Email Marketing Metrics Beyond Open Rates
A campaign report can look encouraging while leaving the most important question unanswered. The open rate rose, the click rate held steady, and the email platform marked most messages as delivered. Yet the team still cannot tell whether the message brought people to the action it was meant to prompt. The difficulty is sharper when two campaigns have different audience sizes or when an apparent jump in opens comes from how mail software loads images.
For a marketer deciding what to send next, email marketing metrics are useful only when each number has a clear job. I would read them in a sequence: how many messages reached the platform’s delivered count, how many recipients clicked, how many completed the intended action, and whether sending produced signs of unwanted mail. I would keep opens in the report, but I would not let them decide which campaign won. The cost of this approach is a little more setup: the team must agree on an action, connect its reporting, and keep the same definitions across campaigns.
Start with the action the email was meant to produce
Before looking at rates, name the result. A product announcement may aim to bring people to a feature page; an invitation may aim for registrations; a sales email may aim for purchases. These are examples of campaign goals, not interchangeable definitions of success. If the goal is registration, a click to the registration page is a step toward it, while a completed registration is the outcome. A campaign with more clicks can still produce fewer registrations than a campaign with fewer, better matched clicks.
That distinction determines what deserves the top line of a report. For a campaign with a measurable website or app action, I would put the completed action beside the delivered and click counts. Google Analytics calls an event that measures an action particularly important to a business a key event; an organization can mark a collected event as a key event and report how often users trigger it. The organization chooses which action matters. Google Analytics explains key events here.
The choice has to be specific enough to survive a campaign review. “Engagement” cannot tell the team whether an invitation worked. “Completed event registration” can. If a purchase is the intended action, report purchases rather than treating a product-page visit as the final result. When the action happens away from the email platform, the team also needs a workable connection between the email click and the action. Without that connection, the platform can report interest in a link, but the campaign’s contribution to the later action remains uncertain.
A simple illustrative case shows why the distinction matters. Suppose Campaign A has 10,000 delivered messages, 400 recipients with a recorded click, and 20 completed registrations. Campaign B has 5,000 delivered messages, 250 recipients with a recorded click, and 30 registrations. A produced more clicks in absolute terms, but B produced more registrations from half as many delivered messages. Those figures are invented solely to demonstrate the calculation; neither campaign establishes a general benchmark. If the team’s purpose was registrations, I would examine B’s offer and audience fit before celebrating A’s larger click count.
Keep the denominator beside every rate
An email rate is a fraction, so its denominator determines what the number means. Mailchimp describes its open rate as the share of successfully delivered messages registered as opened and its click rate as the share of delivered messages with at least one click. That makes delivered messages a practical common denominator for comparing these two rates within that reporting system. Mailchimp defines both rates and their tracking.
Use the illustrative campaigns again. Campaign A’s 400 clickers among 10,000 delivered messages yield a 4% click rate. Campaign B’s 250 clickers among 5,000 delivered messages yield a 5% click rate. A delivered more total clickers because it had twice the delivered volume; B persuaded a larger share of its delivered audience to click. Those are different statements, and both can matter. If a report shows only percentages, it hides scale. If it shows only totals, it hides the different-sized opportunity each campaign had.
I would display the numerator and denominator together: “400 recipients clicked / 10,000 delivered (4%).” Then I would add the action count with a clearly named basis, such as “20 registrations / 10,000 delivered (0.2%).” The latter is a reporting choice for the illustrative case, not a universal platform metric. It lets a reader follow the sequence from delivered message to recorded click to completed action without silently changing populations halfway through.
This is also why I would resist placing “clicks per open” at the center of a comparison. Dividing clicks by recorded opens may appear to isolate how persuasive the body was, but an unreliable open count gives the resulting ratio an unreliable denominator. Mailchimp says Apple Mail Privacy Protection can distort “clicks per unique open” in its reports. Its explanation of Apple Mail Privacy Protection describes that effect. A click rate based on delivered messages still has tracking limitations, but it avoids building the headline measure on an open count known to be affected by remote-content loading.
Keep the reporting period and audience visible as well. A rate calculated from one campaign should not quietly be compared with a total from several campaigns, or with a segment whose membership changed. The arithmetic might be correct while the comparison answers the wrong question. If the team changes the offer, audience, and send conditions at the same time, even a large difference in click rate cannot isolate which change mattered. For a decision about copy, compare campaigns with sufficiently similar audiences and goals, and describe the other differences rather than assigning all the credit to a subject line or button.
Treat opens as a signal with a known blind spot
An open is tempting because it appears to sit at the start of the reader’s journey. In Mailchimp’s tracking, a tiny image is included in a message, and a download of that image can register an open. If images are turned off, an actual read may go unrecorded; Mailchimp also factors clicks into its open reporting when the tracking image has not loaded. Mailchimp describes how its open tracking works. An open rate therefore measures the platform’s observed events under its rules, not a direct count of humans who read the message.
Privacy settings can push the error the other way. Apple says Protect Mail Activity downloads remote email content in the background by default, regardless of whether a person engages with the message. Apple describes that behavior in its Mail privacy documentation. Mailchimp says that, for contacts using Apple Mail with the feature enabled, preloaded tracking pixels can make messages appear opened without the contact opening them, inflating reported open rates. Mailchimp details the reporting impact.
