Understanding Qualitative Data Collection through In-depth Interviews

Analysis of qualitative data does not follow a formula which requires then a researcher to familiarize themselves with the research area through reading findings from interviews. The researcher must seek a deep understanding of the information collected before becoming objective in analyzing the data. Qualitative data analysis is time-consuming, and researchers should be ready to deal with research area for longer periods to provide actual information and data on the research topic as explained by Bryman, A. (2007). Researchers need to have the capacity to accommodate different views to ensure maximum collection of information from different people.

Interviews take three forms; the structured, semi-structured and unstructured of question administration as noted by Shkedi, A. S. H. E. R. (2014).The structure from is done verbally by administering predetermined questions and is usually used when interviewing respondents with literacy problems. The interviewer does not ask to follow up questions to answers given by the respondents. The semi-structured interviews consist of predetermined questions but the participants are allowed to discuss in detail on any issue. This form of interview is flexible and allows for maximum data gathering as participants are not limited to their interview. This type of interview is mostly used in different fields to gathering formation as it has an in-depth coverage of topics.

The unstructured forms of interview often have no organization and interviewers do not have predetermined questions for the interviewee explained by Shkedi, A. S. H. E. R. (2014). This from is time-consuming as ideas and theories do not follow any pattern hence the participants tend to wander across unrelated topics

This form of data collection involves grouping of six to eight individuals who share same knowledge on particular fields to discuss an issue relating to that area. The group discussion is moderated and recorded by the researcher, and the interview is less structured. Through this method of data collection enables an interviewer to collect information from a wide audience and provides a broader understanding of attitudes and beliefs that different people hold as explained by Buckler, S. (2015).

In carrying out interviews, researchers need to realize that articulation of ideas and opinions vary among the correspondents. This requires the researcher apply different techniques to understand the attitudes of the respondents noted by Gottlieb, M. R. (2016).

These techniques include asking clear questions during the interview. This requires the interviewer to use words that can be understood by the respondent. The question structure should be short, precise and incomprehensible words should be avoided. These questions should be administered singly to avoid confusion and misinterpretation.  The questions should be open-ended to avoid limiting respondents from expressing their thoughts and views on an issue.  

Types of Interviews Used in Qualitative Data Collection

For researchers to understand the attitudes of the respondents, the question structures should allow them for individuals to express experiences before their feelings. This allows for a chronological expression and gives respondents time to internalize their feelings by expressing their experiences as explained by Galman, S. C. (2016). To deepen discussions, the researcher should probe by requesting the respondent to provide more information on the area they have already commented on, for example, asking them to give more details.

Researchers need to clarify questions and responses to avoid misinterpretations on their part. This allows for confirmation of what the researcher has interpreted, and the respondent could express more in the research area. Sensitive questions should be avoided as respondents could be irritated or uncomfortable to carry on with the interview (Chirban, 2007). The researcher should create an environment that is not hostile towards the respondent from expressing them.

The process of data analysis involves to identification, examination, and interpretation of findings to answer research questions. These methods require three steps to identify crucial information from the data. They include thematic content analysis, narrative analysis, and deductive approach on the research findings.

The researcher finds common features in the data collected which requires the researcher to be familiar with the data and label them. This enables linking of data that explains same issues and the link them to the research question themes. The researcher needs to develop a write-up of the research findings to create coherency of the data gathered.

The narrative analysis requires the researcher to make sense of the research stories gathered. This involves analysis of these stories by providing meaning; these stories are compared to establish interpretations. The researcher may create a new story from stories gathered to provide more insight to the research questions.

A deductive approach can be applied where research has predetermined research questions. Therefore, data that is irrelevant are omitted from the findings. This method is used where information is already available, and the researcher uses them to test already preconceived theories. The methods require the researcher to have an in-depth understanding of the data collected.

Customer satisfaction

Factors contributing to consumption of strawberries; freshness, size, and the ripeness

Consumer distribution across the country; which cities have higher consumption and why, fruit demand

Factors that determine the purchase of strawberries; situations in which customers consume the fruit

Features and attributes that respondents consider before purchasing strawberries

Methods of Analyzing Qualitative Data

The current image of strawberries

 The factors that contribute to the negative or positive image of the strawberries

Strawberry purchase motivators

Customer attitudes

What attracts new customers to purchase strawberries?

