It’s Tuesday afternoon and you’ve just been handed a stack of customer feedback forms with a wealth of information and data to go through and analyse before Friday. You look at the forms; there are numbers, scales, and paragraphs upon paragraphs of commentary.
You pause for a moment and breathe. Where do you begin? What can you even do with all that information?
In reality there are no clear cut answers to your questions. Qualitative Analysis and Quantitative Analysis are both effective tools in their own right and it really depends on what you’re after.
Are You An Explorer or Confirmer?
Quantitative Analysis enables you to interpret the data statistically by which I mean you can make mathematical judgements about the data.
This is what you need if you are:
- Trying to identify patterns over a period of time;
- Deciding how effective a certain variable is; or
- Determining the satisfaction levels of a particular service, etc.
This approach is useful because it can provide you with objective information to understand what has occurred or what will occur. Below is an example of a question which provides Quantitative data:
On the other hand the more subjective approach is Qualitative Analysis. Qualitative Analysis allows you to interpret the information in non-mathematical ways and often focuses on the how and why part of the survey.
Let’s say you want to discover reasons why customers disliked your service, how to improve a product or why one area of your business is better than another, that’s when Qualitative Analysis becomes the more suitable selection for you.
It provides an exploration into individuals’ feelings; uncovering the motivations, desires, behaviour and needs. However, the accuracy/validity of the findings may vary due to the subjective nature in which the information and data is analysed and interpreted.
Below is an example of a question which provides Qualitative data:
Validity and Reliability
Quantitative Analysis is all about hard objective data i.e. non-anecdotal information. As Quantitative Analysis is a ‘numbers game’, the validity and reliability of the data gathered from the customer feedback or survey is much more concrete.
Now I’m not saying that all Quantitative analysis are reliable and valid; the validity and reliability depends on the instruments used and what it’s measuring (the topic of Validity and Reliability is much deep, so we’ll save that for another post) – what I’m simply pointing out is that given that Quantitative tools use numerical and objective data, the level of validity and reliability is higher than the subjective non-numerical data obtained from Qualitative tools.
With Qualitative instruments and data, you are not able to place quantitative measures against your results – but as stated previously, it depends on what you’re trying to achieve with the data that you have. You may not necessarily want such narrow and specific data.
Qualitative data is great to explore your respondents’ perception and to uncover hidden reasons why your customers are happy or unhappy with your products. Whatever the reason may be, you need to remind yourself of what you’re trying to achieve with the data that you have.
How Much Data Do You Need?
The notion of the ‘bigger the better’ applies to Quantitative analysis as, generally, the larger the sample size the better the insights you are able to obtain from the data.
Let’s say for example, you would like to rate your organisation’s professionalism on a Likert Scale of 1-7. You will be able to gain a more reliable perspective of your organisation’s professionalism with a larger population.
A larger sample size enables you to be more confident on how the overall population feels and make a much stronger generalisation.
Putting It All Together
In general in the customer feedback process you want to have both Qualitative and Quantitative Analysis because they complement each other.
For instance in your survey you will want to have a range of questions for quantitative analysis to tell you what you are doing well and what you are doing poorly:
- How good was our customer service from 1 – Very Poor to 7 – Very Good?
- How fast was our delivery time – from 1- Two Weeks to 7 – Same Day
- How responsive were we—from 1- Unresponsive to 7 – Very Responsive
You should also have some questions for qualitative allow you to understand how to improve:
- What did you like about our service?
- What did you dislike about our services
- Where can we improve?
Of course, the next time you run your customer survey you should really have thought through the different types of analysis beforehand. So before you go ahead and jump into your selection remember to:
- Define the objectives and what you’re trying to achieve
- Identify the tools and types of data needed to achieve those objectives
- Make your selection!
Anything else to add? Feel free to comment below and tell us what you think!