Careers Business Ownership Preparing Data for Analysis and Triangulation Share PINTEREST Email Print Business Ownership Operations & Success Market Research Sustainable Businesses Supply Chain Management Operations & Technology Marketing Business Law & Taxes Business Insurance Business Finance Accounting Industries Becoming an Owner By Gigi DeVault Gigi DeVault LinkedIn Twitter University of Washington San Jose State University University of California, San Diego Gigi DeVault is a former writer for The Balance Small Business and an experienced market researcher in client satisfaction and business proposals. Learn about our Editorial Process Updated on 04/08/20 A market researcher may analyze several unique data points associated with a topic, also known as triangulation, to obtain an understanding of that topic. Various data collection methods are used to capture different views of an item of interest, as well as validate research. The following information explains how data collectors analyze and triangulate information on a specific topic to arrive at a conclusion or trend. Using Triangulation for Data Analysis Market researchers prepare qualitative data from surveys, interviews, and focus groups for analysis and triangulation, in this case, to align multiple perspectives to understand an area of interest. Researchers create tables containing all of their retrieved data to analyze and capture demographic information that may be important to the study. For example, it is useful to highlight the criteria used to select the study participants, as these attributes can be important to the analysis. The criteria or attributes are the basis for identifying key sort categories. At this stage of the data table preparation, it is helpful to think about the information that will be key to the data retrieval when data tables are merged. Consider the many conditions for which data analysis will be made easier and more accurate by merging tables: Multiple respondents—study participants Focus groups—several respondents Study data from different time periods Data grouped by question type across respondents Adding Columns to Tables So far, the data table would show these columns from left to right: Participant Name or ID, Theme Code, Moderator Questions/Participant Response, and Sequence. The next columns to be added would show selection criteria or participant attributes. For example, a researcher may wish to sort participant responses by their role in an organization, by age, or by gender. The text in rows containing questions asked by interviewers or moderators should be bold, so they stand out visually from the responses of study participants. It is helpful to format the table in landscape view by adding columns for pertinent criteria or attributes that will extend the width of the table considerably. Using Short Labels for Key Sort Categories Sort categories can be represented by numbers, letters, or number-letter combinations. Rather than writing out the sort categories in full words, a researcher may choose to use short tags. For example, organizations are different orchestras around the world. The orchestras can be matched with short tags as follows: Simon Bolivar Youth Orchestra = SYouth Orchestra of Los Angeles (YOLA) = L The roles of individuals in the organizations can also be coded: Conductor = 1Concert Master = 2Musician = 3Music Teacher = 4Festival Director = 5 Conclusion The market research budget of a small business owner or, especially, a home-based business generally does not have room for spending large sums on software to analyze the qualitative data collected for business development. Therefore, you can create a table using an ordinary word processing application to conduct text analysis for qualitative market research. The processes described can be applied to the analysis of quantitative data collected from surveys research, focus group sessions, and in-depth interviews.