The practical choice is to use opens as a limited clue, especially when checking whether a message’s subject or audience deserves another look, and to avoid treating a change in open rate as proof that more people paid attention. I would not choose the winning subject line of a consequential campaign solely by tracked opens if the reporting system includes privacy-preloaded events. A click or the intended action is closer to the behavior the campaign was designed to create. Mailchimp itself warns that tests based on opens may be inaccurate under Apple Mail Privacy Protection and suggests using click rates instead. Its Apple Mail Privacy Protection guidance covers tests and automated messages.
The same caution applies to rules that act on the metric. A “resend to people who did not open” group can miss people whose mail software fetched the image without a human reading the email. An automation triggered by an apparent open can also fire for a larger group than intended. If the business needs a resend or follow-up rule, I would first ask which observable action makes the next message relevant. A recorded click or purchase may be a better trigger for some campaigns, though no single trigger fits every purpose. Mailchimp describes these open-based effects and suggests considering clicks or purchases for relevant automation criteria. See its guidance on open-based segments and flows.
Separate message response from delivery conditions
A weak click rate is not automatically a copy problem. The message may have reached fewer intended recipients, reached a different audience, or faced recipient feedback that affects future delivery. Gmail’s sender guidelines describe authentication, subscription practices, spam feedback, and message handling as parts of successful sending to personal Gmail accounts. They also say Google cannot verify third-party open rates and that a low open rate alone does not necessarily indicate a delivery or spam-classification problem. Gmail’s sender guidelines make these distinctions.
I would therefore put delivery and recipient feedback beside engagement in a campaign review. Record how many messages were attempted and how many the sending platform reports as delivered, then note rejected or bounced messages under that platform’s definitions. Watch the recipient complaints and unsubscribe signals the available systems provide. The point is not to blend them into one quality score. Each points to a different decision: a sending problem, an audience or permission problem, or a message that failed to draw the intended response.
If delivery worsens sharply while click behavior among delivered messages appears stable, editing the call to action is unlikely to address the first problem. I would check the sending setup and recipient feedback before another large send. Gmail says senders should follow its authentication and subscription requirements, monitor spam rates, and send to people who want the messages; it warns that repeated spam reports can harm a domain’s reputation. Gmail sets out those sender practices. The exact remedial step depends on what the sending and recipient reports show, not on the open rate alone.
The reverse pattern suggests a different investigation. If the platform reports a similar delivered share but fewer recorded clicks for a comparable audience, examine whether the email’s promise, content, and destination match the audience’s reason for subscribing. The first useful change may be a clearer offer or a more relevant segment. Mailchimp notes that click rates reflect broad trends and recommends testing content, links, and audience targeting to improve response. Its open and click guidance discusses those choices. I would make one meaningful change at a time when possible, so the next report has a better chance of explaining the result.
Follow clicks to outcomes without overclaiming credit
A click tells the team that a tracked link was used. It does not, by itself, tell the team what happened after the visitor arrived. For campaigns where the business action occurs on a website or app, the next useful comparison is between email clicks and the selected key event. Google Analytics lets organizations mark important actions as key events and report counts across channels. Its attribution reports can distribute credit among different touchpoints on a person’s path, and different attribution models can distribute that credit differently. Google Analytics explains key events and attribution.
That matters when a recipient clicks an email, returns later by another route, and then completes the action. A report that assigns all credit to email and a report that shares credit across touchpoints may give different answers about the same path. I would specify the key event and the attribution view before comparing campaigns. Otherwise, a movement in “email conversions” could reflect a changed credit rule as much as a changed campaign. If the team cannot connect the email click to the later action, report the click and the action separately; do not imply that every later action was caused by the email.
For the illustrative registration campaigns, the next question after B’s higher registration count is whether the registrations are the outcome the organization actually needed. If the invitation’s purpose was attendance, registration is still an intermediate step. The campaign report should stop where observation stops and name the next fact needed to judge the result. This prevents a neat dashboard from turning a convenient event into the business objective by default.
Make one campaign report answer the next decision
A useful campaign review can fit on one page. Put the objective in a sentence. Show attempted and delivered counts under the platform’s definitions, the number and share of delivered messages with a recorded click, and the count of the intended action under a named reporting rule. Put opens in a secondary position with a note about image and privacy effects. Add the available bounce, unsubscribe, and complaint information, then write one decision: repeat the campaign, change its audience or offer, fix a sending issue, or gather the missing outcome data.
For example, if an event email drew clicks but few completed registrations, I would inspect the path from the email promise to the registration action before trying another subject line. If the delivered count fell and recipient complaints rose, I would address sending and list practices before judging the creative work. If registrations improved while opens fell, I would keep the outcome in view rather than declaring the campaign a failure on the weakest metric. Each call follows the part of the sequence that changed, while leaving room for facts the report cannot establish.
The strongest email marketing metric is therefore not a universal percentage. It is the count or rate that matches the campaign’s intended action, read alongside the delivered audience and the steps leading to that action. Opens can help frame a question, clicks show a more deliberate response, and key events show whether the chosen action occurred. Delivery and feedback tell the team whether it can keep reaching the audience. Read together, those measures make the next send a decision rather than a reaction to the largest number on the dashboard.