CHAPTER 11:BUILIDING A CUSTOMER CENTRIC ORGANIZATION-CUSTOMER RELATIOSHIP MANEGEMENT

Why is it important for any company to use CRM strategies to manage customer information?

Customer relationship management (CRM) is not just the application of technology, but is a strategy to learn more about customers' needs and behaviours in order to develop stronger relationships with them. As such it is more of a business philosophy than a technical solution to assist in dealing with customers effectively and efficiently. Nevertheless, successful CRM relies on the use of technology.

This guide outlines the business benefits and the potential drawbacks of implementing CRM. It also offers help on the types of solution you could choose and how to implement them.

Implementing a customer relationship management (CRM) solution might involve considerable time and expense. However, there are many potential benefits.

A major benefit can be the development of better relations with your existing customers, which can lead to:

1)increased sales through better timing due to anticipating needs based on historic trends

identifying needs more effectively by understanding specific customer requirements

cross-selling of other products by highlighting and suggesting alternatives or enhancements

identifying which of your customers are profitable and which are not

This can lead to better marketing of your products or services by focusing on:

2)effective targeted marketing communications aimed specifically at customer needs

a more personal approach and the development of new or improved products and services in order to win more business in the future

Ultimately this could lead to:

3)enhanced customer satisfaction and retention, ensuring that your good reputation in the marketplace continues to grow

increased value from your existing customers and reduced cost associated with supporting and servicing them, increasing your overall efficiency and reducing total cost of sales

improved profitability by focusing on the most profitable customers and dealing with the unprofitable in more cost effective ways

4)Once your business starts to look after its existing customers effectively, efforts can be concentrated on finding new customers and expanding your market. The more you know about your customers, the easier it is to identify new prospects and increase your customer base.

Even with years of accumulated knowledge, there's always room for improvement. Customer needs change over time, and technology can make it easier to find out more about customers and ensure that everyone in an organisation can exploit this information.

If the virtual world is the first point of contact between a company and its customers, how might that transform the entire shopping experience?

~ The virtual world could become the first point of contact between companies and customers and could transform the whole experience, writes Jo Best on Silicon.com.

~ Some companies believe Second Life could one day become a first point of contact for customers. Like many other big brands, PA Consulting has its own offices in Second Life and has learn that simply having an office to answer customer queries is not enough. Real people, albeit behind avatars, must be staffing the offices – in the same way having a website is not enough if there isn’t a call centre to back it up when a would-be customer wants to speak to a human being. In future, the consultants believe call centres could one day ask customers to follow up a phone call with them by moving the query into a virtual world and hanging around in Second Life is more fun than being stuck on hold. 

~ However, currently Second Life and its imitators remain relatively niche in usage terms and have their own technology boundaries – not all consumers, particularly the older community, have the tech savvy or indeed the hardware necessary to make use of virtual worlds.

chapter 9: DECISION MAKING

Four most common categories of all include:

Expert system...

A good example of application of expert systems in banking area is expert systems for mortgages. Loan departments are interested in expert systems for mortgages because of the growing cost of labor which makes the handling and acceptance of relatively small loans less profitable. They also see in the application of expert systems a possibility for standardized, efficient handling of mortgage loan, and appreciate that for the acceptance of mortgages there are hard and fast rules which do not always exist with other types of loans. 

EXPERT SYSTEMS:

One of the largest area of applications of artificial intelligence is in expert systems, or knowledge based systems as they are often known. This type of system seeks to exploit the specialized skills or information held by of a group of people on specific areas. It can be thought of as a computerized consulting service. It can also be called an information guidance system. Such systems are used for prospecting medical diagnosis or as educational aids. They are also used in engineering and manufacture in the control of robots where they inter-relate with vision systems. The initial attempts to apply artificial intelligence to generalized problems made limited progress as we have seen but it was soon realized that more significant progress could be made if the field of interest was restricted.

Genetic Algorithms 

An artificial intelligent system that mimics the evolutionary, survival-of-the-fittest process to generate increasingly better solutions to a problem.It essentially an optimizing system, it finds the combination of inputs that give the best outputs.Useful when search space very large or too complex for analytic treatment.In each iteration (generation) possible solutions or individuals represented as strings of numbers.

