Data mining refers to the process of identifying patterns, correlations or anomalies in large data sets through the use of various statistical, mathematical and programmatic techniques. This process is a key concept in many areas such as financial analysis, healthcare, retail and, of course, marketing, particularly in the field of digital marketing.

The primary purpose of data mining is to extract valuable information from existing data, which can then be used to make decisions, predict trends or improve business strategies. Data mining methods range from simple statistical analysis and reporting to complex machine learning algorithms. Frequently used techniques include cluster analysis, classification, association analysis and neural networks.

In the context of marketing, data mining is particularly useful for customer analysis, market segmentation and target group identification. By recognising patterns in purchasing behaviour, interactions on the website or in the use of apps, companies can develop customised marketing strategies that are tailored to the specific needs and behavioural patterns of their customers.

Data mining is often used in combination with other data analysis methods and tools, including data warehousing, text mining and business intelligence, to gain a comprehensive picture of the available data and the insights that can be derived from it. The efficient use of data mining techniques can therefore lead to improved customer satisfaction, higher sales and a better competitive advantage.