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CUSTOMER RELATIONSHIP MANAGEMENT, CASTLE BINGO

Outline

Executive summary
Introduction

III.        Findings

The big data and metrics
Benefits of big data metrics
Recommendations

VII.      Conclusion
VIII.     Ethical and Legal Issues
 
 
 
 
 
 
 
 
 
 
 
 
 
 
CUSTOMER RELATIONSHIP MANAGEMENT, CASTLE BINGO
Executive summary
A data management system is software that is used in the retrieval, cataloging and running data queries. The system organizes and modifies the incoming data I a way that it can be extracted from the other users or other programmers. The database manager is able to create, edit and update customer data in the database. Therefore the information can be edited, searched, added or changed using all the data management systems. Examples of data management system include: file maker, oracle, mySQL, postgresSQL, Microsoft access, SQL server, clipper and Fox pro. Several data management systems have been developed with time. They are important in information sharing thus most of the are equipped with an open database connectivity that enhances inter database information sharing. Some of the information that can be managed by the system include: membership list and subscription list, bookkeeping and accounting records, scientific research data, customer information, inventory information, personal records and library information (College of information and technology 2008).
Introduction
Customer relationship management is an internet enabled information access software that i..s used to manage customer relationships by entrepreneurs in an organized manner. It ensures that detailed customer information is accessed by all interested departments of the business are able to access the required information. Some of the relevant information that can be accessed include; reminding of customers of product requirements, access the records of what a customer purchased earlier. All businesses are highly dependant on customers therefore it is necessary to identify with customers so that their needs can be understood and met by the business to develop a good relationship. A small business is able to meet their customers daily and understand the needs of their customers due to the face to face interaction unlike large businesses like the supermarket where there are long chains between the decision maker and the customer care. In the past few years many companies have tried to invest in customer relationship management to acknowledge and understand the customers. This will change the business from being less product centric and more customer centric (Trapp 2013). The development of this system will enable companies without technology to effectively and efficiently handle customers as this technology would integrate the other forms of communication such as emails, telephone and and internet conversations in writing. It has been realized that companies that use sophisticated technology would benefit more than the companies that use basic data collection methods. Analysis of customer past behavior and anticipation of the future trends is put in (College of information and technology 2008)
Findings
Thomas H Davenport and Jeanne G Harris have indicated in their book competing on analytics` that companies that have employed customer management systems have predictive analytics and enjoy growth and positive performance results predictive analytics would enable an industry to identify the most profitable customers as well as the least profitable ones. Different steps in the supply chain can be tested to identify potential problems and hold ups. Proper analysis of the past pricing and historical sales would allow to reset of favorable profitability form every transaction. The capital cost for the system management has been high in the past but the good news is that Oracle has a new low cost software that would be more affordable to many organizations and some companies have been able to negotiate for lower costs. Daryn Mason of oracle implied that the system has enabled companies and small scale business enterprises and the business as a result have been faced with the challenge to full fill the sudden rush of demand for products and services. Two years ago, Netstore, a UK based information technology and services providing company decided to develop the customer management system Siebel that is part of oracle. Since the Nestore has experienced growth and acquired two more companies. The company has in plans to grow organically and the sales team played an important role in the growth by acknowledgment of their customers and potential customers. Businesses that employ the customer management systems have experienced growth not just from the sales department but also in the financial and commercial departments. Another important benefit of the system Is that user only require minimal training place (College of information and technology 2008).
Our company, castle bingo has several clubs therefore there is need to capture and share data information as never before to improve on customer management and market growth. We are faced with the challenge of high volume data management. Several companies have achieved competitive advantage over competitors through the employment of big data analytics. New analytics are supported by data filters and brute force assaults on massive information sources and the results are integrated with traditional corporate data sources.
The big data and metrics
This refers to data sets that attempt to store, search, share, visualize and analyze vast data quantities. Big data sets have the following characteristics; volume, velocity and variety. But the biggest characteristics is the value of information recovery. Several companies have realized that information acquisition is a competitive advantage and therefore this is the time to implement the big data as It has a capacity to collect large volumes of data. It processes both unstructured and structured data at a high speed. There are different types of data sources namely, operational sources, financial sources, constituency sources and customer sources. Operational and financial contain objective metrics while the customer and constituency sources contain attitudinal metrics. Operational data is used to analyze the quality of the business processes. Example is the use of the customer management system to track the call center interaction quality in terms of response time and call length. The system is also able to measure the financial quality of the company using the financial data obtained from the company`s financial reporting system. Customer data sources from surveys and from online and social media are captured into the customer enterprise feedback system large enterprise companies (Sun & Heller 2012). A company needs to realize what the big data implementation is addressing so that one does not assume that big data only would be enough to produce returns. The application of the big data analytics should results to business returns. The company should not incur unnecessary costs as a result of a discontinuity in big data inputs and the desired business outputs. This would result into a waste of time money and effort. Many companies have adopted lean principles big data to improve on output quality and improve the internal processes. These are:

Define business processes and customer objectives.

