In 2018, marketers will be looking for better and savvier ways to implement artificial intelligence into their email strategies so they can build smarter email journeys for their customers.

Before we dive into how, let’s look at why marketers want to make email journeys smarter. Put simply, artificial intelligence (AI) allows brands to deliver predictive, personalized email journeys at scale. Over time, that personalization can lead to more conversions and increased brand loyalty.

How can marketers use AI to build smarter email journeys in 2018 and beyond? Here are three things you should have in place to get started:


Have your data ready.

Your data should be organized and clean. Dirty or chaotic data won’t do you — or your AI platform — much good.

Keeping your data clean and organized will require you to take a close look at how you’re managing the data you collect, store, and use. In other words, you’ll need to look at how effectively you’re using your CRM and subscriber data.

After the holidays, you’re likely swimming in data. Salesforce recorded nearly 62 billion data capture events during Cyber Week alone. That’s a lot of data and a lot of opportunity. Keeping it clean and organized will allow you to more easily draw insights and set goals.


Have a plan.

According to the fourth annual “State of Marketing” report, marketers anticipate AI use will grow by 53%, marketing automation platform use will grow by 31%, and DMP use will grow by 28%. That’s a lot of investment in building smarter customer journeys and probably includes some of your competitors.

Chances are, though, to get buy-in from your supervisor, VP, or CMO, you’re still going to have to make a case for breaking from the status quo. In other words, don’t propose implementing a load of automation without knowing exactly how it’s going to support your larger marketing and business goals.

For example, if your analytics has shown high cart or browser abandonment, demonstrate how you could use an abandonment email series — with predictive product recommendations and personalized offers — to bring lost buyers back into your funnel. 

You can take it further within Journey Builder, where you can build journeys based on Engagement Scoring. This opens the door to optimized, cross-channel campaigns for users based on their engagement behavior, maximizing the reach of your message and increasing the likelihood of conversion.  


Get familiar with machine learning.

Although they are often used interchangeably, there is a subtle difference between artificial intelligence and machine learning. Saying they’re the same is kind of like saying a dog and a St. Bernard are the same. Yes and no. AI refers to computers doing tasks in ways humans typically would. It involves a human programmer telling the computer exactly how to carry out those tasks. Machine learning more specifically refers to a kind of AI in which computers are programmed to “learn” for themselves.

Put to work for email marketers, machine learning allows your technology to get to know your audience better and make predictive, personalized recommendations based on what it learns over time. It’s a step past automation and has game-changing potential for building the kind of dynamic and personalized email journeys based on user behavior that marketers have been dreaming of for years.

Machine learning for email marketing is still in its adolescence and is getting smarter and more available every year. Check out what Salesforce Einstein is already doing with machine learning and the potential it holds for the future.

The coming year is sure to bring as much promise and challenge as the last. For the ever-evolving world of email marketing, that means continuing to build smarter, more personalized email journeys that surprise and delight your customers.

Want to see these insights in actions? See how three brands are using AI to build smarter email journeys.