Customer Relationship Management is a strategy used to learn more about
customers' needs and behaviors in order to develop stronger relationships with
them. After all, good customer relationships are at the heart of business success.
CRM to be effective requires using information about customers and prospects
in all stages of their relationship with a company. From the company's point
of view, the stages are acquiring customers, increasing the value of customers
and retaining good customers. According to this customer life cycle, the following
goals in analytical CRM can be identified:
Among the advanced technologies most commonly used for effective CRM
is data mining (DM), which allows to sift through large amounts
of data to uncover previously unknown customer relationship properties.
DM enables analysts to model virtually any customer activity and to find
previously hidden patterns relevant to current business problems, or business
evolution and growth. DM can segment and profile customers to better understand
their needs, behavior and profitability.
But data mining is a difficult process which requires many iterations
and adaptions in the data and in the parameter settings until a satisfactory
result is achieved. Thus, analyzing CRM data successfully requires a lot
of expertise in different areas, in data base technology for data extraction
and data transformation to prepare and preprocess the data,
and in data mining and statistics for model building and evaluation. This
is where MiningMart supports you by providing:
- Operators for preprocessing with direct database access
- Use of machine learning for the preprocessing
- Detailed documentation of successful cases
- High quality discovery results
- Scalability to very large databases
- Techniques that automatically select or change representations