Qualitative data is defined as information that can be observed and recorded, but which cannot be quantified or measured. This type of data is often used in fields such as sociology, psychology, and anthropology, where researchers are interested in understanding human behavior. In the text analytics industry, qualitative data is often used to understand the sentiment of a customer or to identify the topics that are most important to them.

Qualitative data is often contrasted with quantitative data, which is information that can be quantified or measured. Quantitative data is often used in fields such as business, economics, and engineering, where researchers are interested in understanding trends and relationships between variables. In the text analytics industry, quantitative data is often used to measure the frequency of certain words or phrases or to calculate overall sentiment scores.

So while qualitative and quantitative data both play important roles in text analytics, they are used for different purposes. Qualitative data helps us understand the why behind customer behavior, while quantitative data helps us understand the what and how.

Systematic Approach to Qualitative research

There are a number of different approaches to qualitative research, but all share a common goal: to understand human behavior. The most common approach is called ethnography, which involves observing and recording people’s behavior in naturalistic settings. Other approaches include case study research, grounded theory, and phenomenology.

Qualitative data can be collected in a number of different ways, including interviews, focus groups, observation, and document analysis. Researchers often use multiple methods to collect data, as this can help them to triangulate their findings and get a more complete picture of the phenomenon under study.

Qualitative data is usually analyzed using methods such as content analysis or thematic analysis. These methods involve breaking down the data into smaller pieces (codes) and then looking for patterns and themes.

Qualitative data can be very helpful in understanding customer behavior. However, it is important to remember that qualitative data is subjective and can be open to interpretation. Therefore, it is important to use qualitative data alongside other forms of data, such as quantitative data, to get a more complete picture of customer behavior.

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