How machine learning can improve our Email Experience

Around 2015/2016, Google began a strategic move, possibly one of the most important it has undertaken in its more than 20 years of existence, to incorporate machine learning and apply it to all its products. Its CEO, Sundar Pichai, saw machine learning as the ultimate disruptive technology, and in a strong display of leadership, embarked on a mission to introduce the technology throughout the company, training all its employees in it.

A few years later, what can we observe? Email, a tool we all use quite regularly, is an interesting example. With Gmail the most obvious and practical difference is the spam filter: you no longer receive spam in the main folders; now all spam goes directly to your folder, where you look and delete it without further ado.

Not so long ago, things were very different: spam messages were showing up in folders all the time, we should have labeled them as such or deleted them, being careful not to delete something that shouldn’t have been deleted.

There has also been a significant improvement in Gmail to understand that something is spam for us, even if it is not spam as such. After sending the same mail to the trash a couple of times, for example, press releases from sources you no longer care about, stop appearing in the inbox. For some time now, spam has been a problem that has practically disappeared, and to which we spend practically no time, despite the fact that we receive a ton of emails every day.

In 2018, Google introduced smart compose, which completes emails automatically and in a way that is so clever that it borders on worries, prompting me to wonder how Google might know what I was thinking of saying to a particular person. A feature I never thought would ever become practical, yet I find myself using it on more and more occasions.

Also, for some time now, the checker has no longer just warned me about typos, but has become a good grammar checker, which is very useful when you often write in your second language.

Google’s use of machine learning means we will continue to use Gmail for the foreseeable future.

Machine learning can greatly contribute to our use of a particular product. But above all, it can build competitive advantages that generate loyalty and make it clear, as happened to me, that switching to a competing product makes no sense.

Applying Google machine learning to Gmail is proof that a strong leadership strategy, such as that undertaken by Sundar Pichai five years ago by betting on machine learning, can yield very interesting rewards and allow you to greatly differentiate your products from those of competitors.

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