Does the month you send cold email in matter more than the day or the hour?

We’ve already covered that the day of the week and the hour of the day move your reply rate by a little, not a lot — a Wednesday morning edge here, a weekend dip there, nothing worth rebuilding a workflow around. But that analysis only looked at timing within a week. Zoom out to the calendar year, and a 2025 dataset of 7.5 million cold emails shows a timing variable that moves the number by a lot more than any hour or weekday does: the month.

The gap, in one chart

Belkins, What Are B2B Cold Email Response Rates? (2026 Study), based on 7.5M emails sent in 2025

That’s not a rounding difference. February’s 0.54% reply rate is about 54% higher, relatively, than December’s 0.35% — a bigger spread than the “Wednesday edges out Saturday” pattern the day-of-week data shows. Zoom out further and the same dataset found the first half of 2025 averaged 0.50% reply rate, while the second half dropped to 0.40%, a 20% decline within a single year, with the sharpest fall landing in July and August.

So does month beat day and hour?

By the size of the effect in this dataset, yes. The day-of-week research we covered previously found modest differences that the study’s own authors described as small. The month-level swing here — 0.54% down to 0.35%, a genuine 54% relative gap — is a larger effect on the same metric, in the same broad category of data. If you’re going to spend attention optimizing a timing variable, the calendar month you’re launching in is the one with more evidence behind it moving the number.

That said, “bigger than a small effect” is a low bar, and one important caveat applies here that doesn’t apply as cleanly to day-of-week data: this is one calendar year from one agency’s client mix, not a controlled experiment holding everything else constant. Some of what shows up as a “July dip” could be which industries or campaigns happened to be active that month, not a pure calendar effect. Treat the direction as credible and the exact percentages as one real year, not a law of nature.

Why the shape looks the way it does

The pattern isn’t random. It tracks pretty closely with when B2B decision-makers are actually at their desks, engaged, and looking for new things to say yes to:

• February peaks because it’s the first full working month after new budgets, new initiatives, and new fiscal-year priorities have landed, and people are back from the holidays with a cleared inbox and some appetite to evaluate new vendors.
• July and August dip because summer vacation season across North American and European markets means a meaningful share of any given recipient list is simply out of office, or working reduced hours with a reduced appetite for anything new.
• December bottoms out for the obvious reason: budget freezes, year-end close, holiday travel, and a general “nothing new until January” posture that most B2B buyers share regardless of industry.

None of this is a secret once you say it out loud — most salespeople already sense that August and December are slow. What the data adds is a sense of scale: it’s not a vague vibe, it’s a measured ~54% swing in the same metric across the same sending population.

What to actually do with a seasonal pattern this size

A ~54% swing is large enough to change how you read a bad month, but not large enough to justify shutting a program down for a quarter. A few practical adjustments the data actually supports:

• Reset your baseline monthly, not just quarterly. A campaign that looks flat in August against your February numbers might be performing normally for August — comparing it to last August, not last February, is the fairer test.
• Front-load high-effort, high-stakes campaigns into January-March and September-October. If a campaign genuinely needs its best shot — a product launch push, a high-value target list — the data says those windows carry a real edge over July or December.
• Keep steady, lower-key volume through the slow months instead of stopping. Volume math still applies in a slow month; you’re just working with a lower expected reply rate going in, not zero.

The false alarm this pattern explains

There’s a specific, recurring panic this data quietly resolves: a team watches its reply rate drop through July and August, assumes the list has gone stale or the copy has stopped working, and starts rewriting subject lines or re-verifying contacts that were never the problem. List decay is real and worth checking independently, but a seasonal dip that tracks the calendar rather than the list’s age is a different diagnosis entirely, and confusing the two wastes effort on the wrong fix. Before concluding a list needs cleaning or a sequence needs a rewrite, check what month it is first — if the drop lines up with a known seasonal trough rather than a sudden cliff mid-month, the list and the copy are probably fine.

Where Norbelys fits into a seasonal calendar

None of this requires guessing when to hit pause, because you shouldn’t be pausing — you should be adjusting. Norbelys lets you schedule campaigns and sequences in advance across any stretch of the year, keep warmup running continuously so a slower month doesn’t cost you sender reputation on top of reply rate, and compare a campaign’s performance against its own history in analytics instead of a single flat industry number that doesn’t account for what month it is. That’s the difference between “our reply rate dropped, something’s broken” and “it’s August, and the data says to expect that” — one of those is a fire drill, the other is a Tuesday.

Building a sending calendar that accounts for the real seasonal pattern, instead of sending the same volume blind every month, starts with a plan you can actually schedule. See how Norbelys’s plans handle ongoing campaigns and start building your 2026 send calendar today.

Seasonal cold email timing — quick answers

Should I pause cold email entirely in July, August, or December?+

The data doesn't support a full pause — it supports adjusted expectations and, if you have discretion over the calendar, front-loading your highest-effort campaigns into the stronger months instead. Stopping entirely costs you domain warmup consistency and the replies that do still arrive during slow months, both of which have real value.

Is February really the single best month to launch a campaign?+

It's the peak month in this particular 2025 dataset, not a guaranteed law for every year or every list. Treat it as a reasonable default for scheduling a high-stakes launch when you have the choice, not as a number to build an entire annual plan around.

How is this different from the day-of-week and hour-of-day timing data?+

Different scale, same underlying idea: recipient availability and attention change the number, whether you're measuring it across a week or across a year. The month-level swing in this dataset is larger than the published day-of-week and hour-of-day differences, which is why it's worth checking before optimizing a smaller lever.