Materials, Methods & Technologies, Volume 7, 2013

Streszczenie: The development of information and communication technology creates possibilities for companies to maintain large amount of actual and historical data. The data keep information that can help companies answer to different questions about business performance and help them in decision making. Within these data there is information that will help companies to get new and keep existing customers. Traditional methods of data analysis could not help in extracting the information that was unknown before from these data. Recently for analyzing the data with the aim to detect previously unknown information is being used data mining which is a combination of artificial intelligence, machine learning, statistics, and information processing systems. Data mining is known as a process that finds patterns and meaning of data in large datasets with the aim to discover crucial information for further use and to transform this information in an intelligible form. The use of datamining techniques helps companies to determine the relationships between various factors such as price, the position of the product or staff skills. As a result, companies can create different offers and products for specific customers based on historical data of sales performed. In our paper, we study the use of Association Rules technique in marketing and we apply it practically to the data gathered by a transaction processing system with the aim to increase existing customers' satisfaction and to attract new customers. The generated rules are implemented in a system that creates different offers and products for specific customers. We expect that the products and offers created by the system to have a positive impact in the increase of customers' satisfaction and attracting new clients.