When I joined the team, email wasn’t broken, but it was quietly draining a lot of energy.

Requests came from everywhere. Product updates, compliance notifications, internal announcements, one-off customer communications. None of them were wrong, and all of them were “urgent” in their own way. The problem was that there was no shared definition of what a proper email request looked like, no consistent data standard, and no clear process from request to delivery. Most conversations happened in long email threads, looping in more and more people over time. Decisions were made, revisited, approved again, and sometimes reversed. The work got done, but at a cost: attention, time, and focus.

I realized pretty quickly that email itself wasn’t the problem. The lack of a process was.

One of the first things I did was separate email into two very different categories. On one side were one-off requests—product announcements, compliance notices, internal communications. These weren’t about optimization or performance; they were about accuracy, coordination, and getting the message out correctly. On the other side were ongoing email cadences tied to users, prospects, or customers. These were living systems that needed constant measurement and iteration. Treating both the same way was creating confusion and unnecessary work.

For ad hoc email requests, the priority became standardization. Every request needed to come with a clear data structure. Beyond email addresses, I required fields like first name, last name, source, and any attributes needed for dynamic content. I created a simple template with fixed naming conventions so everyone was speaking the same language before work even started. This alone eliminated a surprising amount of back-and-forth.

Data quality was non-negotiable. Before any list was uploaded into Mailchimp or HubSpot, it went through deliverability checks using tools like NeverBounce. Past experience had taught me that bad data doesn’t just hurt one campaign—it damages sender reputation over time. On top of that, I used AI-assisted validation to scan for formatting issues, missing fields, or obvious inconsistencies before anything went live. It wasn’t about being perfectionist; it was about protecting the system.

Once content was ready, the workflow became predictable. Drafts were reviewed internally for copy and design, test emails were sent, and only then were stakeholders asked for final approval. After launch, I always followed up within 24 hours with a short performance snapshot—delivery rate, open rate, early signals—and, when relevant, suggestions for next steps. Over time, this closed the loop and set expectations that email didn’t end at “send.”

As volume increased, email threads became the next bottleneck. That’s when we moved requests into a simple Asana request board. Instead of endless email chains, teams submitted requests through a form with required fields. We could see everything in one pipeline, understand priorities, and even forecast upcoming workload. It didn’t just make execution smoother; it made planning possible.

Email cadences were handled very differently. These were long-running programs, so performance mattered. We tracked open rates and click-through rates consistently and used the lowest-performing emails as starting points for optimization. If an email fell below a reasonable open-rate threshold, it became a candidate for A/B testing. Subject lines were adjusted first, then content. Nothing fancy, just disciplined iteration over time. Improvements were incremental, but they compounded.

What mattered most to me wasn’t the tools—Mailchimp, HubSpot, validation software, or AI helpers—but the way they fit together into a system that reduced friction. The goal was always the same: remove repetitive decisions, reduce cognitive load, and let the team focus on work that actually required human judgment.

Looking back, this project wasn’t really about email. It was about turning a noisy, reactive process into something calm and predictable. Once that happened, email stopped being a source of stress and became part of the normal rhythm of marketing operations. And that shift—quiet, structural, and easy to miss from the outside—is usually where the real impact is.