Marketers often judge an email's quality on visuals alone, ignoring the user action that triggered it or technical constraints like image blocking in certain clients (e.g., Outlook), which can render a beautifully designed email blank.
As AI tools perfect written communication, the differentiating skill for marketers will be verbal fluency. Great marketers must practice communicating effectively in live situations without AI assistance, ensuring they don't lose the ability to articulate ideas in person.
Marketers try to replicate web design in emails, but key elements like custom fonts (even Google Fonts in Gmail), GIFs (only the first frame loads in some Outlook versions), and embedded videos are not universally supported, leading to a broken user experience.
Instead of just pushing information, structure event-triggered emails (e.g., after a feature is enabled) to be a two-way communication channel. The first touchpoint should welcome the user, offer resources, and explicitly ask for feedback, creating a valuable loop for product and marketing teams.
Don't let email performance data live in a silo. After measuring meaningful metrics like click-throughs and conversions, proactively share these results internally. This informs sales and customer success teams, enabling them to amplify marketing efforts and understand customer behavior.
When brand teams resist testing simpler, text-based emails, don't argue about aesthetics. Frame the proposal around business value: reduced design and QA time, and the potential for higher conversion rates. Quantify the impact on efficiency and revenue to get buy-in.
In a direct A/B test, simple, text-based automation emails outperformed beautifully designed emails with dynamic content. The text version won on both click-through and conversion rates, proving that simplicity and speed often beat complex visual design in automated flows.
Open rates are unreliable due to automated actions, particularly Apple's Mail Privacy Protection (iOS 15+) which pre-fetches content and marks emails as opened without user interaction. Focus on metrics that reflect true intent, like clicks or conversions influenced by the subject line alone.
For statistically significant A/B test results on major changes like text vs. design, don't rely on a single send. Test within an automated series (e.g., a welcome flow) and collect data for an extended period, like a full quarter, to remove seasonality and ensure a healthy sample size.