Email marketing benchmarks: open rates and click rates by industry, and how to read them

Three email providers publish industry benchmarks from their own customer data, and their overall figures are far apart. Campaign Monitor's benchmarks report, based on over 100 billion emails sent across its platforms in 2021, gives an average open rate of 21.5 percent, a click through rate of 2.3 percent and a click to open rate of 10.5 percent. Mailchimp's benchmarks page, with figures the page states are based on data as of December 2023, gives an all users average of 35.63 percent open and 2.62 percent click. GetResponse, analysing more than 4.4 billion messages sent by its customers in 2023, gives 39.64 percent open, 3.25 percent click through and 8.62 percent click to open. All three are accurately reported. They differ because each measures a different population of senders in a different year, and because open tracking itself changed in September 2021. So use them for direction, and judge your programme against your own trailing numbers, computed the way this page sets out.

This page covers the published benchmarks and the method for reading your own. For deliverability, list health and the flows behind the numbers, see email marketing.

What each named source published

Source	Data year	Sample stated on the page	Open	Click	Click to open	Unsubscribe
Campaign Monitor benchmarks	2021	Over 100 billion emails across its platforms	21.5%	2.3%	10.5%	0.1%
Mailchimp benchmarks	As of December 2023	Campaigns sent to at least 1,000 subscribers	35.63%	2.62%	Not published	0.22%
GetResponse benchmarks	2023	More than 4.4 billion messages from its customers	39.64%	3.25%	8.62%	0.15%

By industry, as published

From Mailchimp's industry table, figures as of December 2023:

• Non profits: 40.04 percent open, 3.27 percent click, 0.18 percent unsubscribe
• Education and training: 35.64 percent open, 3.02 percent click, 0.18 percent unsubscribe
• Business and finance: 31.35 percent open, 2.78 percent click, 0.15 percent unsubscribe
• Ecommerce: 29.81 percent open, 1.74 percent click, 0.19 percent unsubscribe

From GetResponse's 2023 industry table:

• Legal services: 47.26 percent open, 12.11 percent click through, 25.63 percent click to open
• Technology and high tech: 44.72 percent open, 7.40 percent click through, 16.54 percent click to open
• Retail: 41.77 percent open, 5.10 percent click through, 12.22 percent click to open
• Health and beauty: 38.16 percent open, 2.14 percent click through, 5.62 percent click to open
• Travel: 32.83 percent open, 2.52 percent click through, 7.69 percent click to open

From Campaign Monitor's 2021 industry table:

• Education: 28.5 percent open, 4.4 percent click, 15.7 percent click to open
• Nonprofit: 26.6 percent open, 2.7 percent click, 10.2 percent click to open
• Advertising and marketing: 20.5 percent open, 1.8 percent click, 9.0 percent click to open
• Retail: 17.1 percent open, 0.7 percent click, 5.8 percent click to open

Retail sits at 41.77 percent open in one table and 17.1 percent in another. That gap is the most useful thing on this page, because it tells you what a borrowed benchmark is worth as a target.

Why the figures differ by this much

• Different senders. Each provider measures its own customers. The mix of company sizes, list building habits and send frequency is different in each population.
• Different inclusion rules. Mailchimp's page states it counted campaigns sent to at least 1,000 subscribers. GetResponse states it limited the analysis to active senders with at least 500 contacts. A threshold change moves an average.
• Different years. Campaign Monitor's figures are 2021, the other two are 2023.
• Open tracking changed. Apple's Mail Privacy Protection, which Campaign Monitor's page dates to September 2021, pre fetches images, which registers opens that no human performed. Both Campaign Monitor and Mailchimp flag this on their pages. It inflates open rates, and it inflates them unevenly depending on how much of your list reads mail on Apple devices.

The practical consequence is simple. Treat open rate as a directional signal, and make click rate, click to open rate and revenue per recipient the numbers you manage on.

