When contemplating on customer loyalty and satisfaction, you will probably end up conducting a survey to find out if your customers would recommend your company to friends and acquaintances. In such case, calculating the Net Promoter Score (NPS) will be included in the survey. This is a good example of the possibilities of quantitative research; true to its name, quantitative research measures quantities and percentages. Thereby it generates comparable data (i.e. figures) to support and accelerate your decision-making processes. Let us imagine that, according to the survey results, a customer gave you an NPS score of 7, which means they would recommend your company with certain reservations. Therefore, the customer is ‘Passive’. ‘Passives’ do not spread the good news about your company like ‘Promoters’, but neither do they put forth negative comments like ‘Detractors’. In a way, you might be relieved, but also disappointed with the results. What is my customer thinking? What could we have done better? Did we not meet all their needs? How can I hold on to my customer in the future as well?
Numbers tell only part of the story
For the purpose of enlightening the above-mentioned issues it is difficult, if not impossible, to prepare a survey which questions could be answered with numbers or pre-populated answers. Qualitative research methods, such as individual or group interviews, are used to analyse quality per se, that is, your customer’s experiences, perceptions and opinions, instead of quantity. Qualitative research yields for example information on currently concealed needs or signals that indicate possible future needs. In the best-case scenario, possible mistakes in the customer encounter can be fixed with reasonable effort and costs. As a result, you will have a loyal customer also in the future. After all, finding a new customer is more difficult and costly than maintaining an already established customer relationship.
As the pioneer of knowledge-driven leadership, our goal in all our surveys is to produce a sufficient amount of high-quality numerical data. Moreover, we want your survey to reveal the respondents’ views behind the numbers. Therefore, when we are measuring customer satisfaction and loyalty, we also examine why the NPS score was 7 (instead of a full 10). Which factors influenced the score? In our surveys, we use various kinds of tasks and particularly open-ended questions, all aimed at discovering the respondents’ arguments and experiences as well as the underlying values and feelings.
Deeper customer understanding is of commercial importance
Once the data gathering is completed and you get your hands on the results, the numbers are easy to study; you can simply look at how they have developed from the previous years. However, reading through and interpreting the answers to the open questions turns out to be more arduous. There is a lot of data, and it can be difficult to grasp the overarching themes based on the bits and pieces of information. The respondents have used a lot of time and effort to convey their ‘messages’ to you, which is why the open answers should not just be skimmed through. The open answers include suggestions for further development, customer needs as well as praise and criticism, which may have significant commercial value to you. For this reason, analysing the open answers and drawing conclusions based on them is also important. This is to ensure that the valuable information can be utilised by your company. An analysis of the open answers can also create a foundation for implementing other more advanced analytical methods. For example, if we want to apply statistical modelling to the NPS index, a qualitative analysis can be used to quantify the open feedback into a form that is understood by different statistical models.
Side by side or taking turns
A survey is in order when we are implementing continuous measurement with the aim of obtaining comparable data on the experiences of customers, potential customers or staff members. However, the results can be more than just a bunch of numbers; instead, it is useful to complement the questionnaire with qualitative elements that provide a deeper understanding of the respondents’ experiences and their behaviour. If your company has yet to implement the KPIs that support knowledge-driven leadership, a qualitative study can be a good tool during the planning phase of suitable quantitative measurements. Or, if a continuous measurement system is well underway, qualitative research can, for example, provide an insight into the different “whys” in the different stages of a customer relationship, when numbers are not enough to explain for instance the changing purchasing behaviour of customers. Indeed, surveys and qualitative research can be implemented alternately and side by side; this way, the tools of knowledge-driven leadership can be kept up-to-date and accurate. The research method that is best suited for finding out the necessary information is determined by what we want to know. Therefore, qualitative and quantitative research go hand in hand: they complement each other instead of competing with one another.
The author is working at Innolink as the Research Manager in Qualitative Studies
D.Sc. (B.A.), Research Manager, Qualitative Studies
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