Impact of Artificial Intelligence in the Future of Retail and Customer Engagement

Impact of Artificial Intelligence in the Future of Retail and Customer Engagement

DOI: 10.4018/978-1-7998-3919-4.ch007
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Abstract

We are witnessing a real revolution in the way we buy and in consumer habits. It's been decades since brands started taking their first steps in ecommerce, followed by the implementation of the first online payments and the phenomenon of .com. However, even at that time, companies had little information about their customers, and these were perceived and treated as a large homogeneous mass. The stage today is different. The user is proactive and has access to a lot of information, which makes him more demanding. For this and other reasons, the consumer should be perceived and treated as an independent individual and whose needs determine the development and marketing of a brand's products and services (now called a centric customer strategy).
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1. Introduction

We are witnessing a real revolution in the way we buy and in consumer habits. It's been decades since brands started taking their first steps in ecommerce, followed by the implementation of the first online payments and the phenomenon of .com. However, even at that time companies had little information about their customers and these were perceived and treated as a large homogeneous mass.

The stage today is different. The user is proactive and has access to a lot of information, which makes him more demanding. For this and other reasons, the consumer should be perceived and treated as an independent individual and whose needs determine the development and marketing of a brand's products and services (now called a centric customer strategy).

In this context, emotions and hyperpersonalization are a fundamental part of a shopping experience that must become magical in order to fall in love with the customer.

In short, the market evolves: from group to individual, from “macro” to “micro”, from generalist statistics to data.

The consumer and their needs have changed; what's more, it's doing it right now and it's going to do it in an increasingly dizzying way, as a result of the transformation that happens around him. Today, the same user can consume a product or service attracted by its low cost and, at the same time, pay a high figure for another that offers you a unique experience.

Consumption in medium-priced products tends to decrease. In fact, according to experts from the commercial marketing research department of the Autonomous University of Madrid, the number of sales of mid-range products are declining overwhelmingly.

On the other hand, ‘Think’ with Google studios stated that out of every 5 online purchases, 1 involves offline search processes and, conversely, 1 in 3 physical store purchases are preceded by consultations in the online world.

We began to live in a golden age, where technology makes possible businesses that until now were unimaginable because of their technical complexity.

The new interfaces will make experiences flow and build a new way of understanding customer-business relationships. However, all this leads to greater complexity, due to the increase in variables to be taken into account.

Personotechnics and hyperpersonalization, emotion-based shopping, the prosumer movement, the union between the online and offline worlds (omnichannel), the tendency to servitization, and the smartization of products, along with other aspects, increase the complexity of the business, directly affecting their entire value chain.

1.1 Categorization by Calculation Power

Most of the advances so far detailed, go into what is called, Narrow or Soft Artificial Intelligence. These systems have achieved great achievements, but have only been trained to perform very specific tasks, such as winning in a game or identifying breast cancer.

Strong or General Artificial Intelligence would assume a cognitive level of intelligence capable of solving various problems in various areas in a coherent way. This type of intellect aims to combine several fields within AI to give systems greater and less directed reasoning toward a delimited task.

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