In an interview about Applied Artificial Intelligence in Retail, recently published by Futurecom, we addressed some aspects and examples, which we bring here in the full version, without the adjustments made for the edition.
Follow and learn about the impact of these technologies on retail, and how companies have leveraged their results.
How has artificial intelligence evolved?
Artificial Intelligence (AI) is a science that seeks to provide machines, computers and cell phones with cognitive capacity, that is, to simulate the human capacity to reason, make decisions and perform complex tasks.
From a more conceptual point of view, its applications are in so-called Machine Learning (self-learning systems), neural networks, data mining, natural language processing, simulation of human thought, Internet of Things (IoT) and Big Data, among others.
From the perspective of our daily lives, it is already easy to see that the hundreds of practices we experience today, in the so-called digitalization of people and businesses, have behind them the concept and application of Artificial Intelligence, such as when simply sending a message to someone in the family, for example, when a spell checker suggests words that we are typing, or when we do a search on Google.
The first experiments with
AI began in the 1940s and, especially after the 2020 pandemic that resulted in the acceleration of digital transformation, its use grew dramatically.
In business, the use of AI can be seen in commercial practices or operations, in customer service processes – with the well-known customer service robots (chatbots) – in personalized service provided by a machine, in e-commerce, in digital marketing, in the logistics of delivery and receipt of goods, in mapping customer behavior, in offering bitmart database products or dynamic prices, in data collection and analysis, in the generation of management reports, in customer satisfaction surveys, or even in internal communication between work teams.
According to research recently carried out by international consultancies(*), the use of AI is not only a trend for the coming years, but also suggests that the estimate is US$7 billion in investments in 2022.
Other data that proves this trend
only from one aspect of AI: it is estimated that 85% of interactions between companies and customers by 2020 will be carried out with the help of artificial intelligence (**). In addition, there was a 120% growth in the number of companies that plan to offer a chatbot service to their customers.
What are the applications of artificial intelligence in retail?
In retail, more specifically, we can see artificial advantages and disadvantages applied both in consumer interaction and in store operations, and present both on digital platforms and in physical stores, in order to better serve customers and automate internal processes.
Whether on digital platforms, e-commerce or physical stores
AI derivations from Machine Learning, neural networks, data mining, natural language processing, simulation of human thought or the Internet of Things (IoT) are a reality that is behind the most successful businesses, as it allows decision-making, cost reduction and increased efficiency of retail operations.
This is very clear in the area of Customer Service, where customer service robots or virtual assistants (chatbots) allow for greater productivity and personalized service, even when performed by a machine. These mechanisms simulate human thought processing, with self-learning systems, perform data mining, recognize behavior patterns, process natural language, and generate performance reports. The result is an improvement in the customer experience.
As less “human” as it may seem, some data goes against these practices:
35% of people prefer an instant response, even from a robot, to a delayed response from an attendant.
Chat is the preferred support channel for the sg number born between 1981 and 1996.
From this perspective alone, the results of service using AI are the reduction of waiting lines for customer service (operating 7 days a week and 24 hours a day), the improvement in service time, the personalization of service, the reduction of operational costs and the gain in productivity.
