Companies using AI (Artificial Intelligence) like a Brand Strategy

Brands using AI by developing a new business model

A new business model has been developed by some companies. Instead of being a B2B or B2C business model, it is called “B2R2C”, from company to robot to consumer. In this concept, the robots will play the role of intermediaries and gatekeepers between the company and the customers. A lot of companies have already used AI, by creating a robot assistant to start attending the customers. Google, Siri and Alexa are some of the current virtual assistants that already know the necessities of the customers in a predictable way, supposing an enormous help for the implementation of their brand strategy.

This new and increasing use of artificial intelligence to develop brand strategies is not a temporary practice since it is here to stay. And it is only necessary to take a look to specific data to realize this. For example, did you know that more than half of the main objectives for which artificial intelligence has been created are directly related to marketing strategies? That is why, as the results of a survey made by the American Marketing Association have shown, the use of artificial intelligence by companies has increased by 27% in a period of less than 2 years.

How AI can help in the creation of a Brand Strategy

As a good marketeer should now, the first step to come up with a successful strategy is to analyze the environment and making a diagnosis of the company situation in order to make the best decisions. And it turns out that AI can be used from the very beginning, during this initial part of the brand strategy definition process. For example, it is now possible for companies to have predictive analytics being reproduced by different platforms, which enables them to forecast what the consumer behaviors are going to be towards the brand, when putting the strategy into action.

Implementation of the brand strategies using AI

Nowadays, in order to achieve maximum profitability, companies should move to more automated decisions.  Once the firm has a solid base in AI and a wealth of consumer and market data, it can start shifting from task automation to machine learning. The purpose is to economize effort and time and to achieve a more efficient decision-making model. In this way, repetitive, high-speed decisions are avoided and personalized suggestions for a choice are offered. In addition, human decision-making is reserved for important issues so that the organization will achieve better outcomes in its brand strategy.

AI is more affordable to include in brand strategy than it sounds, and both large and small companies can benefit from it. It is considered there are 15 different artificial intelligence techniques throughout the customer lifecycle divided in three categories:

  • Machine learning techniques. Algorithms are trained to generate very sophisticated predictions and conclusions from massive amounts of data applied to propensity models and AI applications. For example, predictable customer service.
  • Propensity Model. A collection of approaches for developing predictive models that look at the past behaviour of a specific customer segment to anticipate future behaviour.

AI Applications. Other types of Artificial intelligence technology that do actions that are often associated with human operators. For example, chat bots.

AI techniques applied through the customer life cycle
AI techniques applied through the customer life cycle


Alicia Menor Gómez, Teresa Álvaro París, Patricia Isasi Calvo and María Rita Zubia Soroeta

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