What is the place of artificial intelligence in email marketing?

In the age of big data, our digital activity generates oceans of data. In 2020, it is estimated that each person will be generating about 1.7 megabytes of information per second. Artificial intelligence powered by big data opens the door to a new world of marketing. In a magic word: “machine learning” or when a machine becomes capable of learning on its own. For several years, this technology has made artificial intelligence take off. Not a single area escaped him. The publishers of the best email software are no exception. Already in our inboxes, AI in email is still in its infancy but tends to evolve very quickly. How can marketers help anticipate user reactions? How much can it affect the results of your email campaign? Here are some concrete illustrations of the role and potential of AI in email marketing.

How can artificial intelligence contribute to the success of email campaigns?

Predictive analysis

While email marketing is currently based primarily on rules, artificial intelligence takes things a step further and enables predictions and content placements based on predefined algorithms and available data.
The anti-spam filters in your inboxes, for example, are based on intelligent algorithms to determine whether a message that arrives is expected or spam. The system will follow some basic rules but will also learn from the consumer’s habits and preferences. Email that is automatically detected as spam, and which is likely to be reported as such by the user, will be diverted to spam automatically and without any necessary action on the part of the recipient.
Some algorithms also make it possible to predict the importance of a message even before it is sent. As such, some high-end email clients have begun to offer predictive eye-tracking functionality. This feature simulates human vision and measures the visual impact of an email by predicting which areas will get the most attention, even before it’s sent. The four analysis reports provided (Heatmap, Gaze Movements, Blackout Report, and Aesthetic Analysis) allow marketers to optimize message presentation to maximize results without having to wait for the statistical reports generated afterwards. shipments.
Thus, predictive analysis makes it possible to predict the behavior of an individual or a group of individuals. It is the essence of marketing that puts customer data analysis at the heart of its development.

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When automation meets AI to improve user experience

Automation, which is based on the customer life cycle, is one of the major challenges of AI in email marketing. Manual automation quickly becomes very complex due to the definition of strict and complex rules. Thanks to artificial intelligence and machine learning, this connection can be customized individually and automatically for each customer. In addition, the automatic scenario is not carved in stone, but is constantly being improved based on the feedback of campaign recipients.

Segmentation and automatic allocation

Gathering at the CSA Summit in Cologne last March around the theme of “Email Just For You”, email marketing experts unanimously agree that tomorrow’s email will be highly personal, interactive and relevant. By cross-referencing all the data collected, intelligent machine learning algorithms find associations between the profiles of your visitors, your customers, your leads and/or recipients and are able to automatically identify segments with common criteria. Algorithmic analysis of behavioral history, combined with several other segmentation criteria (geographic, identity, etc.) makes it possible to send targeted, personalized communications to a group of individuals with common habits and appetites that are automatically determined. By identifying their preferences and what stage of the customer lifecycle they find themselves in, we are now able to more accurately predict the likelihood that our contacts will convert.
In the field of automation, the long-term goal of AI is to tackle more granular, pared-down targets through highly personalized content until one day it reaches a fully individualized automation.

Predictive transmission

It’s every marketer’s dream: to send a marketing message only when the recipient wants to receive it. That’s what Predictive transmission function Developed by a few email marketing players. Based on an algorithm that integrates artificial intelligence, the function uses data analysis and the behavior of each recipient, in particular analyzing the times they most often open/click their emails, in order to send each campaign at the most appropriate time. time. This option has two main advantages:
– Improved delivery capacity thanks to distributed dispatch over time. In fact, to reduce the likelihood that an email will be considered spam, it is preferable to send the message to small groups of recipients distributed over time rather than to mass send all at once.
– Improved campaign performance: An email sent at the optimal time for the recipient (ideally when the latter checks their inbox) will have a better chance of being opened than a message sent at a random time.

By leveraging the analysis of behavioral data of all recipients, predictive sending dramatically increases the engagement rate of marketing campaigns.

conclusion

Although artificial intelligence is still in its infancy, we can no longer imagine the future of marketing, and thus emailing, without dealing with this new technology. Whether we’re talking about artificial intelligence, machine learning, predictive analytics, data mining, or big data, the goal behind these terms remains the same for email marketing experts: learning from the data collected to create a personalized message and experience that’s unique to each Recipient.

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