How Automated Email Templates Help You Scale Up Your Personalization

June 12, 2019 | 4 minute read
James Glover
President and CEO, Coherent Path
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When you’re marketing to an audience who number in the millions, manual personalization becomes an impossible task. In the past, many businesses tried to ignore this challenge by simply sending identical emails to every subscriber on their list — and racking up numerous unsubscribes as a result.

More recently, organizations have aimed to “split the difference” between mass emailing and personalization by segmenting their subscriber lists. But segmentation requires marketers to manually design multiple versions of entire emails — and that doesn’t scale.  In fact, this time-consuming process often still fails to connect each subscriber with the products they’ll be most likely to purchase.

Even so, every marketer wants to send personalized content to every subscriber. But when subscribers numbers in the millions, the sheer scale of the task demands a qualitatively new approach to email personalization.

That’s exactly the problem that automated email templating solves. Through the power of machine learning, this technology leverages a library of creative content and generates millions of personalized emails — enabling small teams to get maximum impact from their creative assets, and keep serving fresh, engaging content to every subscriber on their lists.

Here’s how it works:

Automated Email Templating Makes It Easy to Achieve Quality Assurance at Scale

The more personalized an email campaign becomes, the more email variants there are. Every one of those emails has to be manually designed and then reviewed by the quality assurance (QA) team — a process that becomes flat-out impossible as the number of recommended variants skyrockets into the millions.

This means marketers are confronted with a seemingly irresolvable tradeoff: either reduce the degree of personalization (and sacrifice engagement as a result) — or hand over control to the machine, and risk sending out nonsensical auto-generated emails that might not accurately reflect the brand’s voice.

However, automated email templating solves the problem behind that problem. In this approach, the creative team designs individual pieces of creative, not entire emails, and stores them in a content library. By campaign, marketers specify which zones of the template should be personalized by the machine. The software then populates those zones with the ideal content for each customer by selecting from the pre-approved creatives in the content library  —  all within your ESP and at the time the campaign is launched.

And since the template and previously used creatives are already approved, the QA team only needs to check new content, vastly reducing the per campaign QA time – all while delivering a wealth of personalized emails to your subscribers.


Templating allows you to support a large number of email variants within a single campaign.


Creating Automated Templates Is a Simple One-Time Process — but Their ROI Keeps Increasing as the Campaign Learns

If your team can code an email in HTML, they can create and customize an automated email template. But whereas a basic email template might pull in a small amount of personalization — say, in the subject line and greeting, for example — automated templates tap into powerful machine-learning logic, which enables them to personalize pre-specified zones throughout the email.

For example, you might specify that the machine shouldn’t feature ads for your autumn wardrobe in emails about your spring fashion sale — or that it should only send recommendations for children’s clothes to customers who actually have children. Staying within the guidelines you’ve provided, the software will crunch the numbers on your latest interactions with each customer, and use that data to generate the most engaging possible emails on the fly.

This templating setup is a simple one-time process. After a quick one-time setup of each template, just specify your own rules for the machine to follow. The sophisticated recommendation engine leverages data from real-world subscriber interactions to assemble fresh, inspiring, personalized emails for every subscriber on your list, any time you choose. And you’ll always be able to create new templates, simply by moving the content blocks around.

And most excitingly of all, the machine will continue to learn from every interaction with your customers — both through email, and through any other touchpoints you connect. That means the software’s recommendations will keep improving over time, delivering even stronger engagement and greater ROI from this one-time setup process.

By solving the problem behind your personalization challenges, automated email templating serves as a force multiplier for your marketing team. This technology saves you the work of designing thousands of emails from scratch, while streamlining your QA process, reducing the risk of human error, and connecting each customer with the content that’ll engage them most strongly — all while staying true to your brand’s voice, without requiring any more time or resources than you’d spend on an ordinary small-scale campaign.

Isn’t it time you scaled up your email sophistication, with automated templates?


Personalization is an important key to crafting an effective email. You also have to make sure that the email is relevant and something the recipient would welcome. Learn more about how by reading “Do More with Email Deliverability and Privacy.”














James Glover

President and CEO, Coherent Path

James Glover is President and CEO of Coherent Path, where he helps retailers transform their email program into a modern data-driven channel focused on revenue. Prior to Coherent Path, James was VP of Sales at Desktone where he was responsible for accelerating customer adoption and revenue growth from zero to over 100 customers to whom he sold through world-class partners like Dell and Time Warner Cable. Before that, James held executive positions at Memento (acquired by Fidelity Information Services) and Watchfire (acquired by IBM). He earned a Bachelor of Commerce degree from the University of Toronto.

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