With AI, you can optimize every stage of your email marketing strategy. Some of the ways you can make use of AI in Email Marketing are explain below
- Using Natural Language Generation for Email Copy
- Augmented Audience Research Using Predictive Analytics
- Campaigns based on User Segmentation and Behavioral Prediction
- Large-Scale Email Content Testing
Using Natural Language Generation for Email Copy
It’s easy to find a copywriter who can write emails. It’s impossible to find a copywriter who can do it efficiently. Organic writing has benefits and drawbacks, but most copywriters’ analytical processes are based on personal experiences: They can’t do scenario analysis as fast as an AI engine.
The other end of the spectrum is natural language generation. Instead of processing data, you can use technology to create content. Companies like Phrasee have tailored their AI engine to meet email copy needs, as have news agencies like the Associated Press.
Automatically generate email subject lines and body copy without the tedious iterations of a copywriter. Its AI engine ensures scalability and consistency.
Augmented Audience Research Using Predictive Analytics
Understanding your audience is now a data-driven process. While spreadsheets and data visualization tools are useful, more effective tools exist, especially cloud-based and predictive analytics.
Statistics to predict consumer behavior is not new. It’s been used for decades in TV and media buying. It took a long time to make it cost-effective and precise enough for email marketing.
WARC created virtual user personas using publicly available data and user purchase history. The data was then used to test campaigns for confidence before launching.
It works well with AI’s superior processing power. Only campaigns with a high conversion probability benefit from its use.
Also, using data from Google Analytics and third-party sources, neural networks can now forecast buyer behavior. Using a tool like Quantcast, you can tailor your campaigns to match user intent at each stage.
Campaigns based on User Segmentation and Behavioral Prediction
Retargeting is an underutilized email marketing tool. Many marketers use retargeting settings in MailChimp, for example, to send automated reminders for abandoned carts, and while this works for some brands, it leaves a lot of work undone.
Remarketing works by retargeting your customers at the right time. Even if an email distribution platform helps you deliver emails at a specific time, you must decide when.
That’s where AI comes in handy. Appier, for example, organizes all of your user data, from browsing to purchases. It can then segment the data based on behavior and suggest the best time to send emails.
Large-Scale Email Content Testing
Making scaling decisions based on which content form is working is one of the most time-consuming tasks in email marketing. Because you can only spend so much money on automated campaigns, you should only send out your best-performing content.
A/B testing was the old method. The better of two copies of an email is used as the final copy. For large-scale email campaigns, the A/B technique isn’t as effective. The longer the email, the more tests you need.
Bandit testing can be used to perform scaled email tests. Its name comes from casino “bandits” who use multiple slot machines to increase their odds of winning. Bandit testing tests more than one version of an email at a time.
The data from your email analytics account can help you understand which copies work best. In AI-based scaling, an AI engine analyzes historical data and predicts future outcomes for each email.