The document discusses various customer relationship management (CRM) modeling tools. It describes tools for customer database management, data mining, simulation, and SAP CRM. Customer database management software helps analyze customer data to determine investments, craft messages, execute campaigns, and improve retention. Data mining tools can be used for acquisition, optimization, and understanding customer interactions while protecting privacy. Simulation tools enable scenario analysis and collaboration. SAP CRM supports marketing, sales, and service functions to focus on customer-driven growth and differentiation.

1. CRM MODELING TOOLSCH.HEMCHANDGOWTHAM MBA-A

2. Database marketing techniquesprovides data of a large number of direct customers or potential customers. Demographic variables - age, gender, race, education, occupation, income, religion, marital status, family size, home ownership, socioeconomic status, and so on. Geographic variables - zip code, state, country, region, climate, population, and other geographical census data. Psychographic variables - life style, personality, values, attitudes etc. Behavioral variables - product usage rate and end, brand royalty, benefit sought, decision making units, ready-to-buy stage, and so on. Past business history includes various business statistics on customers.

3. Guidelines for Choosing the Right CRM Software:Assist the marketing department in all its marketing efforts.To learn customer preferences and thus contribute to customer retention.Assists in the sales function.Relevant data in an easily adaptable manner. Should be customer oriented and serve to connect to each customer.Must address the relationship between the supplier and customer.Must have an FAQ system Easy to use and easy to customize

5. MODELING TOOLSCustomer Database Management SoftwareMicro StrategyData Mining ModelSimulation toolsSAP Customer Relationship Management (SAP CRM)

7. Customer Database Management SoftwareDetermine investments in product development.

8. Craft effective advertising messages.

9. Execute sales and marketing campaigns.

10. Understand customer satisfaction.

11. Discover trends.

12. Improve customer retention and lifetime value.

13. Run loyalty programs.Micro StrategyDelivers the analytical flexibilityrequired to continually evolve your customer ever changing needs. It provides:Application Flexibility – Metadata Based Applications: quickly changing reports, modifying metrics, or changing the underlying database structure Each object can they be used in combination with others to create any analysis needed. automatically updated everywhere it used which eliminates errors and minimizes administration costs.Investigation Analysis – Drill Anywhere

14. Advanced Analytics: It has over 200+ statistical, logical, financial, and mathematical functions available. It offers predictive analytics using regression, clustering, market basket, decision tree, and neural network analysis to understand, segment, and target customers for promotions.User Scalability:It is specifically designed to scale to the largest number of uses using multi-layered caching, clustering, load balancing, and true 64-bit compliant code. It helps to meet the needs of all your constituents, whether internal or external. Security: Customer data must be kept absolutely private. It provides Access Control to individual metrics and data creating a comprehensive and centrally controlled security policy.

16. Data Mining and Privacy: A Conflict in the Making? Privacy. Users of data mining should start thinking about how their use of this technology will be impacted by legal issues related to privacy. Customer Acquisition and Data Mining. This could involve finding customers who previously were not aware of your product, were not candidates for purchasing your product . Campaign Optimization: Maximizing the Value of Interacting with Your Customers· Scoring Your Customers. The process of using the model is distinct from the process that creates the model. Typically, a model is used multiple times after it is created to score different databases. · Understanding Data Mining: It's All in the Interaction. · Visualizing Data Mining Models.The purpose of data visualization is to give the user an understanding of what is going on. Since data mining usually involves extracting "hidden" information from a database, this understanding process can get somewhat complicated.

18. SIMULATIONSimulation toolsGeneric and specific software for complex systems scenario analysis . Browser based applications and tools. Collaboration People work together toward a common goal, making use of their intellectual, social, emotional, spiritual and creative endowments.