Machine Learning (ML), a subset of Artificial Intelligence (AI), may be an unknown tool to many retail business owners and managers. However, once they learn what it is, how it can benefit the bottom line, and how to use it, it could become another means of increasing sales and profits.
The attached infographic, Machine Learning in the Retail Sector, presents an all-encompassing overview of the topic. It begins with a basic explanation of artificial intelligence and machine learning. Essentially, artificial intelligence is the development of computer systems that can accomplish tasks that we typically think of as requiring human traits. For example, AI applications use visual perception, speech recognition, language translation, and decision-making tools to analyze and solve problems, speed up processes, and even learn.
Machine learning falls under the umbrella term of artificial intelligence. Computers are provided with algorithms that allow the system to access and analyze data, find trends, automatically learn from experience, and continually improve over time. The system learns from data analysis to identify patterns and draw conclusions with virtually no or minimal human intervention. The short definition is that ML helps computers achieve through data analytics what humans do naturally — learn from experience.
How does machine learning work in the retail sector? ML uses what is known as predictive analytics technology, which is the use of data, algorithms, and machine learning techniques to make predictions based on past data. In the retail sector, predictive analytics can be used to determine how customers might react to various marketing and advertising campaigns and what they will purchase in the future. From that information, you can target the relevant ads to customers and personalize offers of related products that complement what they previously bought. Ultimately, this helps retail businesses retain current customers and grow sales.
Graphic created by Aptitive.