Most companies have operational metrics that they keep about the ways they interact with customers, as well as an abundance of customer information through CRM tools. For example, support centers keep track of metrics such as time to resolve, time on hold, etc. And CRM tools can give us information on account history, such as products purchased, tenure, etc. An ideal situation would be to link these sources of data with customer survey data in order to gain a fuller picture of the customer experience.
In terms of operational data, this information allows you to link perceptual ratings and op metrics to understand where to focus to gain the most improvement in the customer experience. Knowing the actual metrics (ex. time to resolve issue) as opposed to simply the respondent’s perception (i.e., satisfaction, quality) of the time to resolve, adds another dimension to the data that can provide additional actionable information. For example, it can potentially tell you if your customer’s tolerance in the actual time it takes to resolve your issue as well as if there are different levels of tolerance for your customers. Additionally, it can help companies set their operational goals with the customers in mind so that company’s improvements will also help to increase the customer’s experience.
In terms of CRM data, this could help add variables that would be useful in understanding the customer’s experience. For example, if see Account A’s score is significantly declining, CRM data can be useful in seeing what changes have occurred in our relationship with Account A that may help explain this decline. Are we really doing that much worse? Have they changed the products that they are buying with us? Another potential benefit is this could reduce the need to ask customers certain questions in the survey. For example, if we know why the customer called support then do we really need to ask that question in the survey?
As you can see, there are many benefits to linking this information during the analysis of customer survey data; however, there are some things that need to be considered during this process.
· What is the best level to link this data at? Is it for an individual respondent or at an account level?
· Is CRM data kept up-to-date so that we can be confident in its accuracy?
· What do you do if customer’s survey data and operational data don’t agree?
· Should Customer Data be a consideration when setting operational goals?
· What are the other uses of CRM data?
Over the next few weeks, we will be discussing these considerations, as well as providing cautions and benefits surrounding each concept.
Director, Marketing Sciences