Good Morning {{first_name}}!

Malene here.

This week, we are having the conversation that every email marketer needs to have with their dashboard and then never look away from. Open rates are lying to you. Not maliciously, but consistently.

Thanks to Apple Mail Privacy Protection, inbox pre-loading, and bot activity, a significant portion of what your platform is calling "opens" is inbox technology doing its thing while your subscriber is still making coffee. And yet, open rate is still the first metric most teams report on, celebrate, and optimize for.

We are going to fix that today. We are going to talk about what buyer intent actually looks like in email data, where it shows up, and how to build your CRM measurement framework around signals that require a human decision rather than a pixel preload. No vanity metrics. Just intent.

Let’s dive in.

Apple's Mail Privacy Protection, which launched in 2021 and has been expanding its reach since, pre-fetches email content, including open-tracking pixels, regardless of whether the subscriber actually opened the email. Microsoft and other providers have followed with similar behaviour.

The result is that open rates across most email programmes are inflated to a degree that makes them unreliable as an intent signal. Fifty large US retailers sent nearly 42 billion emails over Black Friday and Cyber Monday in recent years, many embedded with tracking mechanisms that were already measuring phantom opens.

Your open rate feels reassuring. It is frequently a story your inbox technology is telling you about itself.

Here is the specific damage that open rate obsession causes inside a CRM. When open rate is the primary success metric, the team optimizes for subject lines. Subject line optimization improves at making people curious enough to trigger a preload or a glance, which is not the same thing as making people interested enough to act. The downstream behaviour, clicks, conversions, and revenue per email, stays flat or declines because the content and the offer were never the focus. The subject line was.

Meanwhile, the CRM is accumulating "engaged" contact records based on open data that does not reflect genuine interest. Segments built on open behaviour include large numbers of contacts who have never made a deliberate choice to interact with your emails. Lifecycle automations trigger off these signals and fire into a population that looks engaged on paper but is not moving toward purchase. The reporting dashboard becomes, as one version of this problem put it, a bedtime story rather than a business tool.

Acquisition fills the bucket. But a measurement framework built on inflated open data cannot tell you which contacts are actually moving toward retention and which ones are quietly disengaging. You cannot fix a leak you cannot see.

The distinction that matters here is between passive exposure and intentional engagement. An open, real or pre-loaded requires nothing from the subscriber. A click requires a decision. A conversion requires multiple decisions. Revenue per email requires an actual transaction. These are the metrics that reflect what is actually happening in your subscribers' minds, and they are the ones your CRM should be built around.

CLICK-TO-OPEN RATE IS YOUR FIRST REAL SIGNAL: Click-to-open rate, which is the ratio of clicks to actual human opens, strips out the preload noise and tells you what percentage of people who genuinely engaged with the email found the content compelling enough to act on. A high open rate with a low click-to-open rate is a sign that your subject lines are working, but your content or offer is not landing. That is a useful diagnosis. A flat open rate with a strong click-to-open rate tells you the opposite. CTOR gives you a signal about content quality that raw open rate cannot.

REPEAT CLICK BEHAVIOUR IS YOUR STRONGEST INTENT SIGNAL: Segments built around subscribers who click repeatedly and across multiple emails consistently outperform segments built on opens alone. A subscriber who has clicked three times in the last 30 days has demonstrated a pattern of intentional engagement. That pattern is a buyer signal. It belongs in your CRM as a tag or segment, and the next email that person receives should reflect what they have been clicking on, not what the general list is getting. Behavioural segmentation built on click patterns is one of the highest-return CRM investments an SMB marketing team can make.

REVENUE PER EMAIL AND REVENUE PER SUBSCRIBER ARE THE METRICS THAT CLOSE THE LOOP: Open rate tells you nothing about money. Revenue per email and revenue per subscriber tell you almost everything that matters for business decisions. These metrics require accurate attribution tracking to work properly, which is a setup investment worth making. Once you can see which emails in your lifecycle are directly correlating with transactions, you can allocate creative effort, budget, and sequencing decisions based on what is actually generating revenue rather than what is generating the most comfortable-looking dashboard numbers.

WHERE TO USE OPEN RATES LEGITIMATELY: Open rates are not entirely useless. They are a reasonable signal for subject line and sender name testing, and they can function as a rough indicator of brand health over time when tracked as a trend rather than an absolute number. If your open rate is declining steadily over six months, something is changing in how your audience perceives your emails, even accounting for privacy noise. Use open rates as a directional indicator of brand intrigue, not as evidence of intent or engagement.

Pull your current email performance report and identify which metrics are doing the most work in your decision-making. If open rate is at the top, move it to the bottom or remove it from the primary view entirely.

Rebuild the report with click-through rate, click-to-open rate, conversion rate, and revenue per email as the headline numbers. If you do not have revenue attribution set up yet, start with CTOR and conversion rate and build from there. Then look at your top-performing emails under this new framework and compare them to your top-performing emails by open rate.

The two lists will likely not match, and the gap between them is where your measurement framework has been misleading your strategy.

Buyer intent shows up when subscribers make choices, not when inbox technology preloads a pixel. The teams that build their CRM measurement frameworks around action-based signals, clicks, conversions, revenue, and downstream behaviour are the ones who can actually see which contacts are moving toward a purchase and which ones are drifting.

That visibility is the foundation of every retention strategy worth building. Stop measuring what flatters your dashboard. Start measuring what reflects a human decision. The two are not the same thing, and your programme's performance depends on knowing the difference.