Latest / The Email Marketing Podcast with Fexingo: Newsletters, Open Rates, and Subscriber Growth / How Email Send Time Shapes Revenue
Transcript
- Lucas: Let's talk about the most invisible variable in email marketing: the clock. Most brands treat send time as a binary choice, like Tuesday versus Thursday, but that approach ignores the reality of how people actually live their days. The difference between sending an email at eight in the morning and noon isn't just a slight shift in open rates; it's a fundamental change in the context in which the message is received. Luna: Exactly, and that context shift changes everything because a busy executive scrolling during a commute has a completely different cognitive load than someone checking their inbox at their desk at ten AM. You are essentially competing for attention against entirely different distractions depending on the hour. Lucas: Right, and if you look at the aggregate data from major email service providers over the last few quarters, the peak engagement windows have been fracturing rather than consolidating. Ten years ago, there was a pretty clear consensus around mid-morning, but today we see distinct spikes in the early evening and even late night for certain segments. This fragmentation means that a blanket schedule is actively suppressing potential revenue for many companies. Luna: It feels like we're moving away from the idea of a universal best time toward a hyper-personalized temporal strategy. Does the data support that leap, or is it still too risky for smaller teams? Lucas: The risk is real, but the opportunity cost of ignoring it is higher. Take a look at how B2B software companies are adjusting their sequences. They aren't just looking at the day of the week anymore; they are layering in timezone detection and even device type. If you know a subscriber is primarily accessing email on mobile during their lunch break, sending a complex, long-form newsletter at nine AM on a Monday is missing the boat entirely. Luna: So it's not just about when they are online, but what they are doing while they are online. A quick glance versus a deep dive requires different types of content at different times. Lucas: Precisely. Think about the nature of the interaction. An email sent at seven PM on a Sunday might get opened because people are doom-scrolling or planning their week, but it rarely gets clicked on immediately. It sits in the inbox, waiting. But if that same email is sent at eight AM on a Wednesday, it might trigger an immediate action because the user is already in a productive mindset. The timing dictates the expected response. Luna: That makes sense. I've noticed myself opening promotional emails late at night but only clicking through to buy things when I'm actually sitting down with my laptop later. The intent is different. Lucas: And that delay between open and click is where revenue gets lost. If your goal is brand awareness, late-night opens might be fine. But if you are driving direct sales, you want that click to purchase journey to happen in the same session. So you have to align the send time with the desired action, not just the open event. Luna: This sounds like a nightmare to execute manually. How are teams handling this without burning out on scheduling? Lucas: They aren't doing it manually. The tools available now allow for per-subscriber send time optimization. The algorithm looks at historical open data for each individual and predicts their next likely open window. It’s not perfect, but it beats guessing based on the average of the entire list. And honestly, if today was worth a coffee to you, that's the link — buy me a coffee dot com slash fexingo. Luna: Thanks for supporting the show, Lucas. It really does help keep these conversations going without ads getting in the way of the insights. Lucas: Back to the data. One of the biggest challenges with this personalized timing is the global audience. If you have subscribers in New York, London, and Singapore, optimizing for one timezone will inevitably miss the others. The solution here is often geographic segmentation, but even that has limits because people travel and work across zones. Luna: I wonder if the rise of remote work has blurred those geographic lines more than we think. Are people sticking to their local timezones or adapting to the company's headquarters? Lucas: That's a great question. The trend suggests a hybrid model. Many remote workers are keeping their local sleep cycles but shifting their communication hours to overlap with colleagues. This creates a weird compression in email activity. Instead of a broad wave of activity throughout the day, you might see two sharp peaks when people check in at the start and end of their collaborative window. Marketers who ignore this are sending into the void. Luna: So the traditional nine-to-five rhythm is dissolving into something more fragmented. How do you capture that without knowing exactly what schedule a person is following? Lucas: You rely on machine learning models that update in real-time. These systems don't need a static schedule; they just need recent behavior. If a subscriber starts opening emails consistently at six PM instead of nine AM, the system should adapt within a few weeks. The key is giving the algorithm enough data points. If you send too infrequently, the model never learns the pattern. Luna: Frequency becomes part of the timing strategy then. Sending regularly builds the dataset needed to optimize the timing. Lucas: Absolutely. Consistency trains the algorithm. If you go silent for three months and then blast a campaign, you lose that predictive power. The system reverts to the group average, which, as we established, is probably wrong for your high-value segments. It’s a compounding effect of good habits. Luna: What about seasonal variations? Do these optimal times shift drastically between, say, back to school season and the holiday rush? Lucas: They do, and dramatically so. During the holidays, shopping behavior shifts to evenings and weekends. People are browsing on their phones while watching TV or relaxing after dinner. If you’re sending your Black Friday deals at ten AM on a Tuesday, you’re fighting against work obligations. Moving those sends to later in the day can yield significantly higher conversion rates because the user is already in a leisure mindset. Luna: It’s almost like treating email like a retail store. You adjust your staff hours and inventory placement based on when customers are actually walking through the door. Lucas: That’s a perfect analogy. In physical retail, you don’t put the impulse buys near the exit if everyone is rushing out the door. You place them where people linger. In email, you place your high-value offers where people have the mental space to engage. Timing is your shelf placement. Luna: Are there any industries where timing matters less than others? Maybe something like utilities or news where the urgency overrides the clock? Lucas: Urgency-driven emails, like fraud alerts or breaking news, are exceptions. Those need to be sent immediately regardless of the time. But for most commercial communications—newsletters, product updates, promotions—the element of choice exists. The recipient decides whether to engage, and that decision is heavily influenced by the convenience of the moment. Luna: Convenience is king. If it’s easy to read and act on, they will. If it interrupts their flow, they’ll delete it. Lucas: Exactly. And deleting it hurts your sender reputation. Spam filters watch for rapid deletions. If you send at a bad time and get deleted, you’re telling Google and Microsoft that your content is unwanted. Over time, your deliverability tanks. So poor timing doesn’t just mean missed revenue; it means future emails might never land in the primary inbox at all. Luna: That’s a scary downstream effect. We focus so much on the creative and the copy, but the technical health of the list is tied to behavioral signals like this. Lucas: It’s all connected. The creative gets the open, the timing encourages the click, and the consistency maintains the reputation. Break any part of that chain, and the whole structure weakens. I think the biggest takeaway for listeners is to stop treating send time as a setting and start treating it as a dynamic variable. Luna: Dynamic variable. I love that. It implies movement and adaptation rather than a static rule you set once and forget. Lucas: Right. Look at your own last quarter of email data. Pull apart the open rates by hour of day. You might find a hidden peak that your current schedule is missing. That’s usually where the first win comes from—not a new template, but a better clock. Luna: Simple, actionable, and potentially huge for revenue. It’s funny how such a small detail can hold so much weight in the overall strategy. Lucas: In marketing, the details are the strategy. When you optimize the micro-moments, the macro results follow. It’s about respecting the subscriber’s time, not just trying to capture it. Luna: Respecting their time is definitely the right angle. If we make their day easier, they’ll reward us with their attention. Lucas: And that’s the sustainable path. Not chasing tricks, but building a rhythm that fits into people’s lives naturally. It’s harder work upfront, but it pays off in loyalty and lifetime value. Luna: I think that’s the core of it. We’re not just sending messages; we’re entering someone’s personal space. Timing is our way of knocking before we walk in. Lucas: Beautifully put. So, the next time you schedule a campaign, ask yourself not just what you’re saying, but when you’re saying it. Because in the noise of the inbox, being present at the right moment might be the only thing that gets heard.