Compute your own, and compare to your own

Use the delivered count as the denominator, not the sent count. These are the five definitions worth standardising inside your team:

Metric	Formula
Delivered	sent minus bounces
Open rate	unique opens divided by delivered
Click through rate	unique clicks divided by delivered
Click to open rate	unique clicks divided by unique opens
Unsubscribe rate	unsubscribes divided by delivered
Bounce rate	bounces divided by sent

Export your last fifty campaigns and compute your own distribution. The median and quartiles of your own programme are a better target than any published average:

// benchmark.js, run: node benchmark.js campaigns.csv
// columns: name,sent,bounces,unique_opens,unique_clicks,unsubscribes
const fs = require('fs');

const rows = fs.readFileSync(process.argv[2], 'utf8')
  .split(/\r?\n/)
  .slice(1)
  .filter(Boolean)
  .map(function (line) {
    const c = line.split(',');
    const sent = Number(c[1]);
    const bounces = Number(c[2]);
    const opens = Number(c[3]);
    const clicks = Number(c[4]);
    const unsubs = Number(c[5]);
    const delivered = sent - bounces;
    return {
      name: c[0],
      openRate:   delivered ? opens / delivered : 0,
      clickRate:  delivered ? clicks / delivered : 0,
      ctor:       opens ? clicks / opens : 0,
      unsubRate:  delivered ? unsubs / delivered : 0,
      bounceRate: sent ? bounces / sent : 0
    };
  });

function percentile(values, p) {
  const sorted = values.slice().sort(function (a, b) { return a - b; });
  return sorted[Math.floor((sorted.length - 1) * p)];
}

['openRate', 'clickRate', 'ctor', 'unsubRate', 'bounceRate'].forEach(function (key) {
  const values = rows.map(function (r) { return r[key]; });
  console.log(
    key.padEnd(11),
    'p25 ' + (percentile(values, 0.25) * 100).toFixed(2) + '%',
    'median ' + (percentile(values, 0.50) * 100).toFixed(2) + '%',
    'p75 ' + (percentile(values, 0.75) * 100).toFixed(2) + '%'
  );
});

Run it monthly. A campaign below your own twenty fifth percentile is the one to examine; a campaign above your seventy fifth percentile is the one to copy. That comparison holds no matter what any provider publishes.

What to change when each number is low

Number	What it points at	First change
Open rate low	Sender reputation, subject line, send time, list age	Authenticate the domain, then test subject lines on a stable segment
Click to open low	The email body is not matching the promise in the subject	One offer, one clear link, shorter copy
Click rate low but click to open healthy	Too few people are opening at all	Work on deliverability and segmentation, not the body
Unsubscribe rate rising	Frequency or relevance	Segment by engagement and reduce sends to the cold group
Bounce rate above a couple of percent	List hygiene	Remove hard bounces immediately, re verify old imports

What people ask about email marketing benchmarks

What is a good open rate for email marketing?

The published averages span roughly 21 percent to 40 percent across the three sources above, for the years each one names. Use your own trailing median as the target, and treat any single open figure as directional given that Apple's Mail Privacy Protection registers opens automatically.

What is a good click rate for email marketing?

Campaign Monitor reported 2.3 percent for 2021, Mailchimp 2.62 percent as of December 2023, and GetResponse 3.25 percent for 2023. Compute your own median across the last fifty sends and manage the gap between your best and worst quartile, which is the part you control.

Which metric should a team report monthly?

Click through rate, click to open rate, unsubscribe rate and revenue per recipient. Open rate belongs in the pack as context rather than as the headline.

Why is my open rate higher than it used to be?

Image pre fetching by privacy features registers opens without a human reading the message, and the share of your list on those clients sets how much it lifts the figure. Compare year on year against your own data and lead with clicks.

How many campaigns do I need before my own benchmark means anything?

Enough that one send cannot move the median. Around thirty comparable campaigns gives a usable distribution, and reporting the count beside the median keeps everybody honest.

Should I compare against my industry or my own history?

Both, in that order of effort. Spend ten minutes on the industry figure for context and the rest of the time on your own quartiles, because that is the comparison that tells you which email to send next.

A second channel to benchmark the same way

This page told you to compute your own numbers rather than borrow an industry figure. Apply that to a channel with no published benchmark at all: how often an assistant names you when a buyer asks.

Choose ten questions, ask them in three assistants, and count the mentions out of thirty. That is your baseline. Repeat monthly and compare yourself to yourself, exactly as with open rates. Nobody else's average will tell you much here. AI Knows Us keeps the counts, the competitors named and the sources, so the trend becomes a table.