DATA MINING APPLICATIONS

In every industry data mining applications provide new insights to improve competitive advantage and optimise business. Here you can find some of our business cases and data mining applications:

B to C industry. Customer Churn Prediction.

The Data Mining algorithm predicts for each customer the probability (or chance) that he/she will churn in the (near) future (e.g. prediction period = today + 6 months). The Data Mining algorithm also provides detailed information about characteristics of churned customers versus characteristics of retained customers. The algorithm is trained on customer data which measures customer behavior and  is collected today and in the past.

Goal: If you know today which of your valuable customers will churn in the (near) future and what their characteristics are, you can act upon this information immediately and prevent them from churning. You are able to understand your customers behavior pattern and you can use this information to react to their needs.

Figure 1 illustrates a simplified example of the output results of a customer churn prediction business case. For example, the chance that customer xxxxxx will churn in the near future is 83%, indicating that there is a high risk of loosing this customer. The churn indicator for this customer is his/her age. The chance that customer yyyyyy will churn in the near future is 20%, indicating that there is a low risk of loosing this customer. Finally, the algorithm learns us that good paying customers living in Brussels (zip code = 1000) are at very high risk (re.  customer zzzzzz showing 0.92!) if their age is between 40 and 60.

Figure1. Customer Churn Prediction.

Similar business cases: Customer Value Prediction – Customer Profile Prediction – Customer Next Buy Prediction.

Other industries.

Pharmaceutical sector & medicine. Classifying breast tumors and skin lesions – Data Mining for medical quality measurement – Knowledge discovery in clinical datawarehouses.

Health and patient safety. Hospital infection control – Data Mining for performance improvements of safety, quality and care for patients and residents in health care organizations.

Traveling, transportation and cargo industry. Market profiling in online travel industry – Optimising customer service using Data Mining solutions.

Energy. Knowledge discovery from patterns of energy use – Using Data Mining techniques to analyse factors effecting efficiency changes – Data Mining model generations for decision improvement.

Automotive. Artificial intelligence discovers fraudulent warranty/insurance claims – Fault diagnosis prediction – Modeling customer targets.

Government. Fraud detection in tax registrations – Using Web Usage Mining for detecting child abuse – Data Mining the web to discover money laundering.

Finance. Identifying suspicious transactions and discovering money laundering by means of Data Mining techniques - Portfolio clustering.