What’s a good cold email open rate, reply rate, and meeting rate?

TL;DR

• Open rate: 40-60% is healthy. Under 25% means your deliverability is broken or your subject lines are dead. Over 70% sounds great but often means open-tracking is inflating itself (Apple Mail Privacy Protection auto-opens count).
• Total reply rate: 2-5% is normal cold. 5-10% is good. 10%+ usually means you’re either warm or running a tightly targeted niche.
• Positive reply rate: 0.5-2% on cold. This is the number that actually matters — total reply rate includes “unsubscribe me,” “wrong person,” and “not interested.”
• Meeting booked rate (per send): 0.3-1.5%. So 1,000 sends = 3-15 meetings.
• Spam complaint rate: under 0.1% always. 0.3% gets you throttled at Gmail. 0.5% gets you blocked.
• Apple Mail Privacy Protection has broken open rates as a metric. Stop optimizing on opens. Optimize on reply rate.

Open rate — and why it’s a broken metric

The reported open rate on your campaign tool is no longer a clean measurement. Apple’s Mail Privacy Protection (MPP), launched in iOS 15 and now the default for most Apple Mail users, pre-fetches tracking pixels on the server side. That means every email sent to an Apple Mail user gets “opened” the moment it arrives, regardless of whether the human ever sees it.

For B2B audiences, Apple Mail accounts for roughly 30-50% of recipients depending on segment. So if your campaign tool reports a 55% open rate, the real human open rate is probably 35-45%. Subtract the auto-opens; that’s your actual signal.

The practical numbers, after MPP correction:

• Excellent: 50-65% reported (real human opens ~35-50%). Strong subject lines, clean deliverability, named sender.
• Good: 40-50% reported. Healthy infrastructure, decent subject lines.
• Watch: 25-40% reported. Either subject lines need work or you’re landing in promotions/spam at meaningful rates.
• Broken: under 25% reported. Either deliverability is collapsed (most likely) or your list is bad. Stop the campaign and diagnose.

The most common cause of an open rate under 25% is not the subject line — it’s spam-folder placement. Your domain reputation, authentication setup (SPF, DKIM, DMARC), or warmup state is the problem. Subject lines are second-order.

Reply rate — the metric that actually counts

Reply rate is the number you should be tracking. It survives MPP, it correlates directly with pipeline, and it’s harder to game than open rate. The general ranges, across B2B cold outbound:

• 2-5%: normal cold outbound. Generic ICP, templated copy, no warm signal. This is most teams’ baseline.
• 5-10%: good. Specific ICP, real personalization (not just {{firstName}}), tight subject lines, multi-touch sequencing.
• 10-15%: very good. Usually means tight niche targeting, founder sender, or a campaign with strong specificity to the prospect.
• 15%+: either warm outreach disguised as cold, a very narrow high-intent list, or measurement error. Sanity-check.

Segment matters. SMB cold campaigns tend to see lower reply rates (2-4%) because SMB owners are buried in vendor pitches and respond reflexively to fewer of them. Enterprise sees 3-7% on tight ICP campaigns where the prospect knows the problem you’re solving. Mid-market is the sweet spot for cold outbound and consistently produces the highest reply rates per send across the three.

Positive reply rate — the only number that maps to pipeline

Total reply rate is misleading because it counts every reply, including “unsubscribe me,” “not interested,” “wrong person,” out-of-office bounces, and angry responses. A campaign with a 7% reply rate and a 0.3% positive reply rate is worse than a campaign with a 4% reply rate and a 1.8% positive reply rate.

The split, on healthy campaigns:

• Positive (interested, want to talk, ask a question): 15-35% of total replies.
• Soft pass (not now, maybe later, ping me in 6 months): 20-35% of total replies.
• Hard pass (not interested, unsubscribe, remove me): 25-45% of total replies.
• Out-of-office, wrong person, autoresponder: 10-25% of total replies.

