AI in Email Marketing: How is AI Used in Email Marketing?

This article is about how AI is changing email marketing. It talks about how AI can send customers personalized emails to get more revenue from email.
May 09, 2024
AI in Email Marketing: How is AI Used in Email Marketing?
As AI supports almost all business fields, you may wonder if the technology can also assist in email marketing. Indeed, AI already aids marketing in many ways, Generative AI for content creation, product recommendation for personalization, and Large Language Models for chatbots. However, team Retentics believes that AI is not yet fully utilized in email marketing, despite the availability of advanced technologies and already proven use cases. This article introduces how AI is used in email marketing to maximize revenue and profit, with specific use cases highlighted.

AI segments your customers for a particular purpose

In general, the revenue split between automatic email campaigns and manual ones is 50/50. The automatic email refers to flows in Klaviyo such as welcome coupons, cross-selling recommendations, and cart abandonment. If you are a marketer at an early-stage DTC brand, this proportion may not apply, but as your brand grows, you eventually need to segment customers carefully to avoid fatigue, which results in unsubscribing and low LTV.
notion image
Whereas the primary objective of generic email campaigns is to remind your customers of your brand, advertise new arrivals, or share news, a flow, also called automatic emails, should target the right customers with the right items at the exact moment to generate revenue. Thus, automatic email campaigns mostly wait for the right time until your customers need something based on their preferences or the behavior of all your customers. For instance, if many of your customers tend to buy product B two months after purchasing product A, you should recommend B to customers today who bought A two months ago.
AI can hyper-personalize this part. Some of your customers may buy B three months after A, while others do so six months later. Understanding your customers at as granular a level as possible increases the level of personalization, improving all metrics of engagement finally. When you promote new jeans, the primary target recipients should differ from those for a t-shirt. You will see the different net revenue from your campaigns with this!

AI even personalizes generic campaigns with dynamic item recommendations

We recently tested the hypothesis: Can we add just a couple of items at the end of an email to recommend? Of course, you can do whatever you want, but what we wanted to identify was whether item recommendations in unrelated campaigns also increase revenue. The answer is yes, they do, even a lot.
the example of adding recommendations items in the email (retentics)
the example of adding recommendations items in the email (retentics)
AI calculates so many cases with various variables, and as a result, it always has items to recommend to each of your customers, regardless of whether the probabilities are high or low. This is the biggest advantage of AI compared to humans. We tend to take the most representative number when trying to understand something and simplify it for execution, whereas AI can consider almost infinite numbers under different conditions.
When we conducted A/B testing with our customer companies, it showed that adding the recommendation to any email campaign increases the order conversion rate by an average of 1.56 times, without exception.

AI optimizes coupon amounts to maximize profit with minimal testing

Marketers often have a difficult time determining what percentage discount they should offer their customers. A 0% discount typically results in minimal order conversions, whereas a 100% discount generates no revenue. What smart marketers do, then, is conduct tests to find the optimal discount percentage. They might split all customers into a certain number of groups and offer discounts of 0%, 5%, 10%, and 20% to see which shows the best conversion rates and calculate costs to determine the most profitable coupon discount. However, what if you could identify the best discount for each customer, meaning you only offer discounts when they will change their purchasing decision?
It is almost impossible to create a formula for each customer to calculate the likelihood of purchase based on different discount amounts without AI technology. However, for instance, causal ML(Machine Learning) requires minimal testing data to determine the best discount amount based on customer similarity. You may have already experienced this with large e-commerce services and brands. If you add items to the cart and leave, sometimes you receive a discount within 15 minutes, but sometimes you don’t receive one at all.

In closing,

AI is starting to make big changes in email marketing. It can get to know each customer really well and send them emails that are extra personal. Brands can use AI to segment their customer list into very specific groups based on what people like and when they shop. Then the AI can send automatic emails to each group with the right products at the perfect time.
Team Retentics are currently working with various DTC brands, conducting A/B tests to help optimize their AI email marketing strategies. We will continue sharing insights on our blog, so if you're interested in staying on top of how AI helps email marketing, please subscribe below by leaving your email address. You'll be the first to receive notifications as we release new content!
Share article
RSSPowered by inblog