Qualitative Versus Quantitative Analysis

Market researcher, there are a number of different research methods available. The first basic classification for research methods is the difference between qualitative and quantitative research. Quantitative research is based on numbers, while qualitative is not. This difference has implications in particular with respect to the way the data is analyzed, but there are also implications for how it is gathered as well. Examples of qualitative research methods are interviews, focus groups, surveys and reviews of primary source documents.

Quantitative methods can also be done with surveys and interviews depending on the question, but also can reflect on market data such as sales and market share (ORAU.gov, 2016). The reason market researchers use these different methodologies is that they are best used in different situations. For example, the techniques that are used in quantitative research are discrete and often are replicable.

The downside to quantitative methods is that there is no real room for open-ended questioning, thus there are limits on the type of knowledge that a researcher can acquire. An example would be asking members of a focus group to rate their impressions of product on a scale of 1 to 10. This is quantitative research, and those numbers can be analyzed in a number of different ways. But those numbers do not answer the question of why the consumer feels a certain way.

With quantitative research, the data can usually be analyzed much more quickly, because quantitative data can be analyzed with relatively large sets (ORAU.gov, 2016). This is a disadvantage, conversely, with qualitative data. Qualitative data takes longer to interpret because there are no techniques for mass analysis of the different data points. The research must attempt to codify and analyze qualitative data manually. Furthermore, it is difficult to generalize these types of answers, and because of that it might be difficult to extrapolate them to a larger population (Sheragy, 2016).

However as discussed, as powerful as quantitative data is, it is not rich in the sense that it cannot express non-numeric concepts well. With qualitative data, there is more richness, more room for open-ended response. What this means is that while quantitative data can help a researcher to answer a specific question, qualitative data can answer more questions, and even open up new ones. There is a level of depth and detail possible that cannot be reached with quantitative data.

There is even the ability for a researcher, in something like an interview, to introduce new questions, making some forms of qualitative research inherently more flexible (no author, 2016). One of the disadvantages of qualitative, and by that score an advantage of quantitative, is the cost. Qualitative research typically requires more time to gather an equivalent number of data points. Interview, focus groups and surveys deliver rich data, but the number of participants is small. With quantitative data, the data sets can be massive.

An example of this would be, for example, gathering sales data. A company could interview people and ask them when they are most likely to buy an umbrella, for example. The answers may not be accurate because people remember things differently from how they occurred, and it would take a long time to get only a few hundred responses.

But a retailer can gather quantitative sales data, overlay that with weather data, and realize that 50% of umbrella sales come in days when it is not raining in the morning, but starts to rain in the late afternoon. This data, if gathered nationwide, is not only more accurate and robust, but is also going to come in with tens of thousands of data points instead of just a few hundred, and will come in at a lower acquisition cost as well.

Qualitative data is often more useful when launching a product. The reason for this is that without a track record, quantitative data either will not exist or will be costly to acquire (such as through test marketing). A series of focus groups yielding qualitative data will not only help understand how the launch might go, but might also help to understand if any changes need to be made prior to launch.

Where there is no significant historical data set, quantitative data is less useful, a disadvantage for that form, and qualitative data then can have an advantage. All told, there are a lot of reasons to use either of these forms of data in market research. The key factors are how much time you have, how much money.