So part 2 in my series of posts about improving customer satisfaction, using information from your satisfaction surveys.
Last time we looked at three general lessons:
- There is no average customer.
- Too much and too little are not equally bad.
- You can't talk to customers too much (unless you're selling).
Now I'd like to turn to the question of how you can make best use of a customer survey to inform change. Bruce Temkin has a really interesting blog post in which he argues that research agencies need to be supplying more "contextual insight" and less "statistical analysis" if they want to help their clients. I think this is 100% right.
The interesting thing is that many researchers turn to a statistical fix when they want insight, which is like buying a CRM system to get closer to customers—it might help, but it doesn't address the fundamental need. The challenge is to identify the fundamental questions we want to answer with the research.A survey can basically give you three types of information:
- Attitudes—how customers believe they feel/felt or think/thought
- Behaviours—customer perceptions of what you or they did
- Classification—what you know, or customers are happy to tell you, about who they are
How can the survey help? By moving beyond attitudes (like satisfaction scores) to the behaviours and processes that are driving them. We can start to ask customers how long their last delivery took, and how long they expected it to take. Now we can start to match that data up to our internal measures to reach evidence-based conclusions (rather than speculation) about what is causing the low score. Customers might be dissatisfied because:
- Our performance is bad—we need to speed up our deliveries. But let's not dilute our effort by working across the board. Can we identify particular products or customer types where delivery time is more of a priority? Where are the "cliff edges" in the data—often there are points of tolerance with issues like this where satisfaction suddenly drops off.
- Customers think our performance is worse than it is—asymmetric impact means that they remember the missed deliveries more than the on time ones. Communicating real performance and celebrating success can help, but make sure you don't cheat. The train companies have shot themselves in the foot by using a bizarre definition of "on time" when they communicate the percentage of departures on time.
- Customers' expectations are unreasonable—they want delivery in a time that defies the laws of physics. Communication and controlling expectations is the answer here (although Seth would probably tell you to change the laws!)
The lesson is that survey data does not begin and end with attitudes, even if that's what we're mainly concerned with. Surveys are not a good measure of performance, and to make them useful in improving performance you have to use them intelligently to inform what you do. Find out, empirically, what is causing customers to feel the way they do, and you can start to plan concrete changes that will result in visible gains in performance.