Overview of Data Mining applications
This is an overview of current applications of data mining in solving problems across different industries and business sectors.
- predictive and risk assessment models for the financial services industry, including credit and insurance scoring algorithms
Biotechnology and pharmaceutical industry
- building special data mining and visualization tools for pharmaceutical and biotech companies, focused on genomics/functional genomics and drug discovery
- tools for the analysis of genetic sequence data.
Customer Relationship Management (CRM)
- integrating and analyzing customer information from Internet and traditional business channels, enabling businesses to improve their customer acquisition, retention and profitability.
- tools for understanding, targeting, and interacting with customers
- browser-based Web visitor analysis, campaign management, revenue forecasting,
- analyzing online shopping behavior and delivering targeted personalized marketing messages to different market segments.
(Telecom, credit card usage)
- detecting fraud and predicting typical card usage at merchant location
- internet credit card fraud detection and risk management service for online merchants.
- uncovering network intrusions
- detecting bad debt and application fraud
- knowledge management solutions for creating, managing, disseminating and archiving protocols, procedures and care plans.
- data warehousing solutions for healthcare industry
- matching employers needs and job applicant's references. Allows employers to select job applicants who are best suited to the company's needs.
- creating, optimizing and deploying marketing campaigns
- integrating direct marketing and Web commerce. Learning from every consumer interaction and applying the knowledge in real-time to deliver the right offer to the customer
Real time decision making
- integration of algorithms in real-time transaction systems
- automated customer interaction facilities
- detection of retention patterns and trends, triggering appropriate actions.
- support for the future demand planning, seasonal sales,
- size and channel profiling,
- customer behavior analysis,
- price optimization
- marketing promotion modeling
- allow retailers to better understand and predict their customers' buying habits.
Stock and investment analysis and prediction
- optimizing trading strategies,
- predicting stocks changes,
- investment analysis for investment in real estate and residential property
- solutions for churn management, lifetime value analysis, product analysis, and fraud detection
Tourism and travel
- market profiles for the travel industry.
- providing browser-based Web visitor analysis (finding patterns in web log data)
- marketing campaign management,
- visitor and buyer segmentation and qualification
- analyzing online shopping behavior
- automated delivery of targeted personalized marketing messages to different market segments
- content aggregation/web automation for continuous content acquisition, through "driving" the browser to visit web sites and extracting meaningful information.
- measuring, tracking and acting upon visitor Internet activity
- Web server log analysis tools
© 2001 LIS - Rudjer Boskovic Institute
Last modified: January 18 2019 16:33:51.