Neutral network 

 Attempts to emulate the way the human brain work.Artificial intelligence are composed of interconnecting artificial neurons (programming constructs that mimic the properties of biological neurons). Artificial neural networks may either be used to gain an understanding of biological neural networks, or for solving artificial intelligence problems without necessarily creating a model of a real biological system. The real, biological nervous system is highly complex: artificial neural network algorithms attempt to abstract this complexity and focus on what may hypothetically matter most from an information processing point of view. Good performance (e.g. as measured by good predictive ability, low generalization error), or performance mimicking animal or human error patterns, can then be used as one source of evidence towards supporting the hypothesis that the abstraction really captured something important from the point of view of information processing in the brain. Another incentive for these abstractions is to reduce the amount of computation required to simulate artificial neural networks, so as to allow one to experiment with larger networks and train them on larger data sets.

Intelligent Agent

Purposed knowledge-based information system that accomplishes specific tasks on behalf of its users include multi-agent systems and agent-based modeling.

An example of intelligent agent is used in technology in Travel Reservation Systems…a travel agent, software or human, must not operate on behalf of any single airline or any other similar company, so that it will be able to obtain optimum offers for their clients. Therefore, by definition, the perfect software travel agent will be one owned by a travel agency and will work to obtain optimum packages for its customers.  

CHAPTER EIGHT -> Accessing Organizational Information (Data Warehouse)

1. ROLES AND PURPOSES OF DATA WAREHOUSES AND DATA MART IN ORGANIZATION

The purpose of the Data Warehouse in the overall Data Warehousing Architecture is to integrate corporate data.  It contains the "single version of truth" for the organization that has been carefully constructed from data stored in disparate internal and external operational databases.The amount of data in the Data Warehouse is massive.  Data is stored at a very granular level of detail.  For example, every "sale" that has ever occurred in the organization is recorded and related to dimensions of interest.  This allows data to be sliced and diced, summed and grouped in unimaginable ways. 

Typical Data Warehousing Environment

 Contrary to popular opinion, the Data Warehouses does not contain all the data in the organization.  It's purpose is to provide key business metrics that are needed by the organization for strategic and tactical decision making.Decision makers don't access the Data Warehouse directly.  This is done through various front-end Data Warehouse Tools that read data from subject specific Data Marts.The Data Warehouse can be either "relational" or "dimensional".  This depends on how the business intends to use the information.ETL (Extract Transform Load) jobs extract data from the Data Warehouse and populate one or more Data Marts for use by groups of decision makers in the organizations.  The Data Marts can be Dimensional (Star Schemas) or relational, depending on how the information is to be used and what "front end" Data Warehousing Tools will be used to present the information.Each Data Mart can contain different combinations of tables, columns and rows from the Enterprise Data Warehouse.  For example, an business unit or user group that doesn't require a lot of historical data might only need transactions from the current calendar year in the database. The Personnel Department might need to see all details about employees, whereas data such as "salary" or "home address" might not be appropriate for a Data Mart that focuses on Sales.

Typical Data Warehousing Environment

Some Data Mart might need to be refreshed from the Data Warehouse daily, whereas user groups might want refreshes only monthly.

 2. The relationship of business intelligence and data warehousing 

Many of the tool vendors who sell their products or softwares call it business Intelligence software rather than data warehousing software. Business Intelligence is a term commonly associated with data warehousing. Business Intelligence is a generalized term where a company initiates various activities to gather today's market information which also includes about their competitor. Today's business Intelligence systems are contrasted to more classical way of information gathering in mining and crunching the data in the most optimal manner. In short we can say BI simplifies information discovery and analysis. In this way the company will have a competitive advantage of business and intelligently using the available data in strategic and effective decision making. it has the ability to bring disparate data under one roof  with a meaningful information and ready for analysis.

Business intelligence usually refers to the information that is available for the enterprise to make decisions on. A data warehousing (or data mart) system is the backend, or the infrastructural, component for achieving business intelligence. Business intelligence also includes the insight gained from doing data mining analysis, as well as unstructured data (thus the need for content management systems). All the source data from disparate sources are used to load/Stage data. Different sources can be flat files, another database or some other process. The starting point of the Data warehouse should extract the data in order to load into its environment.This data may not be the expected format or size. your business demands are different or your organization business requirements are different. So the business process has to modify the data or better word is to transform the incoming data to meet requirements and objectives. This is called Transformation. Once every slicing and dicing of the data is done along with applied business rules, this data is ready for loading into the target tables. This process is called Loading. So overall till now we have done Extraction, Transformation and Loading. In short we call this ETL. There are lot of tools available in today's market which does help in achieving the ETL process. Once this data is loaded in to the database, this is ready for next processing. We call that database as Data warehouse database. The next process could be building of data marts or directly reporting from it. There are lot of tools/software available for reporting/analysis. Some call it business reporting or analysis tool.