The popularity of Artificial Intelligence is growing every day. More and more companies aim to implement AI in their business. Indeed, nowadays artificial intelligence can help to optimize many tasks and solve many problems. From analysis to implementation, AI can provide important services.
Email marketing is not an exception! Artificial intelligence offers a large number of possibilities for increasing efficiency and overall marketing performance.
Did you notice how sometimes it can be hard to increase email open rates? How difficult it can be to achieve email marketing goals?
In this article, we will share with you 5 applications of AI in email marketing.
“Email Marketing Problem Number One: Declining Attention”
As users receive more and more information, it is getting harder to grab the audience’s attention. As more and more companies become professionally engaged in content marketing, the battle for attention intensifies.
Email marketing can be used as a very powerful tool if you use it correctly. To increase the email open rate, targeted messages should be sent to the right people at the right time. Only those who are able to respond precisely to the needs of their customers can expect high email open rates. With AI technologies, these tasks can be done automatically and way more efficient than before.
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5 Exciting Possibilities of Using Artificial Intelligence in Email Marketing
1. Generation of New Potential Customers with Lookalike Modeling
A typical use case for the use of AI is the lookalike campaigns of Facebook. There are dozens of services that use artificial intelligence to find out which customers have the greatest potential. They use existing profiles in your customer database (lookalike campaigns) to do this and thus recognize the additional potential for other contacts. For example, cxense shows exactly how this can work.
This can not only improve the email open rate but also increase conversions.
2. Email Automation with AI
AI-supported systems are designed to carry out machine-controlled or automated campaigns based on customer information. These systems can precisely identify at which phase of the customer’s journey the user is.
Therefore, this technology can be very useful for email marketing. It uses data such as past purchases, interests, and browsing behavior to launch machine-driven campaigns. As a result, it helps to increase email open rate and develop leads.
3. Hyper Personalization in Email Marketing
Personalization is not a new phenomenon in email marketing. The sender address, subject line, salutation, and text content have all been personalized since the first day in email marketing. However, when it comes to dynamically sending targeted information, artificial intelligence is used.
A typical application example is to send explicit information based on the social behavior of a user which is exactly tailored to his status. Texts, as well as images, can be created independently of human power. This information can match a user’s location or it can also be product information that is targeted based on the user’s behavior on social media. The possibilities are almost unlimited.
4. Cross-media Individualization
Artificial intelligence becomes really interesting when it is able to recognize the very specific needs of customers via several channels and playout information directly and precisely. This means it has to recognize user behavior on the web in social media in email marketing via different channels. Based on this information it determines which emails have to be published next or which landing pages have to be adapted to the specific needs of the user. The leader in these matters is definitely Amazon.
Most e-commerce companies in this country still find it difficult to use variable recommendations based on marketing information. Artificial intelligence can help them not to miss the boat.
5. Data Analysis, Forecasting, and Anomalies in Email Marketing
A prerequisite for any method mentioned is a good database. Statistics such as email open rates/clicks rates, impressions, visitors, sessions, and conversions should be collected consciously in order to use artificial intelligence for predictions and monitoring. These marketing automation result in a number of new metrics that are fundamental for predicting campaigns or detecting anomalies in your KPIs.