Qualitative Data VS Quantitative Data

Qualitative Data VS Quantitative Data


The difference between qualitative data and quantitative data is that, qualitative answers the why? and the how? more in depth than quantitative data using people's hidden interpretation. Qualitative data helps understand the different meanings people place in their experience, which is something quantitative data can't answer completely. Also, qualitative data  can be collected in many different ways.

Some of the ways qualitative data can be collected is by using focus groups, individual depth interviews, and case studies. Using this types of data help the researcher extract feelings, emotions, motivations, perceptions and consumer language or self-described behavior. In the other hand quantitative data lack techniques of providing the insights needed to make those business decisions.

Quantitative data measures consumer behavior, which answer the questions related to how much, how often, how many, when and who. Quantitative data is collected more often thru survey and is more use for theory testing. One of the biggest difference between qualitative data and quantitative data is the interpretation. Qualitative data is reduce to numeral codes and maintain a clear distinction between facts and judgements, while qualitative data is more verbal.

Why do senior executives feel more comfortable relying on quantitative data than qualitative data?

Senior executives feel more comfortable relying on quantitative data, because qualitative data is too subject too human errors and bias in data collection and interpretation. They believe such data provides an unstable foundation for expensive and critical business decisions.

How qualitative research company can lessen the senior executives skepticism?

The best way to lessen the senior executives skepticism is by doing some of the following:

• Carefully using literature searches to build probing questions.
• Thoroughly justifying the methodology or combination of methodologies chosen.
• Executing the chosen methodology in its natural setting rather than a highly controlled setting.
• Choosing sample participants for relevance to the breadth of the issue rather than how well they represent the target population.
• Developing and including questions that reveal the exceptions to a rule or theory.
• Carefully structuring the data analysis.
• Comparing data across multiple sources and different context.
• Conducing peer-researcher debriefing on results for added clarity, additional insights, and reduced bias.

In conclusion, there are many reasons to believe that qualitative data takes less time to get results and is being use more and more in many companies, and you can't avoid human error by analyzing the data collected following the steps above.

Business Research Methods (Eleventh Edition) Donald R. Cooper/Pamela S. Schindler