What Is a Good Email Open Rate? How to Judge Yours

There is no single "good" email open rate. Mailchimp's published average across all its users is 35.63%, but that figure dates from December 2023, blends every industry together and counts opens that privacy features and security scanners can trigger without anyone reading. For a small business, a more useful answer is this: a good open rate is one that holds steady or rises against your own baseline, for the same type of email, sent to the same audience and measured the same way.

This guide gives you the published numbers, explains why they rarely transfer cleanly to your list, and shows how to tell a harmless dip from a real delivery problem. If you are still unsure how opens relate to clicks and click-to-open rate, start with our explainer on click rate vs click-through rate.

What an open rate actually counts

The usual formula is unique opens ÷ emails delivered × 100. Mailchimp's help centre describes open rate as the share of successfully delivered emails that recipients opened.

The "open" itself is detected by a tiny, invisible tracking image placed in the email. When that image is downloaded, the platform records an open. That mechanism explains almost every oddity you will see in your reports:

• Some real reads are never counted. Plain-text emails carry no image, so they cannot be tracked at all. People who keep images switched off do not load the image either. Mailchimp counts a click as an open even when the image did not load, which narrows the gap but does not close it.
• Some opens are not reads. Anything that downloads the image registers an open, whether or not a person looked at the message.

In other words, your open rate is really a "tracking image loaded" rate. That is still worth watching, as long as you read it for what it is.

The published benchmarks, and what they leave out

The most widely quoted free benchmarks come from Mailchimp's email marketing benchmarks page. Its headline averages are:

• All users: 35.63% open rate, 2.62% click rate
• Non-profits: 40.04% open rate, 3.27% click rate
• Education and training: 35.64% open rate, 3.02% click rate
• Business and finance: 31.35% open rate, 2.78% click rate
• Ecommerce: 29.81% open rate, 1.74% click rate

Before you hold your own campaigns up against those numbers, notice four things the source itself tells you:

• 1. The data is not recent. Mailchimp states the figures were last updated in December 2023 and may differ from benchmarks shown inside its app.
• 2. It is an average of very different senders. The data covers campaigns sent to at least 1,000 subscribers, from one-person startups to Fortune 500 companies, in industries the users reported themselves.
• 3. Privacy features affect it. Mailchimp's own disclaimer says open-rate accuracy may be impacted by Apple's Mail Privacy Protection. Its bot-filtering help page says filtered reporting for Apple MPP opens is available from July 10, 2024, which is after the benchmark date.
• 4. It reflects one platform's counting rules. Another tool may treat bots, deliveries and repeat opens differently, so its averages are not interchangeable with these.

Use a benchmark as a sanity check, not a target. If you are at 9% while comparable senders report around 30%, something is probably wrong and worth investigating. If you are at 33% and the benchmark says 35.63%, the difference tells you nothing.

Why your open rate can look better than it is

Apple Mail Privacy Protection. Apple's privacy page explains that when Protect Mail Activity is on, Mail downloads remote content in the background when a message is received, rather than only when the person opens it. A tracking image is remote content, so many Apple Mail users register an "open" at delivery time. Our guide to Apple Mail Privacy Protection and open rates covers the measurement side of this in detail.

Security scanners and link previews. Mailchimp's article on bot activity lists antivirus scans, anti-spam security from email providers, Apple MPP and link preview generators as non-human activity that can falsely inflate open and click metrics. It also warns that open and click metrics drop significantly when bot filtering is switched on.

The practical upshot: a list with many Apple Mail users, or many company inboxes protected by security filters, can show a healthy open rate even when interest is falling. That is why a high open rate on its own should never be taken as proof that a campaign worked.

Why it can look worse than it is

Low numbers are not always bad news either. Check these before you worry:

• You checked too early. Mailchimp recommends waiting at least a few hours before reading open rates, because opens keep arriving after the send.
• The email is plain text, or mostly read with images off. Neither produces tracked opens.
• Bot filtering was switched on recently. Your numbers will fall even though nothing changed for real readers.
• The audience changed. A new import, a colder segment or a different sending domain will all move the baseline.

