DYK # 6: Did you know that you need qualitative AND quantitative data to drive your business performance?
We often hear conversations about quantitative VS. qualitative data. Whereas in actual fact, the conversation should be about how best to leverage combined quantitative AND qualitative data.
And worry not, there’s no technical jargon here, it’s meant to be easily understood for everyone 😉
Before we get into it, let’s look at what qualitative and quantitative data actually is.
Qualitative (qual) data:
Typically unstructured data, meaning text, words, audio or even video
It can come from your survey verbatim or other unsolicited sources, such as telephone conversations, social media comments and chats, etc.
Quantitative (quant) data:
Typically structured data, e.g. numbers-based, countable, or measurable
It can come from survey questions and metrics (e.g. CSAT, NPS CES), or your backend systems, e.g. your billing system, CRM, etc.
While quantitative data tells you What is happening, qualitative data gives you the Why behind your numbers and helps you explain drivers of performance. In terms of understanding and driving Customer Experience (CX) success and business performance, you will need both types of data, and you need to be able to combine that data in your analysis.
What do I mean by that?
Let’s stay in the world of CX and look at an example.
If you measure e.g. Customer Satisfaction (CSAT) through a survey, the CSAT score tells you what is happening, e.g. customers are satisfied / not satisfied, or 80% or your customers are satisfied, that sort of thing.
If you want to understand why your customers are satisfied, you need a bit more information. You can look at driver questions (if you have those as part of your survey), to understand your overall satisfaction score. E.g. if you ask specifically about staff friendliness, facility cleanliness, price, etc. and analyze what drives or weighs down satisfaction based on those driver questions. The challenge with that is (as always with surveys), that you only hear feedback to questions you ask. Meaning if you don’t ask about something that’s important to your customer, you won’t know about it, leaving you potentially missing out on actual drivers of your satisfaction performance and making poorly informed business decisions.
That’s where qualitative data comes in. Most often we look at verbatim data from surveys, but you can also leverage other data sources (for more on that topic, check out DYK # 4 - data sources).
By analyzing qual data, whether it’s solicited or unsolicited, you can uncover what drives or reduces satisfaction, based on what your customers tell you, in their own words. E.g. your driver questions may not cover things that are newly emerging, such as the impact of COVID on the experience your customers have with you. Your customers may tell you that they feel uncomfortable if your staff doesn't wear masks when interacting with customers. If you have a text analytics solution in place, you will pick up on “COVID” and “mask wearing” as a driver for dissatisfaction, and if you have a good text analytics solution you can even understand the impact mask wearing has on your CSAT score and the overall experience. Customers may choose not to visit you any longer, or not as frequently, which has a direct impact on your business performance.
To stay with our above example, if you look at your quant data you may notice a drop in CSAT and a drop in guests, visitors, bookings, etc. but quant data doesn’t tell you why you’re seeing that drop. By combining your quant with your qual data you can identify “mask wearing” as a crucial driver of dissatisfaction as well as dropping booking rates, and in turn revenue. Being able to collect and analyze both types of data and analyze them together is immensely powerful to drive your CX improvements as well as your business performance.
We hope that was a useful insight for you. As always, if you have any questions or would like to chat, do not hesitate to get in touch 🤓
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