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In marketing research, classification of data is a crucial step that facilitates the systematic arrangement, analysis, and interpretation of collected data. Proper classification helps in converting raw data into meaningful information that aids in decision-making. Data classification involves categorizing data into various classes or groups based on common characteristics or attributes. It serves to simplify complex data and highlight patterns or trends that are otherwise difficult to discern. Classification of data in marketing research can be approached from several perspectives, including the nature of the data, the source of the data, and the method of data collection. The various aspects of classification of data are as follows: 1. Classification Based on Nature of Data: (a) Quantitative Data: This includes numerical data which can be measured and subjected to mathematical operations. Examples include sales figures, number of customers, market share percentage, etc. (b) Qualitative Data: This data refers to descriptive information that cannot be quantified. It includes opinions, attitudes, preferences, and perceptions obtained through interviews, focus groups, or open-ended questionnaires. 2. Classification Based on Source of Data: (a) Primary Data: Data collected directly from the source for the specific purpose of the research. It includes data from surveys, experiments, interviews, etc. (b) Secondary Data: Data that already exists and has been collected for other purposes. It includes data from government publications, industry reports, previous research studies, etc. 3. Classification Based on Data Attributes: (a) Nominal Data: This is the simplest form __________ ___ ____ __________ ________ _________ __________ __________ ________ __________ ____ ______.
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