Week 10 Questions

1. What is your understanding of CRM?

Customer relationship management involves managing all aspects of a customer’s relationship with an organisation to increase customer loyalty and retention and an organisation's profitability. Customer relationship management helps companies make the their interactions with customers seem friendlier through individualisation.

 2. Compare operational and analytical customer relationship management.

 
The two primary components to a customer relationship management strategy are operational CRM and analytical CRM. 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 and includes all systems that do not directly deal with the customers. The primary difference between operational CRM and analytical CRM is the direct interaction between the organisation and it's customers.
 
 

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

A marketing campaign's success is directly proportional to the organisation's ability to gather the right information. The three primary operational CRM technologies a marketing department can implement to increase customer satisfaction are;


The three primary operational CRM technologies a sales department can implement to increase customer satisfaction are;


  

4. How could a sales department use operational CRM technologies?

One of the primary reasons a company loses customers is bad customer service experiences. Providing outstanding customer service is a difficult task and many CRM technologies are available to assist organisations with this important activity. The three primary operational CRM technologies a customer service department can implement to increase customer satisfaction are;
A contact call centre; is where customer service representatives (CSR) answer customer inquiries and respond to problems through a number of different customer touch points. A contact centre is one of the best assets a customer driven organisation can have because maintaining a high level of customer support is critical to obtaining and retaining customers.
Web based self service systems; allow customers to use the web to find answers to their questions or solutions to their problems. A great feature of the web based self service is click to talk buttons. Click to talk buttons allow customers to click on a button and talk with a CSR directly from a website. Powerful customer driven features like these add tremendous value to any organisation by providing customers with real time information without having to leave the website.
Call scripting systems; access organisational databases that rack similar issues or questions and automatically generate the details for the CSR who can then relay them to the customer. The system can even provide a list of questions that the CSR can ask the customer to determine the potential problem and resolution. This feature helps CSR answer difficult questions quickly while also presenting uniform image so two different customers get the identical answer.
5. Describe business intelligence and its value to businesses.

Business intelligence;  applications and technologies used to gather, provide access to, and analyse data and information to support decision-making efforts. Many Businesses are finding that they must identify and meet the fast-changing needs and wants of different customer segments in order to stay competitive in today’s consumer-centric market. BI can tell companies things like; determining who are the best and worst customers thereby gaining insight into where it needs to concentrate more for its future sales, identify exceptional sales people, determine whether or not campaigns have been successful, and determine in which activity they are making or losing money.

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

As businesses increase their reliance on enterprise systems such as CRM, they are rapidly accumulating vast amounts of data. Every interaction between departments or with the outside world, historical information on past transactions, as well as external market information, is entered into information systems for future use and access. The amount of  data being generated is doubling every year. Data is a strategic asset for a business, if the assest is not used the business is wasting resources. With all the data available it is surprising how difficult it is for managers to get a clear picture of fundamental business information, such as inventory levels, orders in the pipeline, or client history. Many organisations contain disparate silos of information. Rarely do these systems speak the same language and there is no simple way for a non technical user to get answers quickly. It has been said that organisations are data rich and information poor. The challenge is to transform data into useful information. With this information, employees gain knowledge that can be leveraged to increase company profitability.

To improve the quality of business decisions, managers can provide existing staff with BI systems and told that can assist them in making better more informed decisions. The result creates an agile intelligent enterprise. A few examples of using BI to make informed business decisions include;

  • Retail and sales: predicting sales - determining correct inventory levels and distribution schedules among outlets and loss prevention.
  • Operations management: predicting machinery - finding key factors that control optimisation of manufacturing capacity.
  • Law enforcement; tracking crime patterns, location and criminal behaviour - identifying attributes to assist in solving criminal cases.
7. What are two possible outcomes a company could get from using data mining?

At the centre of any strategic, tactical or operational BI effort is 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 and progress through increasing levels of detail or the reverse. Data mining is the primary tool used to uncover business intelligence in vast amounts of data.

Analysis use the output from data mining tools to build models that, when exposed to new information sets, perform a variety of information analysis functions. The analysts provide business solutions by putting together the analytical techniques and the business problem at hand, which often reveals important new correlations, patterns and trends.