With an average open email rate of 18.0% in 2020, it’s not like marketing teams are crushing this email thing. Wait, isn’t 18% pretty good? We get that standards are low here, for sure. Bottom-line? Email remains a priority.
About four billion people have an inbox. It’s a tough sell to abandon that marketing strategy. But working through the sludge of open rates, send times, tone, content, links and the looming unsubscribe monster remains an absolute grind for marketers.
Some say artificial intelligence (AI) can help. In fact, it’s become one of the early go-to use cases for AI in marketing, according to Paul Roetzer, CEO and founder of the Marketing Artificial Intelligence Institute.
“If you think about your job as a marketer, you write all the rules, you figure out the emails to send, when to send them, what to say, what promo to offer, what price point to use. You are going through and literally writing all these rules that’s trying to predict what’s going to generate the outcome you desire,” Roetzer told CMSWire’s Rich Hein and Dom Nicastro in an episode of the CX Decoded Podcast. “And so that is the history of marketing. We’re trying to do these things to get someone to take an action, and we don’t really think about it as a bunch of all these predictions, but that’s really what it is. And so AI is sort of this umbrella term for the tools and technologies that make machines smart.”
A Lot of Email Marketing Gets Done
Email. No matter how much people talk about the move away from email and into more real-time communication channels, email’s here to stay. About 35% of marketers choose to send three-to-five emails per week to their customers, according to a HubSpot report. Some of you send more. Admit it.
Are marketers tapping into AI and machine learning to help? In terms of what marketers feel are valuable AI implementations in their marketing programs, the use case of recommending highly targeted content to users in real time is number 1 among 49 use cases presented to marketers in the 2021 State of Marketing AI report by Drift and the Marketing Artificial Intelligence Institute.
That use case scored a 3.96, putting it on the cusp of “high value” (4.0), with 5.0 being “transformative.” The AI marketing use cases that trailed in the top five include:
Adapt audience targeting based on behavior and lookalike analysis (3.92)
Measure return on investment by channel, campaign and overall (3.91)
Discover insights into top-performing content and campaigns (3.86)
Create data-driven content (3.82)
Related Article: CX Decoded Podcast: Practical Use Cases of AI in Marketing
Where AI Fits Into Email Marketing
Marketers are using AI to personalize their newsletters and see increases in brand awareness, website traffic, engagement and open and click rates, according to Jared Loftus, chief operating officer of rasa.io, which provides AI-backed solutions for marketing emails. “Additionally,” he said, “our clients are learning more about their audience with the unique data a personalized newsletter provides. They’re learning more about what niche topics people are most interested in.”
Email marketing is still one of the most important marketing tools marketers can leverage for lead generation and customer engagement, according to Loftus. It’s always been a struggle to compile an email list that could be segmented effectively in order to customize emails appropriately, he added. “Now,” Loftus said, “marketers are finding success with AI-based email newsletters by custom curating content for customers based on their past viewing and engagement behavior.”
The very-common practice of A/B testing in email newsletters is not effective, Loftus contends, because web traffic and engagement rates are still low for these click-based products. Personalized email newsletters are designed to allow marketers to target users based on their past viewing and engagement behavior. They also allow marketers to use advanced segmentation tools.
“This means that the ROI of this lead generation tool is much higher due to the fact that consumers are already familiar with the content before they see it, and they’re much more likely to make a purchase or become an active user if they’re already engaging with your brand,” Loftus said.
Email Subject Line and Send Time Help
Naturally, one vendor’s input doesn’t make a market. Further, the global worth of marketing automation platforms, for which email and email analytics are bedrock capabilities, is expected to reach $25.1 billion by the end of 2023.
However, the uses cases for AI in email marketing run deep, according to a blog post from Mike Kaput of the Marketing Artificial Intelligence Institute. Some of the use cases include:
Writing email subject lines.
Writing portions of emails.
Sending personalized emails to each prospect.
Optimizing send times.
Cleaning up email lists.
Automatically creating email newsletters with unprecedented personalization.
He cited tools like Phrasee, Seventh Sense, Drift Email and rasa.io. “Email newsletters are a piece of email marketing, and, at the same time, a huge, separate beast to decode and optimize,” Kaput wrote. “Luckily, AI technology exists to make the whole process a whole lot smarter and more effective.”
Personalized email newsletters sit in the middle of the martech stack because they require a well-developed infrastructure and a combination of technologies, according to Loftus. They are usually composed of an automated email platform that can send out newsletters, and a web analytics or market intelligence tool to gather information about users.
Related Article: 3 Misconceptions About AI in Marketing
Putting the AI Machine to Work
Roetzer said most marketers tend to look at their mail subscribers and constantly slice and dice some form of data to figure out how to get more people to open, click and engage.
“You’ll play around with send time, and when should I send it,” Roetzer said. “Maybe you do that by what time zone they’re in. You’re probably going to play around with subject lines. You may play around with the links within it. You’re going to kind of just keep testing things looking for what’s going to get more of the outcome I desire from my newsletter.”
What if the machine, though, personalized all hundreds of thousands of those interactions, knowing when someone tends to open emails and then starts sending your newsletter when they’re most likely to open it? Then, after 10 to 15 newsletters, it starts to learn what you actually click on and what subject lines got you to open.
And you can still add the human element. You can still write the 200-word editorial upfront and still mix in that personal connection but let the machine do the heavy lifting, according to Roetzer.
“In the background at all times, the machine is learning your personal preferences,” Roetzer said. “And then as the newsletter gets created and sent the machine actually chooses from let’s say 50 links that could go in there, it picks the 10 that it thinks you are most likely to click on. That’s the power of AI applied to newsletters.”