Data can be classified as qualitativeor quantitative. Qualitative research is exploratory and seeks to find out what potential consumers think and feel about a given subject. Qualitative research aids in identifying potential hypotheses, whereas quantitative research puts hard numbers behind these hypotheses.
Quantitative research relies on numerical data to demonstrate statistically significant outcomes. The Internet can be used to gather both qualitative and quantitative data. In fact, the communities on the web can be viewed as large focus groups, regularly and willingly sharing their opinions on products, markets and companies.
When both qualitative and quantitative research are used, qualitative research usually takes place first to get an idea of the issues to be aware of, and then quantitative research tests the theories put forward.
The main differences between quantitative and qualitative research are represented in the following table.
| Quantitative | Qualitative | |
|---|---|---|
| Data gathered | Numbers, figures, statistics, objective data | Opinions, feelings, motivations, subjective data |
| Question answered | What? | Why? |
| Group size | Large | Small |
| Data sources | Surveys, web analytics data | Focus groups, social media |
| Purpose | Tests known issues or hypotheses. Seeks consensus, the norm Generalises data | Generates ideas and concepts – leads to issues or hypotheses to be tested. Seeks complexity Puts data in context |
| Advantages | Statistically reliable results to determine if one option is better than the alternatives. | Looks at the context of issues and aims to understand perspectives. |
| Challenges | Issues can be measured only if they are known prior to starting. Sample size must be sufficient for predicting the population | Shouldn’t be used to evaluate pre-existing ideas. Results are not predictors of the population. |
