Lots of data. But do you understand your customers?

Good ratings, but few repeat purchases. More website visitors, but hardly any additional enquiries. Interest in an offer, yet many objections in sales.

Anyone who jumps to the conclusion that this is a pricing, product or communication problem risks investing in the wrong place. Qualitative market research helps to develop possible explanations and to examine them critically.

A metric is not yet an explanation

Asma Qureshi puts it aptly in Quirk’s:

“behavioral data is not the same as behavioral understanding.” ^[1]

A longer time on page can mean interest – or difficulties in use. The metric alone does not determine which explanation is correct.

Thomas Krombach describes a similar problem on marktforschung.de, using AI-based attention screening as an example: predicting which packaging elements stand out does not yet answer which message people understand. ^[2]

For companies, this raises a practical question: What else do we need to find out before we act?

The decisive information often lies in the context of use

An illustrative example: an app is rated positively but rarely opened. The team suspects usability problems and plans a redesign.

A diary study could provide a different explanation: the right occasion for use rarely arises, or the information needed is already available elsewhere. A follow-up interview can explore these situations in more depth. This would lead to different measures than a new design.

The example is hypothetical. However, it shows why the choice of method should depend on the open question. Interviews uncover individual experiences; observed use can reveal usability barriers; diaries document recurring situations.

Dirk Wieseke of KERNWERT describes the benefit on marktforschung.de as follows (translated from German):

“The context is not only explained, but above all made visible.” ^[3]

Qualitative research must question itself, too

A convincing participant quote does not make a robust study. Writing in Research Live, the trade publication of the UK’s Market Research Society, Mark Thorpe calls for more context and analytical depth in qualitative research. ^[4]

This affects everyday research practice: good analysis also looks for contradicting cases. It distinguishes between observation, self-report and interpretation.

Interviews do not automatically provide proof of causality. A purposively selected qualitative sample usually does not allow statistical projection. Memories and diary entries are selective, too.

For clients, this means: ask to be shown what a recommendation is based on – and what uncertainty remains.

Three questions before your next study

Which decision is pending? A research brief should state what needs to be decided afterwards. This determines which insights are relevant.

Whose experiences do we need? In B2B studies, for example, a job title alone is rarely sufficient. Users, buyers and budget holders can assess the same offer differently. Recruitment must fit the research question.

How do we test the consequence? An identified barrier may suggest a concrete improvement. Whether it actually works can be examined, depending on the question, with a pilot, an experiment or a quantitative follow-up study.

Not every problem requires every method. The next step should reduce a clearly defined uncertainty.

Our standard at WMM

Qualitative research is particularly valuable when companies see a change but do not yet sufficiently understand its meaning.

Our aim at WMM is to bring together the research question, the right participants and a transparent analysis. A good result shows what the data support, which explanation remains open and which next step makes sense.