If none of those apply and the drop is real, the most likely cause is that fewer of your emails are reaching the inbox. That is the case worth your time.

Build a baseline instead of chasing an average

The method is the same one we recommend for clicks, applied to opens: take your recent sends of one email type, keep the measurement settings identical, and use the median as your normal. A few open-specific rules make the baseline trustworthy:

• Keep bot filtering in the same state for every campaign you compare, if your platform offers it.
• Read opens at the same point after sending, for example always 48 hours later, so early and late reports are not mixed.
• Separate email types. Welcome emails, order updates, newsletters and promotions behave differently. One blended average hides problems.
• Record a normal range, not only one number. If your last ten newsletters landed between 24% and 31% with a median of 27%, a send at 26% is ordinary; a send at 15% deserves a look. (Those figures are illustrative.)
• Reset the baseline after big list changes, such as a large import or a cleanup of inactive contacts.

When a low open rate is a real problem

Opens are weak evidence of interest but still a useful alarm for delivery. Treat a drop seriously when several of these appear together:

• 1. It is sudden and large compared with your baseline for the same email type, and the audience did not change.
• 2. It is concentrated at one mailbox provider. Split your report by recipient domain. If Gmail addresses fell sharply while other domains held steady, look at Gmail-specific signals rather than your content.
• 3. Clicks fell as well. If opens drop but clicks hold, a measurement change is the likelier cause. If both fall, fewer people are seeing the email.
• 4. Bounces, complaints or unsubscribes rose at the same time.

Then check the delivery basics. For Gmail, Google's email sender guidelines ask senders to keep the spam rate reported in Postmaster Tools below 0.3%; our Google Postmaster Tools checklist shows where to find it, and the spam rate send pause checklist covers what to do before the next send. Confirm SPF, DKIM and DMARC still pass using our DKIM, SPF and DMARC guide. Landing in Gmail's Promotions tab is a different matter from landing in spam; the Gmail Promotions tab guide explains the difference.

How to improve open rate without gaming it

• Be recognisable. Use a consistent from name and sending address that subscribers know.
• Write specific subject lines that match what the email delivers. Our guide to subject lines that get opened has examples, and misleading ones tend to cost you later in complaints.
• Test, but pick winners by clicks. Open-based subject-line tests are distorted by privacy opens. The A/B testing guide explains how to set up a fair test.
• Send to people who still want your email. Segment by recent activity, and run a re-engagement campaign before removing long-inactive contacts.
• Review frequency. Mailchimp notes that, in general, sending more emails reduces engagement per email sent. If open rate slides as frequency rises, test sending less.

Where BestEmail fits

BestEmail's campaign analytics include open and click tracking, bounce and unsubscribe monitoring and per-campaign performance summaries, and subscribers can be organised with tags and segment definitions. That is enough to keep a separate baseline for each email type and audience. Whatever tool you use, label opens as a directional number and put clicks and outcomes first in your reports.

FAQ

Is a 20% open rate good?

It depends on your baseline and your measurement settings. It is below Mailchimp's all-users average of 35.63%, but that average is from December 2023 and includes privacy-related opens. If 20% is normal for your list with bot filtering on and clicks are steady, there is no problem to fix.

Is open rate still worth tracking?

Yes, as a trend and an early warning for delivery problems. It is no longer a reliable measure of whether people read or liked an email, so do not use it alone to judge content.

Why did my open rate jump without any change?

Common causes are more Apple Mail users with privacy protection on, more security scanning on business inboxes, or bot filtering being switched off. Check clicks: if they did not rise too, the jump probably is not real interest.

What open rate should I aim for with a new list?

Avoid fixed targets. Send to a clean, opted-in list, record your first eight to ten campaigns of one type, and use their median as the starting baseline. Then aim to keep it steady while clicks and conversions grow.

Sources

• Mailchimp: Email Marketing Benchmarks & Industry Statistics
• Mailchimp Help: About Open and Click Rates
• Mailchimp Help: Use Open Tracking in Emails
• Mailchimp Help: About Bot Activity and Bot Filtering
• Apple: Mail Privacy Protection & Privacy
• Google Workspace Admin Help: Email sender guidelines