This article features content from Revolution 2017. Join us for in London March 2020 for our next event. Interested in learning more? Click here.

We thank Matt Hayes, CEO of Emarsys partner Kickdynamic, for writing and contributing this guest post.

There is no doubt that artificial intelligence will become an essential tool for marketers to achieve better personalization.

Its correct use will allow automation of repetitive manual tasks that are still taking valuable time and resources that could be better spent developing strategy.

It will allow automation and scaling of personalized marketing that, today, is still very much ‘one-size-fits-all.’

At Emarsys Revolution 2017 in Berlin, I spoke about the value of Open Time Content — the ability to send emails with content that populates in real-time, each time the email is opened.

I define real-time personalization as the ability to automatically change email content to match each individual’s behavior, preferences, and within the context of their stage of the buyer journey.

That being said, AI is generally not being used in marketing campaigns today.

How come?

Email marketing teams are still facing major hurdles in using customer data, personalizing content, and scaling their marketing for individual experiences. Let’s look at each of these and how they might be improved upon in 2018 to move closer towards personalization at scale.

How to Use Customer Data for Email Personalization

More data is being generated at a higher rate than ever before, and it’s only increasing. You’re likely collecting more and more data on each customer — or at least have the ability to do so.

However, in most cases, the data is not “email-ready.” It’s not in a state that can be used for email personalization. Correct data is not tracked, or may not be available in your Email Service Provider.

To be able to use customer data in an effective way to create more personalized content, it needs to be at the core of your email marketing setup — it must be a part of the strategy.

You may be asking “what data do I have?” “How do I use it?” “How will it update when a customer’s preferences change?” A lot of that has to do with how the data was collected.

How data is collected

The value, accuracy, and usability of your customer data depends a lot upon how it was gathered. Data will be more accurate, for instance, if you collect it using self-select opt-ins like subscriptions or registrations which promise ongoing value.

Here is a three-tiered approach to thinking about customer data:

  • Preference: self-selected data via a preference center — this can include preference brand or design, for example.
  • Previous email behavior: clicks and opens — when and where customers have clicked on previous email campaigns and links.
  • Previous website behavior: browsed or purchased — when and where customers have been browsing your website.

Example: Staples

For an example of a “daily deal,” Staples has completely automated this process. Its email marketing team hasn’t touched this campaign since setting it up six months ago as the system takes care of everything, constantly switching out the deal and the content:

daily deal

Types of data, sector-dependent

Certain types of data will tell you more about a customer than other types.

  • Category
  • Brand
  • Gender
  • Average order value (AOV)

Based on the aforementioned types of customer data, you’ll be able to use machine learning technology to take action and use the data in the following ways.

  • Product recommendations — based on previous browse/purchase behavior
  • Propensity to purchase — the likelihood of purchase based on identified patterns in past purchases

Personalizing Email Content for Individuals

How are you supposed to show millions of individual customers millions of content variations — all based on their preferences, behavior, or propensity to purchase?

If the goal is true one-to-one personalization, with each customer receiving content that is unique to them, then you must be able to produce unique and dynamic content in the email for each individual.

You can’t, of course, manually create emails that are unique to each individual. Yet content has to appear as if it were written this way. It must be intelligently delivered too, based on an understanding of a customer’s context — and thus, must be able change depending on what is happening at that moment.

At Kickdynamic, we believe this is one of the most important aspects that will determine successful uses of AI technology and achieving personalization. Using AI technology will not work unless you solve this first.

Scaling Email Personalization

The term “scale” is thrown about a lot. What exactly is scale?

It’s the ability to customize an email to every individual, in every email sent — not just one-offs, or to two or three segments.

A very practical example would be in a business as usual (BAU) email. This email generally goes to every customer and is one-size-fits-all. This email strategy is never going to be replaced. The content, especially in retail/fashion, will always have an element of merchandising to it. But 30-50% can still be personalized.

Traditionally, dynamic content or segmentation would be used to show different content to different people. However this does not scale. To me, this where email marketers will find the best application of new technology and it’s what will have the biggest impact – replacing segmentation and traditional dynamic content with new technology, including that which is enabled with AI.


Organizations must go through these stages to become ready to take advantage of new, emerging technologies.

It must start with preparing your data for automation — beyond simple segmentation — and ensuring you have the ability to personalize content to each customer. Only then can you think about delivering one-to-one personalization, at scale, for each individual customer.

The benefits of personalization are clear: increased engagement, conversion and revenue. Customers now have an expectation for brands to send them relevant content and recommendations based on their preferences… and this is only going to become stronger in 2018.

Learn how our smart personalization engine can help you tailor your content for each individual customer.

Join world-renowned marketing expert Jay Baer plus marketing leaders from Gap and Cheaper Than Dirt at Emarsys Revolution in Las Vegas, NV, March 18, 2018!

Matt HayesMatt Hayes is the Co-Founder and CEO of Kickdynamic. Matt is the driving force behind the collective goal to innovate email marketing with Kickdynamic. He is an email expert with over 12 years experience managing email & marketing campaigns globally. He loves Rugby, running and music. Kickdynamic helps brands add more personalization to their email marketing.