Cross Tabulation Analysis Explained
A cross tabulation (or crosstab) report is used to analyze the relationship between two or more variables. A cross tabulation report will have the x axis as one variable (or question) and the y axis as another variable. This type of analysis is crucial in finding underlying relationships within your survey results. (or any type of data!)
Generally survey results are presented in aggregate only – meaning, you only see a summary of the results, one question at a time. Cross tabulations take this one step further and enable you to see how one or more questionss correlate to each other . This type of analysis can reveal a relationship in your data that is not initially apparent.
A Real World Example
If you were a store owner and asked the question "Do you like our products?" to customers, would the answers help improve your business? Of course! But without cross tabulation, it would be hard to gain further insights.
The data table below is from a sample survey in this scenario. You can see people generally do not like this company’s products. But does that tell the whole story? No, it does not!
Here is the same data below, but now we'll create a cross tabulation report with the respondents’ gender (asked in a prior question). A graph is also incorporated to better visually represent the data.
Walking Through the Example
Using above table, we can see the columns shaded in blue are the total survey responses. The question is asking if respondents' like the products at the store. This question has been cross tabulated, with age range from another question, which are shaded in green.
In the table, we can see that the total of the blue columns (47), matches the total of the green columns (47). All data has been accounted for, and is properly segmented by gender. Looking at the green shaded cells we can now look at the relationships in our data. We can see right away that it appears males tend to love the stores products and females tend to dislike the stores’ products. This result can also be seen in the graph above.
A feature unique to SurveyKing, is the ability to toggle response counts with response percentages. This makes your data table clean and easy to follow along with. You can also export this table to a spreadsheet at any time within the results section.
The Importance of Cross Tabulation
Find Hidden Relationships:
Only with cross tabulation, were we able to see that a younger age group liked our products. Without this, a marketing team might have seen the survey results and thought, "Wow our products aren’t liked, maybe we need to re brand". In reality though, the younger age group does like their products!
Clean, Useable Data:
Cross tabulation makes it easier to interpret data, which is beneficial for researchers who have limited statistical knowledge. The clarity offered by cross tabulation helps deliver clean useable data that be to improve decisions throughout an organization.
Getting Comparisons Set Up in SurveyKing
From the results screen click on "Comparison Report". This will bring up a screen where you can choose the segments you want to look at for the report. Choose from the dropdown the criteria question you want to compare. Select your answer choice then click "Add Segment". This segment will now be shown on the left hand side of the screen. When you have added all segments you wish, simply click the "Create Report" button.
Compatible Survey Questions
At this time only certain questions are compatible with this report type. We are working to improve our reporting capabilities.