5 Steps Involved In Qualitative Data Analysis

A lot of research and observation are involved in building fame and success for a brand. Though the task is not as easy as it seems, many companies hire data and research experts to help them achieve their targets and aspirations. They monitor all the activities of their competitors and try to influence the public’s search results based upon search rankings and optimisation.

Qualitative data analysis involves the collection of data through various methods of observations, one-to-one interviews, focus group discussions, and lots more. The statistical representation of the data is called categorical information – which is based on attributes arranged categorically and properties of an object or phenomenon. When looking to analyse this data through one-to-one interviews or surveys, there is a method which most of the data analysts use for getting the correct information.

Following are the steps involved:

  1. Arranging the data:

The data that analysts receive and collect is very unstructured and seems senseless when looking in one glance. Therefore, researchers first transcribe the data they collect. The first step is arranging it systematically and converting all of it in text format. They can either export the data into a spreadsheet or manually type it. Many computer-based programs and tools are available for computing and arranging the data collected during research.

  1. Organising the data:

After arranging all the information, researchers must organise their findings. They need to set an order for presenting their data systematically. The best way to do so is by going back to the research objectives and then organising it according to the questions asked. Arrange all the research objectives in a tabular form for it to appear visually appealing. Avoid working with unorganised data as that will lead to a wastage of time without conclusive results.

  1. Set code for the collected data:

Coding is the best way to compress complicated and vast data. It categorises and assigns properties and patterns to the collected information. It is an essential step in data analysis for developing theories from research findings. After posting codes to it, build on models to gain an in-depth insight for making sensible decisions.

  1. Validate the information:

Ensure that the information collected has no flaws and is accurate in all aspects. The entire research process involves recurring validation of data and includes two advantages:

  • Accuracy of the research design and methods
  • Reliability of methods for accurate results
  1. Conclusion of the analysis:

All researchers must conclude their data. They should present it systematically in the form of a report. The report should include the method of the research, for example, public opinion research, for concluding, the positives, negatives, and limitations of the study, the suggestions or inferences of the findings, and any related information to support future research. It is crucial to present this report because it helps identify the data for service issues. It also includes the public perception of specific topics and reflects their concerns and opinions.

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