*This is a guest post by Sharon Shapiro, Director of Content Marketing & Integrated Planning at Bluecore

AI has finally arrived.

For years, we’ve heard about its potential, and now we’re finally seeing the impact. According to The Wall Street Journal, 30% of organizations are conducting AI pilots and 47% have embedded at least one AI capability in standard business processes.

In particular, marketing and sales — with their direct tie to revenue — are expected to see the biggest impact of AI, per McKinsey.
 

How AI Changes the Game for Email Marketing

 
Narrowing in further, AI is poised to change the game for email marketing in numerous ways.

According to a recent study of executives at top retail brands and marketing agencies, the most valuable impact of AI in 2020 will be improving marketers’ ability to deliver true 1:1 personalization at scale across digital channels like email.

One important force behind this ability to personalize at scale is that AI allows email marketers to move away from lists. AI Personalization also “gives marketers yet another tool to scale personalization, requiring less time for execution, and allowing more opportunities for optimization” according to Lyndsey Adamo, Senior Strategist, CRM & Email at Tinuiti.

Lyndsey Adamo email strategist
 

The Shortcomings of Lists in Email Marketing

 
Traditionally, email marketers have used customer lists culled from a source of truth, like CRM, to segment audiences and avoid blasting their entire subscriber base at once. But once pulled, these lists are static, meaning they can’t capture changes in behavior in real-time, and they lack context.
 

How AI Eliminates the Need for Lists in Email Marketing

 
Going forward, AI will eliminate the need for these types of lists. Instead, AI will allow email marketers to observe data, make decisions on that data and then take action in a single system. Critically, this data will stay updated in real-time and provide regular feedback on customer engagement with emails to help improve campaigns over time. 

This setup will improve personalization in email marketing (and other digital channels) by making customer data accessible and actionable for all marketers. It will also increase the speed of execution by automating previously manual tasks (e.g. pulling lists) and giving marketers faster insight into data.
 

Making the Shift from Segmentation to Personalization with AI

 
Because marketers have traditionally relied on lists, most personalization efforts in email marketing to date have actually been segmentation rather than true personalization.

What’s the difference? Segmentation occurs when you split customers into audiences (aka lists) using broad factors like past behavior or location. Meanwhile, personalization happens when you individualize the experience for each customer by adjusting elements like product and offer recommendations, content and send time.

Artificial intelligence is allowing the email marketer to reach customers with one-to-one messaging that could not be done so efficiently and successfully without it,” Adamo said.

By eliminating marketers’ reliance on lists and giving them the ability to access and action on data in a single place in real-time, AI allows for truly personalized campaigns in which each recipient sees something different than the next — all from a single email send. 
 

3 Improvements in Email Marketing to Come From AI-Based Personalization

 
In theory, moving past the list sounds great. But how exactly does this impact of AI affect email marketing in practice? And what does the resulting personalization actually look like? Consider the following:
 

1) Fully Personalized Batch Emails

 
Personalized batch emails are a middle-of-the-funnel approach to drive more customers to your website, where they can then engage with your brand and move further down the funnel. The unique thing about these emails is that they send to a larger audience (much like a traditional batch and blast email) but are highly personalized (much like a triggered email that features the specific product customers browsed).

Previously, running effective personalized batch campaigns proved difficult due to a lack of data. AI changes this entirely, allowing marketers to intelligently target all of their customers — even those for whom data is minimal.

How is this possible? First, AI makes the entire process possible — and more efficient — by automatically pairing customers with relevant products, offers and contents based on their past and predicted behavior. Second, AI extends this level of personalization to all customers (even those without much data available) by randomizing recommendations and then learning based on engagement to get better with each send.
 

2) Intelligent Send Time Optimization

 
Next, AI allows for more intelligent and easier to manage send-time optimization. Send time optimization is important, as getting emails to land in customers’ inboxes at just the right time can increase engagement.

In the past, send time optimization efforts have been manual and/or taken a blanket approach. Essentially, marketers would end up testing and then optimizing send time for their entire customer base. However, the time that’s best for one person may be very different than what’s best for another.

AI allows marketers to optimize send times at an individual level by automatically testing send times and then applying the learnings so that each recipient gets the email at the time when they are most likely to engage. This setup allows for smarter, more personalized send time optimization that also eliminates manual work for marketers — a straightforward win-win.
 

3) Goal-driven Predictive Audiences

 
Finally, AI makes it easy for marketers to build powerful predictive audiences that can support specific goals.

Predictive audiences are so powerful because they (a) make decisions on more than just past behavior (which doesn’t necessarily indicate future behavior) and (b) support personalization for customers with limited engagement history. In doing so, predictive audiences allow for very goal-driven and proactive engagement.

Some of the best examples of goal-driven predictive audiences include:

  • Product or category affinity to help expand the reach of targeted campaigns by looking beyond recent browsers and purchasers
  • Predicted lifecycle stage to help save at-risk customers before it’s too late and better communicate with shoppers based on their own unique buying cycle
  • Predicted customer lifetime value and discount affinity to improve ROI on paid marketing channels and on offers shared over email
  • Predicted replenishment to make the repurchase process as simple as possible and get customers what they need at just the right time

 

We’re Just Getting Started with the Impact of AI on Email Marketing

 
We’re already seeing the positive impact of AI on email marketing, but we’re only just getting started. AI will continue to improve the email experience for marketers and their customers alike, so long as organizations have the right technology in place to capitalize on these trends.

What does it take to get started? Check out Bluecore’s Ultimate Guide to ESP Selection for the Modern Retail Marketer and Tinuiti’s CRM & Email Marketing Predictions for 2020 Guide to find out more

About the author:

Sharon Shapiro is the Director of Content Marketing & Integrated Planning at Bluecore, a high-growth marketing technology company based in New York City. Bluecore’s AI-driven retail marketing platform is used by more than 400 retail brands to intelligently connect casual shoppers to the products and offers that transform them into lifetime customers. At Bluecore, Sharon collaborates with top retailers and strategists to highlight the latest trends in retail marketing and spotlight industry leaders. She has had works featured in MarketingProfs and Content Science Review.

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