We live in an age of information. More than just an interesting sounding catchphrase, businesses today are sitting on vast amounts of data, more than any other point in history. Data tracking internal processes, data tracking supply chains, and data tracking customers amongst others.
Naturally, customer feedback is a part of that. While a simple feedback survey seems quite straightforward from the outside, when you think about the amount of data that can be generated through a typical customer experience management (CEM) program, the numbers can quickly become quite impressive. Most programs will receive 30 or more responses per month per location. For a brand with 250 locations that means close to 100,000 customer surveys each year. If you consider that most surveys will be made up of 20 or more questions, then suddenly if you’re a customer experience program manager you’re looking at 2 million individual points of customer feedback.
The question is – What insights are locked inside all of that data?
Some are obvious, location comparisons, average performance, overall scores, trending etc… answers to those questions have always been the biggest values of a CEM program. In fact if a program is well designed and the questions asked are of an appropriate nature, these are exactly the type of insights that can drive great brands to continue executing on a day-to-day basis.
But 2 million points of data are a lot. What else might be hidden in that data? Sometimes there’s more to the data than just the surface level trends, it just takes a bit of deeper analysis to get to it. Today’s technology tools allow anyone with a deeper level of curiosity to dig deeper and discover some of the additional layers of nuance within pools of customer survey data.
Some more nuanced questions that can be answered with customer survey data would include:
- Which factors in the experience hold the most weight when measured against overall satisfaction?
- How overall satisfaction is perceived across different demographic segments?
- How different product categories impact satisfaction?
- How can I measure a cross section of all of these questions looking at products and their impact against satisfaction across different demographics?
The challenge is being able to segment the data appropriately and easily. That’s where a flexible data analysis product can come in handy. Rather than having to rely on external resources program managers should be empowered to be able to quickly slice out interesting segments of customer feedback to make informed decisions. Or at least be able to use these slices of data to be able to follow a single train of thought through to some kind of conclusion or hypothesis.
In today’s world having data is no longer enough. We need to be able to harness the power of actually using it, to be able to effectively drive change.