Digital marketing: how to get into AI (Artificial Intelligence)?

Published on : 04 May 20203 min reading time

Digital marketing helps an organization to focus on customer needs and expectations in order to grow and develop by responding to them adequately, through the internet, social networks, and connected applications and devices. AI or Artificial Intelligence is a group of techniques that allow machines to simulate human intelligence. It allows them to perform tasks that are usually done by humans. How to reconcile the two?

ARTIFICIAL INTELLIGENCE?

Artificial intelligence is divided into two. Machine learning or machine learning uses algorithms to analyse ever-larger data, more efficiently and faster than humans. Indeed, processing such a volume of data for humans would not be possible within a reasonable period of time. It also consists of making machines perform repetitive tasks. Deep learning, on the other hand, allows machines to perform increasingly complex tasks, using the stored data and results to propose optimal solutions to the problems encountered. In this sense, AI and marketing offer a competitive advantage over the competition by allowing to better target needs through predictive trend analysis, and to improve offers on the market.

MACHINE LEARNING AND MARKETING

With its more developed capabilities, AI and marketing allows for more refined analysis by also incorporating variables from outside the organization into sales prediction. Customer data helps the organization to refine the products to be offered to the market to be as close as possible to the wishes expressed. It also facilitates quantity forecasts for production, storage, and distribution to be allocated to each region. It also facilitates prospecting by identifying the audience that shares the same interests as its customers, through the sites visited, or the categories of products sought, through conversion rates, or clicks.

DEEP LEARNING AND MARKETING

To increase sales and improve customer satisfaction, AI and marketing work together to offer complementary products, substitutes or new products that may be of interest to the Internet user. This is achieved by leveraging social network data, browsing history, and all of the user’s preferences. It may even lead to modifying the prices of products according to the visitor’s profile and interest in the product, as well as the associated products. We can even create man-machine conversations based on the analysis of the sentences used to deduce the intentions of the Internet user and respond accordingly. This is an invaluable time-saver for personalized BtoC. Finally, it allows you to promote promoters on social networks with rewards, or to respond to detractors by quickly trying to defuse a possible crisis.

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