Companies gather data to understand the market and customer needs. They do this by conducting qualitative and quantitative data analysis. While quantitative data deals with numbers, qualitative data research explains words, observations, and interpretations. These explanations get presented as theory.
Qualitative data analysis gives a better understanding of the opinions and viewpoint of the customers. It also helps organisations interact with buyers. Data collected through qualitative research is mostly through interviews, questionnaires, focus groups, observations, etc. Let us check some of the methods used in the process:
Content analysis: Qualitative data obtained through questionnaire, surveys etc. have varying responses for the same questions. Analysing those responses and detecting a pattern among them helps in categorising. The content analysis gets used to derive interpretations, meanings, and relationships of the themes, concepts, words, and phrases. It helps in simplifying and grouping vast data.
Discourse analysis: This method involves studying the written and spoken language in a social context. It considers the underlying intentions of responses by deconstructing the data to understand the vocabulary, structure, grammar, and tonality. Companies use this data analysis method to derive conclusions on user intent.
Grounded Theory: Firms use this technique to understand different circumstances in business processes. They also use it to study qualitative data collected through focus groups, interviews, etc. The grounded analysis focuses on comparing phenomena with similar occurrences to develop theories. These help in deriving conclusions for a problem.
Narration analysis: This technique interprets qualitative data collected from open-ended questions, interviews, and observations. It brings clarity to data obtained in the storied form. Companies use them for understanding customer needs and expectations which helps in customer segmentation.
Logical analysis: The data obtained in qualitative research gets clustered. It also causes problems like incomplete and fragmented responses in the case of surveys and interviews. Thus, it requires implementing a logical analysis to interpret such responses and derive conclusions. It is a widely used method to make up for the low quality of data.
These are some of the commonly used qualitative data methods by researchers to explain complicated facts. Organisations use it to learn about their customers and use it in customer segmentation according to demographics, behaviour, needs, and psychographics.