Use Case: Cross-tabbing 2 Dimensions

by Phil A.

This use case examines how to set up your analysis in Advanced Exploration if you want to crosstab 2 variables that are Dimensions, and view this data for a specific time period.

Some common examples that this use case can be used for include:

  • Task Completion by Purpose of Visit
  • Visit Frequency by Path
  • Task Completion by Browser Type
  • Any crosstabs that involve two different demographic data variables

 

For this use case, we'll address the following request: 

 

I want to view respondents’ Task Completion by their Purpose of Visit.

 

 

Step 1: Select your Columns (X-Axis) and Rows (Y-Axis)

To analyze Task Completion by Purpose of Visit, you would place Task Completion (Dimension) as a Row, and Purpose of Visit (Dimension) as a Column.   

 

By default, including only Dimensions in your analysis shows the data in table format.  The chart and table type for a view can be modified by using the “Show Me” option provided in the toolbar.

 

Step 2: Determine the format in which the data will be shown

The “Color”, “Shape” and “Text” options provided in the Marks card allow you to specify how to show this data in the table or chart.  For this example, the data will be shown in “Text” format.

Since respondents’ Task Completion is being evaluated, click and drag the Task Completion variable from the Dimensions list to the “Text” option in the Marks card:

 

 

Step 3: Determine how the data in the output will be calculated

Now that we have specified the variables to be included in our analysis, and that the data should be displayed as text, you must specify how the data will be calculated (e.g. as a percentage or an average). 

For this step, the items below can be performed in the menu shown when right-clicking the Task Completion variable in the “Marks” card:

 

Convert this variable from a Dimension to a Measure (Measure > Count). This will update the data to provide the sample sizes for each item in the table.  

 

Then, specify the type of calculation that should be performed in the table. Since we are interested in the proportion of respondents who were able to complete their Purpose of Visit, we want to view the data as a percentage (Quick Table Calculation > Percent of Total).

 

Finally, since we are working with percentages, we must specify whether the Columns or the Rows in the table should add up to 100%.

By default, the data is calculated so that each row in the table adds up to 100%.  To change it so that the data is instead calculated where the Columns add up to 100%, Compute Using > Table Down

 

 

When viewing data in table format, it is always recommended that you include the Grand Totals for both the Rows and Columns so that you can confirm how the data in the Rows and Columns are being calculated.  You can add these Grand Totals via the toolbar.

 

 

Step 4: Specify your time period

By default, the crosstabs that you create show data for all respondents that completed your survey in the last 3 years.  To focus your analysis on a specific time period, bring the "Time_RespEnd" variable (Dimension) into the Filters card.  

 

Step 5: Convert your analysis into a different chart type (optional)

By default, including only Dimensions in your Columns and Rows will show your data as a table.  You can change the chart type for your analysis by using the "Show Me" option in the toolbar.  

 

 

Additional Use Cases

Aggregate Analysis

Cross-Tabbing 1 Dimension And 1 Measure

Analyzing Data For Multi-Select Questions

Analyzing Respondent-Level Open-Ended Responses

Analyzing Close-Ended Data In Map Format

 

Trended Analysis

Trending A Dimension Over Time

Trending A Measure Over Time

Trending A Crosstab Of 2 Dimensions Over Time

Trending A Crosstab Of 1 Measure And 1 Dimension Over Time

 

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