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What role does artificial intelligence play in the future of email marketing?

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Artificial intelligence, algorithms and deep learning applications are no longer science fiction. The potential is far from exhausted.

Artificial intelligence in email marketing is no longer science fiction. A few years ago, algorithms and deep learning applications were steadily improving the performance and evaluation of various campaigns.

I’m sure we’re just at the beginning. Especially in the field of email marketing, the potential of this new technology is not even exhaustively exploited. The linkage with such artificial intelligence applications creates many new approaches.

Upgrading the customer experience and shortening the customer journey with email marketing

There are already language assistants who read out incoming emails. But what prevents us from not using the email marketing as an audio-visual medium in general?

From the use of audio – conceivable would be a read, personalized speech – up to the graphical representation in the form of e-mails, which are automatically transferred by the artificial intelligence ​​from a two-dimensional to a three-dimensional template.

Imagine, you receive by mail advertising of a glasses supplier. You open the email and are greeted by a short audio snippet: “Hello Robert. Nice that you’re back.”.

Right here would be the addressee, in this case, an existing customer, suggests that he is in a chain store, in the middle of his inbox – and the seller knows him personally.

Talking about Customer Experience: It’s about a new eyewear collection, of course, there are different designs of the frame, colours and tinted glasses to choose from.

The model pleases, in the mail itself, the design can be determined, and you have your new favourite glasses in mind. But as sometimes happens, the question quickly arises: Is that me at all?

After you have linked a photo of yourself with the image of the favoured eyewear model, the artificial intelligence ​​merges your portrait photo with the eyewear model, and you virtually wear new glasses on the nose.

This is not a simple copy-paste method. The underlying algorithm, thanks to Deep Learning – in simple terms, the continual repetition of the same software operation followed by a stand-alone analysis to gain insight – can put the eyewear model photo-realistic in the right place with the same precision as a professional graphic artist, and a split second.

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