Cold email response rates in 2026: what actually moves the number

Belkins tracked 7,530,489 cold emails sent across 2025 and counted 34,393 replies. That's a 0.45% average reply rate. If your program is still budgeting around 2-3% response rates because that's the number a sales tool quoted you in 2023, this is the data that tells you to stop.

What Belkins actually measured

Most cold email benchmark reports quote reply rate against opens, which inflates the number and makes every vendor's report look better than the last one. Belkins didn't do that. In its 2026 response rate study, the agency defines reply rate as unique replies divided by total emails sent, excluding auto-replies and bounce notifications. That's the denominator that matters, because it's the one your pipeline actually runs on.

The dataset behind it is large enough to trust: 7,530,489 emails sent across client campaigns from January through December 2025, producing 34,393 replies and more than 1,200 booked appointments. Belkins also flagged something worth noting for anyone comparing this to older reports — open rate tracking was effectively disabled across most of 2025 as Apple Mail Privacy Protection and Gmail's own prefetching made open data unreliable. That's part of why the field is standardizing on reply rate as the honest metric, and why cold email response rates reported this way look lower than the inflated numbers still floating around from 2021 and 2022.

There's a reason this distinction matters more than it might sound like. Two agencies can run the exact same list, the exact same copy, and the exact same send cadence, and still report wildly different reply rates just because one is dividing by opens and the other by total sends. If a vendor quotes you a cold email reply rate without telling you the denominator, ask. It's the single fastest way to tell whether a benchmark is comparable to your own numbers or just marketing.

Cold email response rates by month and send timing

Reply rate wasn't flat across the year. February was the peak month at 0.54%, and December was the floor at 0.35% — no surprise, given how much of December disappears into end-of-year noise and out-of-office replies. First-half 2025 averaged 0.50% reply rate; second-half dropped to 0.40%. September and October sat closer to the annual average at 0.45%. If you're setting quarterly targets, don't use the same number for every quarter. A campaign that hits 0.40% in November isn't underperforming — it's tracking the calendar.

Day of week followed a predictable shape: Wednesday and Thursday outperformed the rest of the week at 0.48%, Monday sat mid-range, and Friday dropped off. Sunday showed a reply rate of 0.57%, but Belkins flagged that number as statistically unreliable — it's built on only 21,615 emails, a fraction of the volume behind every other data point in the study. Don't build a Sunday-send strategy on a sample that small. This is the same conclusion we reached looking at Instantly's 2026 benchmark data on reply timing: send-time discipline moves the number, but it's a secondary lever, not the primary one.

Cold email response rates by seniority and company size

This is where the study gets genuinely useful for targeting decisions, and it contradicts a lot of default GTM strategy. Founders and owners replied at 0.57% — the highest of any seniority tier Belkins tracked. C-level executives came in at 0.42%. VPs, the tier most B2B outbound programs default to targeting because they sit in the buying committee without the gatekeeper problem of a director, replied at just 0.32% — the lowest of the three groups measured.

Company size shows the same pattern from a different angle. Reply rate drops almost in a straight line as company headcount goes up. Companies with 0-10 employees replied at 0.72% — nearly triple the smallest enterprise segment. Companies in the 11-50 employee range replied at 0.49%, close to the overall average. At 10,000+ employees, reply rate falls to 0.22%. If your ICP is enterprise and your reply-rate targets are built off small-business benchmarks, you're setting your team up to look like they're failing at a number nobody at that company size actually hits.

The read here isn't complicated: founders at small companies reply because they're still doing their own inbox triage and a relevant pitch can actually reach them without three layers of EA and delegated authority in between. A VP at a 10,000-person company has neither the time nor, usually, the authority to reply to a cold email — even a good one. If your outbound program is chasing b2b outbound benchmarks that assume flat performance across every title and company size, you're measuring your SDR team against a number that was never achievable for their actual target list.

This also explains a pattern most outbound managers have seen and never quite put a number on: the rep with the "easy" territory of smaller companies consistently outperforms the rep working named enterprise accounts, even when both are running the same sequence and the same offer. It was never a skill gap. A 0.72% ceiling and a 0.22% ceiling aren't the same game, and comping both reps against the same quota target guarantees one of them looks like they're failing at something nobody in that segment is actually achieving.

Reply rates by industry and geography

Reply rate by industry is where the spread gets extreme. Food & Beverage led every other sector Belkins tracked at 3.47% — nearly eight times the overall average. Education and Government also ran meaningfully above average, though Belkins didn't publish exact figures for those two beyond noting they outperform the baseline. On the other end, Banking and Insurance sat at the bottom of the distribution. In between, a cluster of industries — Construction, Financial Services, Healthcare, and Legal Services — landed in a tighter 0.56% to 0.60% band, each a bit above the 0.45% average but nowhere near Food & Beverage's outlier performance.

