For years, I have looked at email performance the same way many marketers do: through content, segmentation, personalization, and subject lines. When a campaign failed, I analyzed the offer, audience segments, and copy. However, I rarely questioned the production process itself.
Later, I realized that many email marketing teams work hard optimizing email content but don’t focus on how much effort it takes to produce that email in the first place. And I don’t mean that a slow production process kills your campaigns. No, most campaigns eventually get sent. But it kills your team’s ability to launch extra campaigns, increase output without increasing headcount, and react to market opportunities while they’re still relevant.
The real bottleneck isn't where most teams think
When marketers talk about email complexity, they usually think about major product launches, seasonal campaigns, or highly customized sends. Such emails receive lots of attention and team resources, but how often do you really send these emails?
Think about something less exciting, like your weekly newsletter, webinar reminder, or product digest. These campaigns look very similar to the ones you sent last week and the week before. That’s where our bottleneck hides. Such routine emails consume a huge amount of production capacity because teams keep rebuilding variations of the same structure over and over again.
I saw this firsthand with one of Stripo’s recurring newsletters. For a long time, it took me 2–2.5 hours to produce a single email. And it wasn’t because of some fancy design, but because most of that time went into assembling familiar layouts, updating content blocks, checking formatting, reviewing links, and making sure everything looked correct.
When I switched to a modular production approach, the same newsletter took roughly 30 minutes. My emails didn’t become “simpler,” and subscribers haven’t noticed any changes. The real difference was that I got 2 extra hours back to spend on other tasks.
I noticed the same sources of production friction in different teams:
- Rebuilding structures that already exist. Product cards, article blocks, banners, CTAs, layouts: These elements have already been designed and approved but continue to be recreated.
- Approval cycles without a clear process. Feedback comes from different stakeholders at different times, which creates extra rounds of revisions.
- Testing. You need to check that every email still works across devices, email clients, dark-mode environments, and mobile screens. Many teams continue to do much of this manually every single time.
According to the State of Email 2026 by Litmus, it takes 3 days for teams to produce an email, depending on the complexity. That’s why I think reuse remains one of the most underrated concepts in email marketing. Take a pre-tested module, update the content, and move forward by stopping spending time on work that has already been done.
What happens when you free up time
Now, we come to the most interesting part: What to do with this “free” time?
- Volume is the most obvious outcome. If a team can make emails faster, it means more campaigns without hiring additional people. And more campaigns mean more opportunities to engage subscribers.
- Timeliness is another piece of the story. A good campaign you sent at the right moment will perform better than a flawless campaign that arrives too late. Teams with slower workflows often respond after the moment has passed.
- Attention quality. When marketers aren’t spending most of their time building emails, they can focus on messaging, audience research, segmentation, and understanding why campaigns perform well or fail.
- I’ve also noticed that production efficiency creates room for ideas that would otherwise never make it into the roadmap. It can be a new layout, a gamified email, or a different content structure. Usually, marketers don’t have time to execute these ideas or even think about them because they spend most of their workday building emails.
Velocity changes how teams experiment
Most marketers agree that testing matters, but it requires bandwidth. An A/B test isn’t a one-time activity: you develop a hypothesis → build the variation → launch the test → analyze the results → create the next hypothesis. Each step requires time, and if it goes into producing regular campaigns, your experimentation will be occasional.
In practice, I’ve seen many teams run 2–3 meaningful tests each month because they simply don’t have enough time left after doing everything else. Teams with mature production workflows often run more experiments during the same period (8–10 tests per month). It’s not like someone’s less ambitious. The issue is the available bandwidth, which determines how quickly a team learns.
I think the biggest gains in email marketing come from running enough experiments to identify what works. The more iterations a team can complete in a quarter, the faster it learns (and the faster its performance improves). That’s why I think about production velocity as the number of learning cycles a team can afford to run.
Why CMOs should pay attention
Most marketing leaders track open rates, click rates, conversions, pipeline contributions, and revenue, while fewer assess how efficiently campaigns are produced. But I think that’s changing, and production velocity is becoming an operational KPI for the email channel because it influences output, experimentation, and responsiveness.
There’s also a technical side to this conversation. Email operations accumulate technical debt just like software products do (outdated templates, manual coding processes, disconnected tools, no reusable module system, no version control: You get the idea). When we look at them separately, these issues seem manageable, but together, they still slow everything down.
For IT leaders and technical architects, this is where the bottleneck becomes structural. If every email requires developer involvement, the production system itself limits the channel. I can say the same about an issue when email tools are disconnected from the ESP and CRM. Every manual handoff, file export, and copy-paste step becomes friction that does not scale as campaign volume grows.
The ROI calculation is straightforward: Take the average number of hours to produce routine emails → multiply it by hourly labor costs → multiply that by monthly email volume → this is the cost of your current production process. Teams work to improve that process or continue paying for inefficiency every month.
We can apply the same logic to content repurposing. When you reuse content smartly, it costs less than creating everything from scratch while still delivering strong results. And it won’t remove creativity from the process; you’ll just stop spending creative energy on repetitive work.
What velocity doesn't solve
Production velocity has limits, and we have to understand them. A faster workflow won’t magically create better content for you. If your email is irrelevant or an offer is weak, operational efficiency won’t change that.
I’m not saying that you should standardize everything. Some campaigns, such as big launches, brand campaigns, and complex interactive experiences, deserve more time and attention, and you should treat them differently. My point is that you should stop rebuilding the predictable work to focus on the work that needs expertise and creativity.
Even in highly customized campaigns, there is usually technical overhead that you can reduce without affecting the quality of the final result (e.g., adding interactive elements without coding them from scratch). Here, operational improvements can make a difference.
The teams that win aren't always the biggest
I believe that successful teams aren’t necessarily the ones with the biggest budgets or the largest creative departments. The real winners are the ones who can always execute, learn, and adapt.
The turning point in my own work didn’t come when I found a better subject line or a new segmentation tactic. Everything changed when I realized how different a team becomes once it spends less time on routine production work. Such teams can test more hypotheses, learn quickly, and react to opportunities in time.
Production velocity isn’t a metric hiding in the depths of an operations dashboard. Try thinking of it as a measure of how much capacity a team has left for the work that moves the results forward.
