Sub-discipline of artificial intelligence, machine learning technology is changing profoundly the landscape of digital marketing.

Is machine learning the new Grail of digital marketing? In any case, companies have stepped into the water to shift the growing volume of data from Big Data to the sieve of this technology. Hoping to find big nuggets.

And for good reason: Big Data may be everywhere, it remains a rough diamond. Full of mystery, the gem tickles the eye, but you have to go through the size and polishing for its intrinsic qualities come out in the open.

Such are the data when they fall, still rustic and barbaric, in the pocket of the enterprise, coming from many heterogeneous channels. Can digital marketing really benefit? If the tailor is dexterous and uses the right tools, the answer is yes. And one of these instruments is none other than machine learning, or “machine learning”, sub-discipline of artificial intelligence. A method of sorting the wheat from the chaff among the grapes of Big Data to get into the customer’s head and satisfy him more and more.

The ghost in machine learning

No need to tear your hair in front of convoluted definitions to understand machine learning. All that is needed is to see how e-commerce platforms and social networks spend their time suggesting ads to Internet users or services based on data collected upstream. Netflix users are used to it: when they show their interest in a series (ie, Breaking Bad), the algorithm uses the principle of association of ideas to offer them other content likely to satisfy them (Dexter rather than The little house in the meadow, so). It’s the same with a shopping site, a dematerialized music provider or a ticket price comparator, or with Google – which uses machine learning to suggest semi-automatic predictive search. Whatever the case, the user is no longer alone: ​​he must deal with the ghost in the machine, the intelligent algorithm that anticipates his desires to better surprise him.


Tell me which client you are, I will tell you how to consume

The automatic learning of Big Data data makes it easier to draw the contours of the customer journey. By understanding its needs, the algorithm becomes able to predict and anticipate its expectations. As if the waiter, in the restaurant, brought to his customers the dishes they have not ordered yet. Tell me who you are, and how you think: I’ll tell you what to buy.

At a time when consumers value their independence, matching supply with demand may well be the ultimate key to digital marketing. Indeed: accompanied by deep learning, a kind of premium version that works by assembling data, machine learning opens up new and huge horizons for web marketers. From data collected via forms, cookies, loyalty cards, geolocation, mobile applications, connected objects and social networks, companies launch the machine to turn oil into fuel. A fuel that will serve to sell more and better, retain and engage, always with customer satisfaction as a horizon.

Machine learning and digital marketing: a winning duo

In fact, the advent of Big Data, the new habits of consumers and the multiplication of data from IoT explain that machine learning, without being a new concept (the first algorithm appeared in the 1970s), became indispensable for marketers. By 2030, this technology could multiply by 10 the marketing performance of companies, while reducing by 5 their financial risks (source: MagIT). And this having direct effects on their marketing methodology, namely:

  • Increased customization, enabled by more precise segmentation
  • An optimized customer experience, based on the real needs of users;
  • Increased responsiveness of marketing services, through faster recognition of changes in customer behavior;
  • A more relevant use of the marketing resources needed at the beginning of a new prospect’s purchasing path, for better adapted campaigns and a better ROI;
  • A set of more relevant proposals made to consumers from their previous research, thanks to the visual recognition and correlation allowed by deep learning.

These applications are just examples. They will continue to diversify over time, according to the progress of artificial intelligence … but always with the aim of improving the user experience and forging close links between companies and their customers.