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Metrics from Faith to a Reliable Science
从信赖到可靠的科学的指标
One of the metrics that loyalty based marketers have developed is the Net Promoter Score (NPS) which allows to compute the net effect of customers’ recommendations on a business. The NPS was developed by Reichheld (2006)and can be calculated by considering all the customers which have given their opinion on their willingness to recommend a company on a scale of 1-5. The customers can be divided into 3 more groups those who scored the maximum 5, the truest advocates, those scoring 4 which are more uncertain and theones in between 1 and 3 not likely to recommend and more likely to generate negative word of mouth therefore called detractors. The NPS can than be calculated by subtracting from the percentage of promoters the percentage of detractors.
衡量底层的营销人员开发的指标之一是净推荐值（NPS），可以计算的净影会响客户对产品的看法。NPS是由赖克尔德（2006）提出的，通过考虑所有的客户给了他们的意见可以计算出NPS，他们愿意推荐一个公司的规模为1-5。客户如果对其评分为3以上，则取得较大优势，能够吸引最真实的倡导者，那些得分4，在1和3之间的公司大都不可能被客户认可。更容易产生负面口碑的因此被称为批评者。 NPS可以通过计算得出，从发起人的百分比减去批评者的百分比。
The fundamental finding of Reichheld (2006) research was that ‘NPSleaders outgrow their competitors in most industries by an average of 2.5times’. To improve the number of advocates customers organisation can crossthe emotional signature analysis with the loyalty profile of their http://www.ukassignment.org/scyxgl/ customers and determine on which cluster of emotions it should focus upon. NPS isvery useful because it captures a different form of value for the firm than thesales of higher level products, the value of referrals and advocacy.
Customer Lifetime Value (CLV) is a more popular customer metric (Guptaand Lehmann, 2005). In the case of higher education institutions, can beinteresting to calculate at customer segment level. It offers important infor-mation on how much the institution should be willing to invest to recruitand retain a student. The CLV general formula as reported by Gupta andLehmann (2005) is based on the general assumptions of constant margingrowth m over time, constant retention rate r and discount rate i and infi-nite time horizon.
The reason why this metric should be calculated at segment level is that,after graduation the nature of the relationship between student and universitycan be very different.
The best option would be to calculate different retention rates depend-ing on the student segment. In the case of master students, retention ratecould be calculated based on the fact that the student is participating to theuniversity reunions and seminars and has created a communication chan-nel between his company recruiters and the university. While in the caseof students proceeding to further education, PhDs and research programs,the retention rate would be based on how many of them will proceed inSouthampton University (less than 1% according to last year statistics).
Therefore if CLVMScis the lifetime value of the students which do notintend to do further studies and CLVP hDthe one of continuing students and r1and r2=(n continuing in soton/tot.continuing) are the respective retentionrates formula 3.1 could be adapted as following mT,mRand mCare all the profit margins or cost reductions that the uni-versity expects to obtain on tuition fees, recommendations to other studentand employers and margins from student participation to alumni reunions,seminars and foundraisings.
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