what they said, and they give no rate per 1,000 sends; the reason is under what this data cannot tell you.
The main published figures, all as of October 2026, with the counting rule each one uses.
Three things move the number. The denominator: emails sent, delivered, unique contacts, or unique opens. The numerator: every reply, or only the ones you would want. And auto-replies: if Sales.co is right that nearly half of replies are automatic, leaving them in roughly doubles the rate. Belkins and Apollo are the same industry describing different fractions.
Belkins is the only one of those pages that publishes both its counting rule and an industry split. None of them says what the replies actually said. This page does, with its limits stated.
A reply from a human that does one of five things:
Not a positive reply: auto-replies, bounces, out-of-office, "not interested", "remove me", and polite declines. "Not now, try me in Q2" sits on the line. I count it, and six of the 1,543 people said it, so it changes nothing.
A positive reply is not a meeting, and a meeting is not a qualified meeting. That last definition is at what counts as a qualified meeting, and it is the one that decides what you pay.
A positive reply, in our data, is a reply marked Interested in our Instantly workspace. The five types above describe what those replies say. This is the counting rule behind them.
Most Interested labels were set by Instantly's AI classifier. About 93 replies it flagged were later marked otherwise, so they are out, and a few genuine positives are probably still mislabelled. The data covers replies from 7 August 2025 to 24 July 2026, extracted on 26 July 2026 from ROI Maximizer's own Instantly workspace, run by Moe Alhosni.
Our data, counted five ways:
| What is counted | Figure |
|---|---|
| Emails received, any kind | 20,558 |
| Positive reply events, every client | 2,619 |
| Positive reply events, one client excluded | 2,333 |
| Unique interested leads, every client | 1,543 |
| Unique interested leads, one client excluded | 1,378 |
A reply event is one email. A unique lead is one person, dated by their first positive reply; some people replied positively more than once. The tables on this page count people: 1,543 interested leads, that one client included. Its four campaigns account for 165 of them, and our headline reply-event figure, 2,333, leaves them out. A few short windows, from minutes to a day around 1–2 September 2025, 4–5 December 2025, 22 May 2026 and 14 July 2026, are missing because corrupted email bodies broke the export.
None of this is a rate. A rate needs a denominator, and that is where published benchmarks split. Per email or per contact: a five-step sequence sends up to five emails per contact, so its per-contact rate can be up to five times its per-email rate. Every reply or only positive ones: Sales.co found only 14.1% of replies were positive (checked 16 October 2026). Stack the two choices and a tenfold gap can appear with no difference in how the campaigns performed. Every figure we publish, with its denominator labelled, is on our cold email statistics page.
Source: every person who replied positively to our own and client campaigns on Instantly, one row per person, first positive reply dated 7 August 2025 to 24 July 2026. The vertical is the client's market. Clients other than PR Noir and P1 Communications are not named.
| Vertical | People who replied positively | Share |
|---|---|---|
| B2B PR agencies | 300 | 19.4% |
| Agency partnerships | 289 | 18.7% |
| Hospitality PR (UK) | 208 | 13.5% |
| Unlabelled campaign | 198 | 12.8% |
| B2B SaaS | 142 | 9.2% |
| Own outbound (our lead-gen offer) | 138 | 8.9% |
| Web3 / crypto | 123 | 8.0% |
| Finance / PE-VC data | 111 | 7.2% |
| Local / consumer services | 34 | 2.2% |
Hospitality PR (UK) is P1 Communications, whose case study is public. Own outbound is us selling our own service. Unlabelled campaign is 198 people from campaigns that never carried a vertical tag; I left them in because removing them would make the shares look tidier than the data is.
Just over half of the 1,543 came from PR and agency campaigns. That reflects where our clients are, not where cold email works best. It is not a ranking of verticals.
Each person's reply was classified by keyword from its preview, a short opening snippet, not the full text.
| Reply type | Count | Share |
|---|---|---|
| Unclassified positive | 869 | 56.3% |
| Interested | 268 | 17.4% |
| Wants a call | 168 | 10.9% |
| Asked price | 114 | 7.4% |
| Asked for info | 91 | 5.9% |
| Referral | 27 | 1.7% |
| Not now | 6 | 0.4% |
56.3% matched no class. A short preview often stops before the person says what they want, and some replies are not in English. I am not relabelling those as interested. In the previews, the clean intent cluster is interested plus wants a call: 28% of the 1,543.
Read in full, the replies say more. 1,364 positive replies to our own campaigns (counted per reply, not per person) were classified from their complete text: 50% asked for a call, 20% for proof, 15% for the price, 6% for examples and 4% about scope. On a B2B PR client's campaigns, 366 positive replies read in full show 34% asking for a call, 23% for the price, 12% for examples and 10% about scope. Those are the shares to quote. The preview tables show how the verticals differ, not how often people ask for a call.
