Resumen
It is essential to know our customers in order to achieve our overall goal. This knowledge must be profound, not only about their qualities and characteristics but also about their behavior patterns as consumers. This information is necessary to achieve customer loyalty. A clear example is how ads on social media work.
Segmentation groups customers according to their consumer behavior. Behavioral segments are groups of customers who behave similarly concerning the business. These groups of customers with similar buying habits are commonly called customer segments.
Customer segmentation requires as much information as possible about them. That is, transactional data generated when acquiring goods or services, demand potential, market evolution, and trends, among others.
With databases, segmentation and data analysis can be carried out using data mining techniques that allow you to discover customer knowledge. Market segmentation using the K-Means algorithm allows you to segment the market and create data sets by clustering customers to interpret relevant consumption information.
Through the basic use of artificial intelligence, in this course, you will learn the theoretical foundations of Big Data and the data mining technique related to market segmentation. You will be able to perform data pre-processing, data selection, and data processing to obtain keywords that enable you to convert the customer's purchase decision and find relevant data to implement predictive measures and generate decision trees.
Additionally, using specialized software RapidMiner, you will apply the concepts in creating a data mining model that will allow you to be a member of the current business intelligence and have a competitive advantage through the data mining process.
University: Tecnológico de Monterrey
Provider: edX
Categories: Big Data Courses, Marketing Courses, Data Mining Courses
Programa de estudio
Enseñado por
Román Alberto Zamarripa Franco