Quantitative research methods are designed to collect numerical data that help measure variables. It is structured and statistical with objective and conclusive results. It uses a grounded theory method that relies on data collection that is systematically analyzed. Quantitative research is a methodology to use when you need to draw concise conclusions from your research and make predictions of the results.
Qualitative research is a methodology designed to collect non-numerical data to gain insights. It is non-statistical and semi or completely unstructured. Qualitative data collects information that seeks to seek in-depth information on the topic rather than just measuring its worth numerically. This type of research measures opinions, views, and attributes versus hard numbers that would be presented in a graph or a chart. Qualitative researchers seek to delve deeper into the topic of the study to gain information on general perceptions and attitudes.
Data analysis is broad, exploratory, and downright complex, and when you simplify it, it boils down to two methodologies: Qualitative and quantitative data.
The differences between qualitative and quantitative research are:
- Qualitative research is a method of inquiry that study the way society and people think and feel. Quantitative research is a method of scientific and empirical approach that uses more statistical and objective techniques.
- Qualitative research follows a subjective approach whereas the approach of quantitative research is objective, as the researcher is uninvolved and attempts to precise the observations and analysis on the topic to answer the inquiry.
- Qualitative research is exploratory while quantitative research is conclusive.
- The reasoning used to synthesize data in qualitative is inductive but the reasoning in quantitative research is deductive.
- Elements in the analysis of qualitative research are words, pictures, and objects while those in quantitative research are numerical and statistical data.
- Qualitative research is holistic in nature while quantitative research is particularistic. In essence, qualitative research develops the initial understanding, and quantitative research schedules a final course of action.
- Qualitative research is conducted with the aim of exploring and discovering ideas in the ensuing process, while the purpose of quantitative research is to examine the cause and effect relationship between variables.
- The methods used in qualitative research are in-depth interviews, focus groups, etc whereas the methods of quantitative research consist of structured interviews and observations.
- Formulating hypotheses: Qualitative research helps you gather intricacies and details of a particular study, which you can to initially being your research with. Those ideas can become hypotheses to be proven through quantitative research.
- Validating hypotheses: Quantitative research will give numbers that can statistically be analyzed to validate the hypotheses. Was there a mass opinion or was it a subjective perception or attitude? The hard facts obtained will help objectively make decisions for the target audience as a whole.
Objectives In Market Research
B2C market research
While B2C market research usually uses quantitative methods, the use of a fresh product or service facilitates the use of a qualitative methodology. A quantitative approach requires that the respondent has the knowledge or experience to answer the questions asked in the questionnaire. In the case of a new product or concept, however, it is hard to quantify sophisticated consumption perceptions without a proper glimpse of understanding of its structure. With qualitative methodology, it observes new and untainted responses and reactions, collects both verbal and socially cued impressions. This helps understand the responses in-depth, enough to hopefully quantify it later on.
B2B market research
In B2B research, professionals are harder to catch hold off for quantitative research methodologies like surveys, one-on-one interviews, etc. For this reason, it is often more efficacious to conduct qualitative interviews for in-depth insight and reduce wastage of resources and time on comparatively superficial data.
There are many versatile approaches to both quantitative and qualitative data.
A market research method that employs researchers to study how consumers behave in market conditions under different sets of variables and non-variables.
Guided or semi-structured techniques that investigate the consumer’s response to a product or brand.
3. Focus groups
A group of 6 – 12 consumers gathered in an online or offline space based on their predetermined criteria to identify their perceptions and behavior about market demand and supply.
A series of semi-structured questions that investigated customer inclinations, reviews, requirements, characteristics, or expectations.
Secondary research employs information that has already been compiled by other entities.
Qualitative methods: Qualitative research may be carried out in a number of ways based on the nature and context of the study. These options give researchers the opportunity to remain flexible while collecting and interpreting data. Some common approaches are ethnography, action research, phenomenological research narrative inquiry, and grounded theory.
Quantitative Methods: Multiple techniques of statistical research are vital in conducting quantitative market research. Some of the most common and widely used forms are descriptive research, correlational research, and quasi-experimental research.
Data Analysis And Interpretation
Qualitative Data Interpretation
Qualitative data analysis is mainly categorical. Data here is not described through numerical values or patterns, but through instead with descriptive context. Traditionally, narrative data is gathered by conducting a variety of techniques like:
- Observations: These are mainly behavioral patterns that occur within observational groups.
- Documents: Different types of documentation resources can be coded and divided based on the material contained.
- Interviews: One of the most popular forms of narrative methodologies, the interview approach allows for high-focused data segregation.
Quantitative Data Interpretation
If quantitative data interpretation could be described in one word, it would be numerical. There is rarely anything guaranteed in data analysis due to the subjectivism on how to go about versatile methodologies, but one thing guaranteed is that quantitative research is all about numbers and statistics. Quantitative analysis refers to a set of processes by which numerical data is analyzed. More often than not, it involves the use of statistical modeling such as standard deviation, mean and median. The most common statistical terms are:
It represents a numerical average for a set of responses. When dealing with singular or multiple data sets, the mean represents a central value of a specific segment of numbers. It is the sum of the values divided by the number of values within the data set. Other similar terms used are average and arithmetic mean.
Another statistical term commonly appearing in quantitative analysis is the standard deviation. It reveals the distribution of the responses around the mean and describes the degree of consistency within the responses.
This is a measurement gauging the rate of a response in a data set. When using a survey, for example, frequency distribution has the capability of determining the number of times a specific ordinal scale response appears.
Typically, quantitative data is measured by visually presenting correlation tests between two or more variables of significance. Different processes can be used interchangeably and comparisons can be made to ultimately arrive at a consensus. Other signature interpretation processes of quantitative data include Regression analysis, cohort analysis, and predictive and prescriptive analysis.
The term “mixed methods” refers to an emergent methodology of research that advances the systematic integration of quantitative and qualitative data within a single investigation or sustained program of inquiry. The basic premise of this methodology is that such integration permits a more complete and synergistic utilization of data than do separate quantitative and qualitative data collection and analysis. Thus for better optimization, we should take the best of both worlds of qualitative and quantitative research.