In this discussion, Dr. Gary Rhoads, PhD (Enterprise Feedback Management (EFM) Guru) goes into the important details of managing and measuring customer feedback and loyalty. With examples and data he shows how an organization must watch many feedback indicators (and not just Net Promoter for instance) and then link them to business metrics such as profitability and stock price.
Part 1 – after a fairly long introduction, the real meat starts after about 6 minutes. #1 rule for measuring customer / employee satisfaction is to have multiple metrics and correlate them in your own organization with profitability and performance. How loyal are your customers? Do they see you as best in class? Are they passionate about what you do? Do they intend to buy more from you? Will they promote you within their network? Which tools should you be using? The most cost effective tools that will get you the information is Gary’s answer.
Part 2 – how do we measure, should it be a general random sampling or should it be granular examining in detail where customers have a problem and drilling that back to a process or employee. This determines on your objectives, whether it is Product Management or developing frontline employee training programs. Many organizations measure quantitative data and ignore the qualitative – Gary’s advice is to ALWAYS MEASURE THE QUALITATIVE DATA. He gives valuable advice on classifying the tens of thousands of verbatims, bucketize them and then analyze that in detail and determine the frequency of responses in each area, trend those and understand the top 5 responses you are getting . Do this without burning out your employees and having them wade through all of the verbatims.
It is all very well creating measurement, but the real question is what do you do with all of that data? Most CEOs will complain about having all of this data and not doing anything with it.
Descriptive Statistics: For example, we will have some response data on the question: “I trust the financial advice given by XXX organization”. The organization looks at the mean level score and acts – reacting blindly to descriptive statistics can be a huge mistake. You need to do a deeper analysis by looking at why customers are saying what they are saying. In the example above, a low score for institution XXX, may be indicative of consumers not trusting the entire banking industry.
When we look at measures, we need to study which are the leading and which are the lagging indicators? Observing the correlations between the indicator and the performance measure. E.g. Hours spent on employee training is a leading indicator of customer satisfaction (the lagging indicator. Increasing the employee training hours may have a positive effect on repeat purchase.
Part 3 – We should be measuring leading and lagging indicators are regular and frequent intervals. The trick is also to have the right lagging indicators. Percent change in sales or profitability are better lagging indicators than absolute sales or profitability values as the change reflects how effective management actions have been.
Employee loyalty and satisfaction will also have effects on customer loyalty and satisfaction and ultimately profitability. He terms this as linking soft data to hard data. We need to learn what internal things in our organization affect our business performance. (This is balanced scorecard theory). Roades concludes by saying how business and investment decisions will be driven by looking how pulling internal levers effects the external performance measures.