Consumption distribution of strawberries

Classification of consumer demographics to establish age and sex   

Promotion of strawberries consumption

Facilities available for tasting strawberries

Opinions of customers of strawberry tastes; how they could be used in promoting the fruit

Results

 From interviews carried out, the findings from the respondents include:

Many students are average consumers hence the pricing on the strawberries is affordable to a larger student population.   Many consumers prefer medium-sized strawberries. Therefore, there is more demand on medium sized the fruit. Young children influence the purchase of the strawberries across the demographics while teenagers have the least consumption levels especially teenage females.

Many families use the fruit as a snack, dessert or for special occasions.  From the interview, many people take the fruit as a desert after dinner. Many consumers take the fruit without any accompaniment while a considerable number eat as cream or with ice cream. Many households do not consider the fruit as a treat

The freshness of the fruit is a major contributing factor to its purchasing, and during their season they are mostly bought. The major consumers are young children due to the appealing look of the fruit. Teenagers are the least consumers of the fruit which females are having a high negative attitude towards the fruit. The affordability of the fruit attracts new customers who are willing to try out new products.  

Many customers are willing to try new products, and through tasting strawberry and dishes made strawberries. This influences attitudes resulting in an increase in the product sales. Many respondents prefer using these tasting facilities before trying new products. Products tasting is an important promotional tool that could increase strawberry purchase.

Analysis of information collected on the consumption of the strawberries involves familiarization of the data collected from the different correspondents. The scope of information is internalized to help in categorizing them. Information on customer satisfaction, customer attitudes, and promotion of the fruit labeled and grouped together. All information categorized should fit the theme selected to avoid misinterpretation of information. Under customer satisfaction factors such as sales, loyalty, opinions, and views determine the categorization of data into the theme.

This involves the use of the predetermined framework and pre-existing theories to analyze information. From interviews conducted the researcher establishes information relevant to the research questions and deducts information that does not relate to the topic. This involves scan through information collected and identifying information that is irrelevant to the topic and eliminating them (Harding, 2013). In the process themes and concepts are developed to suit the research topic. From the strawberry case study, three themes can be constructed that is; customer satisfaction, customer satisfaction, and strawberry promotion.  These themes fit the research scope as it seeks to provide an understanding of consumer scope of the fruit across the country. This analysis does not provide in-depth analysis of the research findings rather categories into themes.

Conclusion

The use of in-depth interviewing in qualitative data collection is widely recommended for academic research work as learners become the research tool and get totally immersed in the research area. The research technique allows researchers explore new areas through probing which provide the new dimension to the research topic as noted by Chirban, J. T. (2007). This research technique requires the researcher to have an understanding of the research literature and the requirements. The researcher must be sensitive to different situations and be flexible to different perspectives, opinions, and views from the different interviews that are carried out in the research process.

References

Bryman, A., (2007). Qualitative data analysis. Los Angeles [u.a.: SAGE.

Buckler, S., (2015). Qualitative data analysis: Part 1.

Chirban, J.T., (2007). Interviewing in Depth: The interactive-relational approach. Thousand Oaks, Calif. [u.a.: Sage Publ.

Galman, S.C., (2016). The good, the bad, and the data: Shane the Lone ethnographer’s basic guide to qualitative data analysis.

Goldman, A. E., & MacDonald, S. S., (2007). The group depth interview: Principles and practice. Englewood Cliffs, New Jersey: Prentice-Hall.

Gottlieb, M. R., (2016). Interview. New York: Longman.

Harding, J., (2013). Qualitative data analysis from start to finish. London: SAGE.

Kelle, U., Prein, G., & Bird, K., (2008). Computer-aided qualitative data analysis: Theory, methods, and practice. London: Sage.

Shkedi, A. S. H. E. R., (2014). QUALITATIVE DATA ANALYSIS. S.l.: CONTENTO NOW.

Sullivan, P., (2012). Qualitative data analysis using a dialogical approach. Los Angeles [Calif.: SAGE.