{"id":107429,"date":"2020-07-21T04:35:03","date_gmt":"2020-07-21T11:35:03","guid":{"rendered":"https:\/\/www.questionpro.com\/blog\/?p=107429"},"modified":"2023-08-16T08:20:28","modified_gmt":"2023-08-16T08:20:28","slug":"research-webinar-series-cross-tabulation","status":"publish","type":"post","link":"https:\/\/www.questionpro.com\/blog\/research-webinar-series-cross-tabulation\/","title":{"rendered":"Cross-tabulation in research"},"content":{"rendered":"

Have you ever wanted to take your survey data and discover patterns and relationships between your audience groups, but aren\u2019t sure how to have those reflected best on paper? Researchers and insights managers need to understand the \u201cnumbers\u201d or the data before claiming that the research conducted was successful in providing business-applicable results. <\/span><\/p>\n

The problem is that the raw data you initially get won\u2019t give that for you and can even be daunting and misleading to review.<\/span><\/p>\n

The first question you ask yourself when initiating a market research<\/a> study is, \u201cDoes my audience want to buy this product or service?\u201d But you also have to consider all of the different types of customers that represent your audience. Brands differentiate between customers based on demographics, psychographic segmentations<\/a>, and various purchase behaviors and trends.\u00a0<\/span><\/p>\n

You know that there can be multiple different themes and outcomes, but how can you translate your data into results, and further into theories? How do you find those relationships? How differently will one audience group feel towards a product or service than another? What specifically are those differences?<\/span><\/p>\n

Join our <\/span>webinar on how to use cross-tabulation for actionable business decisions<\/span><\/a> and make the most of your survey data.<\/span><\/p>\n

LEARN ABOUT:<\/em><\/strong> Theoretical Research<\/a><\/em><\/p>\n

Cross-tabulation in survey research<\/h2>\n

When running a survey report<\/a>, you\u2019ll first have your basic frequency analysis – or the \u201coverall\u201d insights from the respondents who completed your survey, which gives you a general impression of what your audience \u2018on the whole\u2019 is thinking and feeling. For example, you\u2019ll see what percentages of your total audience selected each response to a question. <\/span><\/p>\n

And you\u2019ll be able to review the demographic representation of the total audience participating in this study. While insightful, this usually does not fulfill the insights or the big-picture objective you, the researcher, were initially seeking out for this study; more data-mining and in-depth analysis<\/a> needs to be done.<\/span><\/p>\n

So what is <\/span>cross-tabulation<\/span><\/a>?! It is a comprehensive breakdown, and a mainframe statistical model displayed in the form of banners or pivot tables, composed of rows and columns. What these tables do is allow you to analyze and measure the interaction between two variables. <\/span><\/p>\n

The rows (or the x-axis) lays out the questions and their difference survey responses. At the same time, the columns (or the y-axis) represent the variable(s) you want to run a comparison on (*sometimes this can also be based on a survey question). This facilitates identifying different patterns, trends, and correlations between parameters within your study – whether they are or aren\u2019t mutually exclusive.<\/span><\/p>\n

Cross-tabulation allows you to go beyond raw data and will enable you to see how one or more questions (or variables) correlate with each other. Cross-tabulating also takes data that looks like it can have several possible outcomes and helps you \u2018zero in\u2019 on a single theory by drawing these trends, these comparisons, and these correlations between different factors in your study.<\/span><\/p>\n

To know more about effectively using cross-tabulation in your research studies, <\/span>join our webinar<\/span><\/a>.\u00a0<\/span><\/p>\n

When and how is Cross-tabulation used in surveys?<\/h3>\n

When running crosstabs, you\u2019re able to apply to following types of groupings as variables:<\/span><\/p>\n