Geography told a similar story of wide variance. Poland led every country Belkins tracked at 1.43%, though on a comparatively small sample of about 46,000 emails. Ireland and Denmark followed at 0.74% and 0.73%, also on lower volume. Among the countries with real send volume behind them, Canada posted 0.63% across 266,000 emails, the United States came in at 0.51% across more than 5.6 million emails — the bulk of the entire dataset — and the United Kingdom sat at 0.48% across 370,000-plus emails. South Africa ranked among the top ten performers without a published exact figure. The takeaway on geography: don't over-read small-sample countries as strategy. The U.S. number, at 0.51%, is the one built on enough volume to actually plan around.

It's worth pausing on why Food & Beverage sits so far outside every other industry in this dataset. A 3.47% reply rate isn't a rounding difference from the 0.45% average — it's a different category of response entirely, and the most likely explanation isn't that the copy is better. It's that the buying dynamic is different. Food & Beverage vendors and distributors are used to fielding cold outreach as a normal part of how the industry sources new suppliers, and the decision-makers tend to be smaller operators who, like the founders in the seniority breakdown, are still reading their own inbox. Government and Education show the same shape for a related reason: procurement cycles in both sectors run on relationships that often start cold, so a cold email isn't fighting the same uphill battle it fights in a category like banking, where compliance and vendor-approval processes make any unsolicited pitch a much harder sell before it's even read.

“Reply rate as replies divided by total emails sent. It's a stricter and, frankly, more honest denominator.”

What this means for your program

Take these numbers and do three things with them. First, stop setting a single blended reply-rate target for the whole program. A campaign hitting founders at small companies in Food & Beverage should be judged against a completely different bar than a campaign hitting VPs at enterprise accounts in banking. Blending those into one team-wide KPI punishes the rep working the harder list and lets the rep working the easier one coast.

Second, revisit who you're actually targeting inside the accounts you already have on your list. If your ICP includes founder-led companies and your sequences are set to bypass founders in favor of a VP of Marketing because that's who's listed as the buying contact, you're routing around the highest-reply-rate seniority tier in the entire dataset. That's not a copy problem. It's a targeting problem, and no amount of subject-line testing fixes it.

Third, treat the send-time and day-of-week data as a real but secondary lever. Shifting sends into the Wednesday-Thursday, 8 AM-to-noon window is close to free — it costs nothing but scheduling discipline — and it's worth doing. But the gap between 0.40% and 0.54% from timing alone is much smaller than the gap between 0.22% and 0.72% from company size, or 0.32% and 0.57% from seniority. Fix targeting first. Then tune timing.

There's a fourth move worth naming, even though it doesn't show up as a line item in Belkins' data: build the seasonality into your forecasting. A pipeline model that expects February's 0.54% reply rate to hold through December's 0.35% is going to make your Q4 numbers look like a program failure when they're actually just a program running into the calendar everyone else is running into. Sales leadership tends to punish the rep or the agency for a December dip that's structural, not situational. Set the expectation ahead of time and that conversation never has to happen.

None of this works if the emails aren't landing in the first place. A reply-rate benchmark assumes your sends are actually reaching the inbox, and that assumption breaks down fast on infrastructure that wasn't built for volume. We've written about the tradeoffs between shared and dedicated cold email infrastructure for exactly this reason — the benchmark numbers in this study assume clean sending domains and healthy sender reputation, not a program still fighting spam-folder placement. And if your outbound partner can't explain which of these levers — seniority, company size, industry, timing — they're actually pulling for your account, that's usually the first sign of the visibility gap that ends up costing agencies the retainer months later.

We've seen this play out directly. On the FMS Investor engagement, the shift that moved reply rate wasn't a copy rewrite — it was re-segmenting the list toward the company sizes and seniority tiers that were actually replying, instead of running one blended sequence across the whole B2B target list. That's the same lesson this data supports: the list segmentation decision moves the number more than anything you write inside the email.

Do this next

Pull your last 90 days of send data and break reply rate out by company size and seniority, not just by campaign or sequence. If you don't already tag contacts by employee count and title tier at the CRM level, that's the first fix — you can't act on this data if you can't see it in your own reporting. Once you can see it, kill or deprioritize the segments performing at a third of your average, and shift that budget toward founder-led and small-company accounts where the reply rate is genuinely higher. Then move your send windows to Wednesday and Thursday mornings, because it's free and it works. If none of this is visible in your current reporting, that's worth fixing before the next campaign launches — talk to our cold email team about what a segmented, reply-rate-aware program actually looks like.

See where you are cited today

A free snapshot audit of your rankings and AI citations before we ever talk.