Positive reply rate of 0.5-2% per send is the operating range for B2B cold outbound. Under 0.3% means your ICP is wrong or your value prop isn’t landing. Over 2.5% usually means warm signal, narrow targeting, or strong founder credibility doing the work.

Meeting-booked rate — the unit of pipeline

Meetings booked per 1,000 sends is the metric every founder should be able to quote. It collapses opens, replies, positive replies, and the meeting-coordination step into one number that you can multiply against pipeline math.

Healthy ranges:

• 3-8 meetings per 1,000 sends: solid cold motion. Most production B2B campaigns land here.
• 8-15 meetings per 1,000 sends: very good. Tight ICP, real personalization, fast reply triage.
• 15-30 meetings per 1,000 sends: exceptional. Usually a founder-sender, narrow niche, or strong inbound assist.
• Under 2 meetings per 1,000 sends: campaign is broken somewhere. Diagnose against the upstream metrics — open, reply, positive reply — to find the leaking gate.

The meeting-show rate matters separately. Of meetings booked, 65-85% actually show up. The 15-35% no-show rate is largely a function of how much time passes between booking and meeting, and whether you send a reminder. A 30-minute meeting booked 2 days out shows at 80-85%; one booked 2 weeks out shows at 55-70%.

The numbers you don’t want — spam complaints, bounces, unsubscribes

Three ceilings you cannot cross:

• Spam complaint rate: keep under 0.1% always. Gmail throttles at 0.3% and blocks at 0.5%+. Microsoft is similar. Your campaign tool shows this metric; check it weekly. If it’s climbing, your list is junk or your copy is fooling spam classifiers.
• Hard bounce rate: under 3% per campaign. Over 5% and you’re burning sender reputation fast. The fix is list hygiene — verify before sending. See bounce taxonomy for the full failure-mode map.
• Unsubscribe rate: under 1% per send. This isn’t a deliverability number, but a high unsubscribe rate (2%+) means you’re hitting the wrong people or the message reads as marketing blast.

The Gmail/Yahoo bulk sender rules (in effect since Feb 2024) make these ceilings firm. The 0.3% spam complaint threshold isn’t a guideline; it’s an enforcement trigger. See bulk sender requirements.

Benchmarks by segment

Rough numbers across the three segments most B2B founders sell into:

The diagnostic framework — which number is broken

If your campaign is underperforming, the answer is usually a specific gate in the funnel, not a global problem. Trace the funnel:

• Open rate is the problem: deliverability (most likely), subject lines (second), or list (third). Start with deliverability.
• Open rate is fine, reply rate is low: copy is the problem. Either the value prop doesn’t land or the CTA is too heavy. See value prop framing and CTA architecture.
• Reply rate is fine, positive reply rate is low: ICP is wrong. You’re reaching people but not the right people. Tighten the list.
• Positive replies are fine, meeting rate is low: triage is the problem. You’re losing interested prospects because reply handoff takes too long. See triage workflow.
• Meetings are booked but no-show rate is high: booking-to-meeting lag is too long, or no confirmation cadence.

The honest caveat

Every benchmark is segment-conditional. A 1% reply rate on a campaign to Fortune 500 CTOs about a $500K platform is a win; an 8% reply rate on a campaign to startup founders about a $99/mo tool is mediocre. The numbers in this chapter are operating ranges across typical B2B cold motions. They’re a sanity check, not a target.

The right question isn’t “is my reply rate good.” It’s “is my meetings-booked-per-send number consistent with a pipeline I can close.” That answer depends on your ACV, your close rate, and the volume your infrastructure can sustain — and that’s the math worth doing.

Where this fits

These benchmarks are upstream of the pipeline-conversion math covered in pipeline conversion, which takes meetings booked and turns them into closed-won dollars. The diagnostic framework above is the entry point for everything else in the replies cluster: classification, routing, triage, and objection handling all assume you’ve measured where the funnel is leaking before you start fixing things.