I gave this talk at the Score Conference in Boston in April 2011. I cover linkage analysis to show how companies can use this method to understand the causes and consequences of customer satisfaction and loyalty.
Linkage analysis is the process of merging or linking different customer databases together and then analyzing the overall database to uncover important relationships.There are there general types of linkage analyses: The first is Financial – in which we can calculate the dollar value of improving customer loyalty. The second is Operational – in which we identify the operational metrics that are closely linked to customer satisfaction. The third is Constituency – in which we identify how employees and partners impact the quality of the customer relationship.
Linkage analysis helps answer important questions that help senior management better manage its business. 1. What is the $ value of improving customer satisfaction/loyalty?2. Which operational metrics have the biggest impact on customer satisfaction/loyalty?3. Which employee/partner factors have the biggest impact on customer satisfaction/loyalty?The bottom line is that linkage analysis helps the company understand the causes and consequences of customer satisfaction and loyalty and thereby helping senior manager better manage its business.Understand the causes and consequences of customer satisfaction/loyalty
Points to ConsiderRelationship SurveyEnsure respondents have, at least, some influence in purchasing decisionsDifferent Types of Linkages are Possible
Using linkage research, companies can gain important insight about the various causes and consequences of customer satisfaction and loyalty.One, companies will be able to understand how to best manage the customer relationship with operational metrics. Two, they’ll be able to manage the relationships of other important constituencies like employees and partners so they can deliver exceptional customer experience to the customers they serve. Three, they will be able to quantify the value of the CEM program by quantifying the impact that the program has on financial metrics.