Metrics_ How to Improve Key Business Results - Martin Klubeck [99]
In the case where you are selling only one product or service, and the need for repeat purchases are rare, the satisfied customer is still your best salesperson. Rather than measure repeat customers, you may want to measure referrals. Remember the story of my laptop purchase (Chapter 7)? A week later, because of the selection, price, but mostly the customer service, I brought my daughter to the same store to buy her laptop. Normally I wouldn't buy another computer for three or four years.
Of course, this store sold more than computers and they should measure whether I return to buy other technology from them. A purer example would be my first book. I'm proud of Why Organizations Struggle So Hard to Improve So Little. It is a good read. But how many sales should I expect to the same customer? In this case you might think total sales are the only measure I need. But, I could learn from looking at usage measures also. Imagine if I could get the number of books ordered by one person or one organization; or the number of referrals—sales in which the buyer was influenced to buy my book from the encouragement of another reader. Another measure could be the number of reviews and the ratings that accompany those reviews. Of course, if I sell another book (like this one), I would want to measure repeat customers if I could. How many people buy both books? If the reader liked one, hopefully they liked it enough to read the other, expecting a certain level of quality and information.
The reason Fred Reichheld's predictors of promoters and detractors has merit is because word of mouth advertising—the kind you can't buy—is critical to a business's growth. New customers are nice to have, but repeat customers become your foundation for continued success and future growth.
In the case of our Service Desk, we expected customers to run into information technology issues on a quarterly basis. If they were calling only once or twice a year, it might indicate that they are using a different source for solving their IT problems. This might include just trying to solve their issues on their own. If they were calling weekly it might mean that the organization's product line and service catalog had too many defects or faults—requiring frequent assistance.
The expectations can be the same, but since we were looking originally at the expectations for a full year, we logically shouldn't expect as high an amount of first time callers (unique users) for a three month period. Since the department felt that the usage was healthy for the period reported, we chose to review the data first. If you aren't sure, a simple tool is letting the measures tell you what the expectations should be.
Figure 10-9 gives us the picture without expectations so that we can use the data to determine what is “normal.”
Figure 10-9. First time callers: three-month running totals (without expectations)
Based on the picture presented by the measures on a running three-month total, the norm looked to be between 5 percent and 15 percent. When I spoke with the team, they felt that five percent was too low. Even though this would create a picture that showed them having Opportunity for Improvement more often, this felt “right to them.” They also felt that the Exceeding Expectations should be set at 20 percent, making the expectations range from 10 percent to 20 percent. Because of the measures, I pushed them to find out why they chose 20 percent. The answer was that “15 percent was just a little too low.” So, I pressed some more. “So, why 20 percent?” And as you may have guessed, the answer was, “it's the next value.”
So I set the range at 10 percent to 17.5 percent. Don't let conventions keep you from setting the correct expectations.
Don't let conventions keep you from doing the right thing.
Figure 10-10 shows the three-month running total expectations for first time callers.
Figure 10-10. First time callers: three-month running totals (with expectations)