In the age of big data, our digital activity generates oceans of data. In 2020, it is estimated that each person will produce about 1.7 megabytes of information per second. Artificial intelligence powered by big data opens the door to a new world of marketing. In the magic word: “machine learning” or when a machine can learn on its own. For several years, this technology has made artificial intelligence take off. Not a single area escaped him. The best email publishers are no exception. It’s already in our inboxes, and AI in email is still in its infancy but tends to evolve very quickly. How can marketers help anticipate user reactions? To what extent can it affect the results of an email campaign? Here are some concrete illustrations of the role and potential of AI in email marketing.
How can AI contribute to the success of email campaigns?
While email marketing is currently based primarily on rules, artificial intelligence is taking things a step further and enabling predictions and content placements based on predefined algorithms and available data.
Anti-spam filters in your inboxes, for example, are based on intelligent algorithms to determine if a message that arrives is expected or spam. The system will respect some ground rules but will also learn from the consumer’s habits and preferences. Email which 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 allow the importance of a message to be predicted even before it is sent. As such, some high-end email programs are starting 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 provided analysis reports (heat map, gaze motions, opacity report, aesthetic analysis) allow marketers to optimize message presentation to achieve maximum 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 very essence of marketing that puts customer data analysis at the center of its evolution.
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When automation meets artificial intelligence to improve user experience
Automation, which is based on the customer lifecycle, is one of the main challenges of artificial intelligence 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 communication can be customized individually and automatically for each customer. In addition, the automatic scenario is not stone-carved, but is constantly being improved based on feedback from campaign recipients.
Auto segmentation and personalization
Email marketing experts, gathered at the CSA Summit in Cologne last March on the theme of “email just for you,” said that email of tomorrow will be highly personal, interactive and convenient. By cross-referencing all collected data, intelligent machine learning algorithms find associations between the profiles of your site visitors, your customers, leads and/or recipients and are able to automatically identify segments with common criteria. Computational analysis of behavioral history, along with many other segmentation criteria (geography, identity, etc.) makes it possible to send a targeted and personal communication to a group of individuals with shared habits and cravings that are automatically identified. By defining their preferences and the stage of the customer lifecycle in which they find themselves, we can now more accurately predict the likelihood of our contacts converting.
In the field of automation, the long-term goal of AI is to tackle more precise, reduced targets through highly personalized content until one day they reach a fully individualized mechanism.
It’s every marketer’s dream: to send a marketing message only when the recipient wants to receive it. This is what Predictive dispatch function It is developed by 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 to analyze the times when they often open/click on their emails, in order to send each campaign in the most appropriate way at present. This option has two main advantages:
– Improved delivery capability thanks to distributed dispatch over time. In fact, to reduce the potential for email to be considered spam, it is preferable to send the message to small groups of recipients distributed over time rather than mass sending at once.
– Optimize campaign performance: An email sent at the optimal time for the recipient (ideally when the latter consults their inbox) will have a better chance of being opened than a message sent at a random time.
By utilizing analysis of behavioral data for all recipients, predictive transmission increases the engagement rate of marketing campaigns exponentially.
Although AI is still in its infancy, we can no longer imagine the future of marketing, and thus email sending, without dealing with this new technology. Whether we’re talking about artificial intelligence, machine learning, predictive analysis, data mining, or big data, the point behind these terms remains the same for email marketing experts: learn from the data collected to create a personalized message and a unique experience each Recipient.