Week 10- CRM & BI

What is your understanding of CRM? Customer Relationship Management (CRM) involves managing all aspects of a customer's relationship with an organisation to increase customer loyalty and retention as well as an organisation's profitability. 

Compare operational and analytical customer relationship management.

Operational CRM supports traditional transactional processing for day-to-day front-office operations or systems that deal directly with the customers.Analytical CRM supports back-office operations and strategic analysis that includes all systems that do not deal directly with the customers. 

Describe and differentiate the CRM technologies used by marketing departments and sales departments

Marketing departments are able to transform to a new way of using business by using CRM technologies that allow them to gather and analyse customer information to deploy successful marketing campaigns. The three primary operational CRM technologies a marketing department can implement to increase customer satisfaction are:

List Generators - compile customer information from a variety of sources and segment the information for different marketing campaigns.

Campaign Management Systems - guide users through marketing campaigns performing such tasks as campaign definition, planning, scheduling, segmentation and success analysis.  

Cross-Selling - is selling additional products or services to a customer. Up-selling is increasing the value of the sale. 


How could a sales department use operational CRM technologies?

Three primary operational CRM technologies a sales department can implement to increase customer satisfaction are:

1. Sales Management CRM Systems
2. Contact Management CRM Systems 
3. Opportunity Management CRM Systems

Describe business intelligence and its value to businesses

Business Intelligence (BI) - refers to applications and technologies that 

are used to gather, provide access to and analyse data information to support decision-making efforts. 

Explain the problem associated with business intelligence. Describe the solution to this business problem

The problem: Data Rich, Information Poor.
Companies have a lot of data, however they are not able to benefit from levering this information and turning it into useful data for analytical and strategic decision making. 

The solution: business intelligence.

To improve the quality of business decisions, managers can provide existing staff with BI systems and tools that can assist them in making better, more informed decisions. The result creates an agile intelligent enterprise. 

What are two possible outcomes a company could get from using data mining?

Data mining is the process of analysing data to extract information not offered by the raw data alone. Data mining can also begin at a summary information level (coarse granularity) and progress through increasing levels of detail (drilling down), or the reverse (drilling up). Data mining is the primary tool used to uncover business intelligence in vast amounts of data. 

Two possible outcomes of Data Mining:

1. Customer Analysis: a technique used to divide an information set into mutually exclusive groups such as the members of each group are close together as possible to one another and the different groups are as far apart as possible.
2. Statistical Analysis: performs such functions as information correlations, distributions, calculations and variance analysis. Data-mining tools offer knowledge workers a wide range of powerful statistical capabilities so they can quickly build a variety of statistical models, examine the model's assumptions and validity, and compare and contrast the various models to determine the best one for a particular business issue.