By vertical, from the previews, as a share of each vertical's people:
| Vertical | n | Interested | Wants a call | Asked price | Asked for info | Referral |
|---|---|---|---|---|---|---|
| B2B PR agencies | 300 | 16% | 12% | 10% | 6% | 2% |
| Agency partnerships | 289 | 32% | 10% | 10% | 8% | 0% |
| Hospitality PR (UK) | 208 | 7% | 5% | 8% | 4% | 5% |
| Unlabelled campaign | 198 | 13% | 8% | 5% | 3% | 4% |
| B2B SaaS | 142 | 1% | 7% | 1% | 1% | 1% |
| Own outbound | 138 | 17% | 20% | 7% | 7% | 0% |
| Web3 / crypto | 123 | 18% | 17% | 4% | 11% | 2% |
| Finance / PE-VC data | 111 | 23% | 12% | 10% | 7% | 0% |
| Local / consumer services | 34 | 38% | 12% | 3% | 6% | 0% |
Agency partnerships produced the most explicit interest of any large row: 32% said so in words. Local services is higher at 38%, but that is 13 people out of 34.
B2B SaaS is the odd row: 1% interested, 1% asked price, roughly nine in ten unclassified. Most of its replies are not in English, and a keyword classifier built on English words, reading only a short preview, misses them. All 142 people in this row come from the one client our other headline figures leave out. Do not read it as "SaaS buyers never ask about price".
Hospitality PR had the highest referral share at 5%, so in that market our second email asks for the right name instead of pushing for a call.
114 people, 7.4% of the 1,543, led with a price question in the preview. In B2B PR agencies, agency partnerships and finance it was 10%. Read in full and counted per reply, the share is higher: 15% of our own campaigns' 1,364 positive replies and 23% of a B2B PR client's 366.
That is 10% to 23% of your warmest replies, depending on the vertical and on whether you read the preview or the whole reply, and the standard playbook answers it with "happy to jump on a quick call to walk you through it". The person recognises the dodge. Two consequences.
First, whoever handles replies needs a price answer ready. If you cannot state your pricing in an email, you cannot state it in a meeting either. Ours fits in one line: a one-off setup fee of $1,000 to $3,000, then $200 to $500 per qualified meeting, no minimum spend, nothing charged for a no-show; or a flat $5,000 a month with no per-meeting fee. Where in each range is confirmed on the call once we have seen your deal size.
Second, email two in the sequence should pre-empt it. If one in ten of the people who were going to reply were going to ask about price, stating the model in email two moves some of them from "asked price" to "wants a call" and filters out the ones for whom the model is a no. Fewer replies, better ones. A reply count looks better when you hide the price. A meeting count does not, which is one of the real differences between paying per meeting and paying a retainer.
question, {FirstName}: 225 people, 15% of the 1,543, off one subject line.{Company} featured in {Publication}: 403 people. The outlet is one the PR client pitches to, and the body offers to get the prospect covered there.partnership with {Company}: 75 people.One caveat. These are the subject lines of emails that got a positive reply. I do not have, in this file, the subject lines of the emails that got nothing. So I cannot say question, {FirstName} has a higher reply rate than anything else. I can say that 15% of the people who replied positively did so to that one line, which is a different claim. If a whole campaign gets nothing, why cold emails get no replies sets out what to check first.
When an agency or a tool quotes you a reply rate, ask for five things: the numerator, the denominator, how auto-replies were handled, the vertical, and the dates. If one is missing, the number is marketing. The rest of the questions are in how to tell if a lead generation agency is any good.
First replies land in weeks two and three and decision-maker conversations in weeks three and four; the phases are in how long until cold outreach books meetings.
A reply from a person that says they are interested, asks for a call or a time, asks what it costs, asks for a deck, case study or examples, or refers you to the right person. Auto-replies, bounces, out-of-office, "not interested", "remove me" and polite declines are not positive replies. A positive reply is not yet a meeting.
The published answers run from Mailshake's 0.5–1.5% average for SaaS senders to Apollo's 4–6% target, and they count different things. Before you compare yourself with any of them, ask for the numerator, the denominator, how auto-replies were handled, the vertical and the dates. If one is missing, the number is marketing.
This dataset stops at the reply, so it cannot say. The one published conversion we have is PR Noir: 27 leads became 10 meetings, 37% lead-to-meeting, in one window for one client. Do not multiply anything by it. A meeting is also not yet a qualified meeting; that definition is the one you pay on.
They measure different fractions. Belkins divides unique replies, auto-replies and bounces removed, by emails sent and gets 0.45%. Apollo's 4–6% is a positive-reply target. Count per contact instead of per email and a five-step sequence can read up to five times higher. Stack the two choices and a tenfold gap appears.
We cannot give a rate per vertical, because the export has replies, not sends. What differs is what people said. In the previews, 32% of agency partnership leads said they were interested, against 7% in UK hospitality PR, and hospitality PR had the highest referral share, 5%. The B2B SaaS row is distorted by replies not in English.
Get three things in writing before outreach starts: the qualification definition, the no-show terms, and what happens in a month with zero meetings. A qualified meeting is defined at what counts as a qualified meeting. Then use the ROI calculator to work out the most you should pay per meeting before anyone quotes you a number.
About the author: Moe Alhosni, founder of ROI Maximizer. He runs the campaigns behind the first-hand data on this site. LinkedIn
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