What is a Cross Tab Report?
A cross-tabulation (“cross tab” for short) is a table produced when all the answers to one question are compared with all the answers for another question. Cross tabulated data is useful for showing a side by side comparison of how respondents answered two or more survey questions in order to determine how they are interrelated.
– A Cross Tab Report shows the relationship between two or more survey questions
– It allows you to quickly compare how different groups of respondents answer your survey questions
– It represents the number of respondents falling into each possible pairing of the answers to the survey questions
Why Use a Cross Tab Report?
The Results Overview displays the results for all completed surveys and provides a summary of your data. However, you may need to know whether there is a difference between how groups of respondents answered your survey questions. Any time you need to see if there is a relationship between two survey questions, then you can cross tab.
Consider the example below:
If you were to just look at Results Overview, you would find that 45% of respondents said they would definitely buy the product
– You suspect that there is a relationship between gender and the intent to buy
– To test your hypothesis, you put the gender question in the column of your cross tab and the intent to buy question in the row
– When you read a cross tab report, you read across the row questions to see if there is a difference between the total and the responses to the column question
While 45% of all survey respondents say they will definitely buy the product, you see that there is a big difference between males and females intent to buy. Men are twice as likely as women to say they will definitely buy the product; 60% of males say they definitely will buy compared to 30% of women.
How do I create a Cross Tab Report?
In creating a cross tab, the question that you believe changes or affects the responses to the other question should be the column question. The question responses that are being affected or explained should be the row question. In the example above, the theory is that gender affects likelihood of purchase, so gender is the column question.
You can also apply a filter to a cross tab report. For example, in addition to analyzing the relationship between gender and intent to buy in the cross tab above, you can add a filter for age if you want to analyze that relationship only males and females between 18 to 34 years old.
What types of questions can cross tabs answer?
For customer satisfaction surveys, find out:
– How do satisfaction levels differ between repeat and first-time buyers?
– What is the relationship between how satisfied customers are and whether they would recommend our product or service?
For employee surveys, find out:
– How do employees in specific departments feel about our company?
– Is there a relationship between office location and satisfaction (cross tab)? Does that relationship still exist when we control for length of employment? (apply filter to cross tab)
For awareness and usage surveys, find out:
– Is there a difference between men’s and women’s intent to purchase my brand?
– Does age affect my brand awareness?
Zoomerang also provides you with over 100 professionally designed online survey templates to help you create a best-in-class survey in minutes. With Zoomerang, you can quickly and easily create online surveys and receive the fast feedback you need to make important decisions. Remember: the information you need is only a survey away!