Role of information system in customer relationship management Coursework

Role of information system in customer relationship management - Coursework Example How to ensure strong customer service and satisfaction Customer satisfaction and service are vital components in the survival and progress of any business. it is for this reason that organizations invests heavily in ensuring that customer service reaches a level that will satisfy and woe the customer towards coming for more. Businesses need to maintain customers in a manner that will make them appreciate the brand, products or services being offered by the businesses. This paper looks at ways in which a strong customer service and satisfaction can be maintained in a business. First, know the needs of every customer in the market so as to avoid forced creation of demand where it is none existent. Secondly, it is important to perform tests with a view of building an understanding of the desires of consumers within the market segment. This helps build up innovative ideas useful in identification and solving possible problems that may arise due to customer expectation about the product o r service the business offers. Thirdly, being true to your customers can help the business a greatly. All deliveries of goods to customers should always be done at the right time. Where delivery may not be possible on the agreed schedule, proper communication with the customer is vital. Fourthly, plan well and perform periodic training of the team you work with in order to uphold business reputation and trust. It is also important to train a team that will enhance flexibility and effective communication skills. Fifthly, always appreciate your customers. It is worth sending thank you messages to your loyal customers. This strategy will likely yield positive results that help in positive growth of the business. Moreover, always create loyalty programs among your customers. This can be done through unique gift offers or special promotions targeting long time customers in the business. Always approach issues related to your customers in a mature manner as though you are dealing with a l ong time friend. This can be done by being sincere to them on issues that may arise in the day to day running of the business. It is important to promise what you can achieve other than giving unrealistic expectations. This is because empty promises tend to anger and frustrate customers making them shun any future transaction with the business. It is for this reason that a successful business need to set correct expectations since it helps in retention of customers. Develop a customer philosophy that will direct the way employees interact with clients. The philosophy developed should be able promote respect and constant appreciation of customers. This is a key component in customer satisfaction and retention. Lastly, develop a quick response time whenever there is a blame game in business transactions. Effective communication and admittance of a mistake can really yield marvelous results in the long term. This should be followed with a communication on what you plan to avert similar mistakes in future. Customer Service System Customer service refers to various business practices aimed at providing services to clients during and after a business transaction. These services are aimed at building customer satisfaction and retention. Customer service system refers to blending of procedures, people and technology with a view of serving customer needs in a way that will promote profitability and achievement of business objectives. It is important to note that implementation of an effective client service system may be quite difficult when all the stake holders does not understand its importance. In addition, all the stake holders should be willing to buy into using the system otherwise its contribution to the business may be futile. There are numerous reasons why organizations need

Bankruptcy prediction Research Paper Example | Topics and Well Written Essays - 3250 words

Bankruptcy prediction - Research Paper Example e year correctly classify the dozen or so listed industrial companies which will fail, but will incorrectly identify about 120 of the remaining 600 as likely to go bankrupt. In fact, analysts who might use the models t help them produce their credit ratings are likely to try them out before relying on them and making them self-fulfulling. It therefore seems unlikely that a misclassification error rate of 1 in 5 for surviving listed companies would be acceptable, even allowing for the substantially greater costs of incorrectly identifying a bankrupt company as sound when compared to those of misclassifying a surviving company as a prima facie failure." Richard Morris This paper examines whether accounting based measures effectively capture publicly available information about a firm's probability of bankruptcy. Section 2 Section 3 describes model and research methodology which includes details about the sample selection procedures, variable estimation and descriptive statistics are reported in section 4. Section 5 present and discuss the results, while Section 6 summarizes and concludes the paper. Also include a list of variables in Appendix A. 1. Literature Review 1.1 Accounting ratios Professor Edward Altman invented a model called Z-Scores by applying multivariate formula to forecast bankruptcy probabilities of the firms over 30 years from 1965-1999. In 2000, he extended his research throughout the year 1999 by improving accuracies of 96% one period prior to bankruptcy to 70% five annual reporting periods prior. Ohlson (1980) also developed a bankruptcy prediction model with logit analysis using a number of bankruptcy firms that were traded on NYSE and AMSE during the 1970s. Begley Joy et al (1997) critised the estimation models of Altman (1968) and...In fact, analysts who might use the models t help them produce their credit ratings are likely to try them out before relying on them and making them self-fulfulling. It therefore seems unlikely that a misclassification error rate of 1 in 5 for surviving listed companies would be acceptable, even allowing for the substantially greater costs of incorrectly identifying a bankrupt company as sound when compared to tho se of misclassifying a surviving company as a prima facie failure." Richard Morris Professor Edward Altman invented a model called Z-Scores by applying multivariate formula to forecast bankruptcy probabilities of the firms over 30 years from 1965-1999. In 2000, he extended his research throughout the year 1999 by improving accuracies of 96% one period prior to bankruptcy to 70% five annual reporting periods prior. Ohlson (1980) also developed a bankruptcy prediction model with logit analysis using a number of bankruptcy firms that were traded on NYSE and AMSE during the 1970s. Begley Joy et al (1997) critised the estimation models of Altman (1968) and Ohlson (1980) were not performed well by using 1980's data.