Define the business goals and customer objectives then build the business strategies on these goals and objectives.It is important to single out the business challenges and manage each with the objective of customer need satisfaction. The point is how the potential customer would perceive the value of a service. Example; an expensive car can be given away at a price but the chances of winning the price may not motivate the customer to play.

Relevant data set identification

Relevant output would be obtained only if the data identified measure for the outcome. Publishers and technological companies are paid to provide data in return. Due to this cost data should only be purchased if the intended outcome will impact the business positively.

Design analysis

The processes and steps of data collection,storage, analysis and visualization should be integrated fully into the business processes and services.

Analytic and outcome measure implementation

The analytics implemented and data collected should measure the business processes performance and services.

Pull don’t pull principle

Emphasize on analytic processes that are customer demand oriented to ensure the processes are relevant to the value derived by both the customer and the business.

Customer feedback integration in the business processes

The low and poor quality data plus unnecessary analytics should be eliminated from the business process and replace with more insightful analytics to ensure a and perfectly refined outcome. The problem with big data is the application of data. It is important that only useful insights are extracted to avoid unnecessary costs (Hayes 2012)
A database management systems have got several advantages, one of the biggest advantages is that information is made available to all potential users. The system is designed in a way that minimizes data redundancy as the information in it only appears once. The data in the system are accurate, consistent and of integrity since changes can only be made from one point. Data consistency enhances easier data management when many programmers are involved. The system is user friendly as access and manipulation of data is easier as reliance on a specialist is minimized. It is beneficial to access information from one source of storage even though the system faces security challenges. The security risks can be avoided if access is only limited to authorized individuals by the use of passwords (College of information and technology 2008).
Benefits of big data metrics

Financial fraud detection, prevention and remediation

Criminals tend to defraud companies through several strategies therefore the use of big data volumes enables a company to discover any suspicious event that indicate fraud. Several companies have become victims of fraud due to the inability to refine their fraud prediction models. With the big data and a more sophisticated IT team, a company is able to improve on the fraud detection models.

Execution of high value campaigns; This is possible due to improved model execution capability campaigns. The campaigns are intended to market company services to increase market base and popularity.
High performance analytics

High performance analytics makes a difference in terms of fraud and risk prevention.

Improved delinquent collection

Just like prepaid phone services the big data with high performance analytics have improved delinquent collection processes to increase collection. Bingo would allow customers access prepaid services (Spakes 2012).
Ethical and Legal Issues
Confidentiality: There should be an informed consent to allow data sharing so that customer information is not leaked out to the other parties outside the business. This is made possible through restriction to access. The sensitivity of the data should be evaluated before it is put on share point so that only relevant customer information is stored. The company should have a confidentiality review among the employees to ensure that the customer details are confidential otherwise penalties will be charged on the culprits. The institutions that access sensitive customer information like the financial information should have a binding code of conduct that should be signed by all employees in charge so that they comply with customer confidentiality guidelines. The company should investigate about what the national laws say about protecting their customer information so that such laws are integrated into the company`s guidelines.
Conclusion
Social media has played a role in ensuring that companies and organizations understand their customers and their perception on the brands and services. Twitter for example send an average of two hundred million in a day that is an equivalence of eight terabytes of unstructured data, similar to a big data. Data mining from the network systems can not help an organization to achieve the desired goal. The application of the big data principles can help an organization or a company to improve the customer relationship. It is notable that retail conversations are not popular topics in online conversations so conversations about business firms are equally low. Therefore most of the time online conversations do not have enough feedback to allow firms to make meaningful analysis. For this reason a firms have the mandate to develop their own data management systems to obtain credible feedbacks and handle customers a manner that would improve the good customer relationship.
Recommendations

The development of a data management system requires proper planning to ensure that the effort applied produces the company`s desired results, the plan should include;
The project description. There should be a detailed education and understanding of the project research to the organization and the staff involved. This will ensure that the project objectives and goals are clarified.
The staff involved in the should understand the data collection methods to be employed and the format of the data.
Security of the acquired information should be assured in terms of Short term storage system and local backups to ensure that important information is not lost or misused.
Ethical and legal matters in terms of access policies and provisions should be employed to protect customer information.
Long term data preservation should be put in place, I.e. Archives for future reference
The assigned data managers should have clearly set responsibilities and as well as a data management checklist to guide the plan.


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