Sunday, May 8, 2011

Customer relationship management and Business intelligence

Chapter 9:


1. What is your understanding of CRM?
A CRM is a system which allows firms to manage customers better. by using these systems companies are able to gain insight into customers shopping and buying habits. They are then able to produce products, sales and items which are best suited to there target market, creating a customer loyalty between the store and the customer. These types of systems are often used by marketing and sales departments of a firm.


2. Compare operational and analytical customer relationship management.
Operational customer relationship management refers in particular to the recording of customer details, often called front office operations, operations customer relationship management directly refers to interaction with customers.
Analytical Customer relationship management refers to the use of operational data and data mining to gain competitive advantage by understanding market buying and selling trends and other customer data which could boost the success  of customer relations with the company and the customer.
3. Describe and differentiate the CRM technologies used by marketing departments and sales departments
The Customer Relationship Management technologies used by marketing departments are campaign management and opportunity management. Campaign and opportunity management includes information such as costs, target audience and return on investment.

The CRM technologies used by sales departments essentially allows for the streamlining of the sales process. CRM technologies in this department are used to coordinate the sales process, by helping salespeople organise their jobs, calendars, contacts, appointments, meetings and multimedia presentations. 

Campaign management systems which enable guides for uses through the marketing campaigns and Cross Selling selling additional products/services, and Up-Selling increasing the value of the sale. This looks at the Marketing Metrics which consists of new customer retention rates and number of reposonses/purchases by a marketing campaign, revenue generated and customer retention rate.
Sales looks at more the number of prospective customers, new customers, retained customers and the amount of new revenue and proposals given.
4. How could a sales department use operational CRM technologies?
there are many advantages that arise within sales departments who use CRM technology. Sales departments are able to use list generators with customer information to determine key statistics to assist in success of sales for example identifying where a particular type of product is sold... removing risk of playing high cost products into lower paying areas.  They are also able to use CRM technology to create cutomer loyalty and this is done by using terms such as creating loyalty card or offering sales such as 'buy one product get the second piece free' or offering pre sale on new products.
5. Describe business intelligence and its value to businesses.
Business inteligence refers to the applications and technologies that are used to gather and analyse data and information to simplify decision making. This allows for businesses to identify problems, study the data that is collected from the sales of a company's products and simplify the way they make decisions in relation to the business and in particular there goods or services.
6. Explain the problem associated with business intelligence. Describe the solution to this business problem.


The key issue with BI is that though it gathers multitudes of data it is unable to gather it into useful pieces of information that are relevant to areas of a business. This causes businesses to be unable to determine there own strengths and weaknesses or areas which need improvement.
7.What are two possible outcomes a company could get from using data mining?
Cluster analysis: refers to the grouping of information or data from multiple databases in order to identify trends and establish behavioral traits of the target market/s
Statistical analysis: Uses regression analysis and statistics to evaluate the trends within the data.

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