How the data is analyzed and visualized for Loop Questions?

How the data is analyzed and visualized for Loop Questions?

Looped Questions in Dashboard

1. Report Page
Each question in the Loop has a visualization chart. Within each chart, a Loop drop down allows users to filter results by a specific loop.

Example Visualization for Loop: Question based


Example Visualization for Loop: Stimulus based



Other Tools on the Report Page

  • Filter: Looped questions can be used in Report Page filters. When a looped question is selected as a reference question, users must specify which loop iteration the filter should be based on.

    In the example below, Shopping Experience is a looped question asked across three stores (i.e. loops). If a user wants to filter respondents who selected “Somewhat satisfied” or “Very satisfied” for Harvest Mart, they can select Harvest Mart as the loop iteration to apply the filter


  1. Participant Info: Users can also choose to display Participant Info with open ended verbatims based on a looped question. Each looped question is split by loop iteration in the list, allowing users to select participant information based on responses from a specific loop.

In the example below, the user can choose to display answers to Shopping Experience from the Harvest Mart loop.


  • Analysis Variable: Looped questions can be used to create Analysis Variables. When defining Analysis Variables, users can currently apply rules only across all loops; we currently don't support creating separate Analysis Variables for individual loop iterations.

    In the example below, if users want to create an Analysis Variable showing the Top 2 results for Shopping Experience, the same rule must be applied across all stores (i.e., all loops). 

However, when using this Analysis Variable as a filter, users can specify which loop iteration the filter should be based on.
In the example below, the user can choose to filter on Top 2 selections from the Shopping Experience T2 Analysis Variable in the Harvest Mart loop.


  • PowerPoint Export: When exporting the report to PowerPoint, the export reflects any filters applied on the dashboard Report Page. Page-level filters are clearly shown on the PowerPoint cover page, and loop filters appear next to the sample size for each looped question.

    In the example below, if users select the Harvest Mart loop for Shopping Experience on the Report page, the PowerPoint export will display the Harvest Mart results on the corresponding slide, with the loop name shown next to the sample size.


2. Crosstabs Page

For each Crosstab tab or sheet, users should first select whether they want to work with Standard (Respondent Level) data or Stacked (Loop Level) data for their analysis. By default, the Crosstab runs on Standard (Respondent Level) data. However, if users want to analyze differences of a looped question across loops, they should switch to Stacked (Loop Level) data.

For example

  • To compare gender differences in the shopping experience of Harvest Mart, users should use Standard (Respondent Level) data, selecting Shopping Experience_Harvest Mart as the Stub and Gender as the Header.


  • To compare shopping experience across Harvest Mart, PurePick, and The Green Mart, users should switch to Stacked (Loop Level) data. They should then select Shopping Experience (which stacks responses from all loop iterations) as the Stub and Brand Based Loop (which indicates the loop iteration for each data row) as the Header.



Please note that changing the data level on the Crosstab tab will remove any headers, stubs, and filters applied at the current data level on that tab. To keep these settings, users should open a new tab to view analysis results at a different data level.



3. Data Export Page
For projects with a loop question, we offer two data structure - 1) Standard (Respondent Level); 2) Stacked (Loop Level)

Standard (Respondent Level) - default export


For respondent level data (where each respondent has one row), columns for the looped questions are added into the standard project data file. Looped questions are split by loop iteration, with each variation shown in separate column(s). The column names indicate which loop iteration the data corresponds to. If the loop question contains a single choice Question A with three loop iterations (Loop 1, Loop 2, and Loop 3), there will be three separate data columns in the data file: Question A_Loop 1, Question A_Loop 2, and Question A_Loop 3.

In respondent level data, the order in which loops were presented to participants is included in the export. If a loop question contains three loops, the dataset will include three separate columns: one indicating the loop shown first, one for the loop shown second, and one for the loop shown third.

For example, in the case below, Shopping Experience is a question within the Brand-Based Loop, which includes three loops: Harvest Mart, PurePick, and The Green Cart. From the data file, we can see that Respondent ID 1358065 was shown Harvest Mart  first, followed by The Green Cart. This respondent answered “Somewhat satisfied” for Shopping Experience for Harvest Mart, and “Very satisfied” for The Green Cart.




Stacked (Loop Level)

Users must tick the box Stacked (Loop Level) Export in the Format Options to export the Loop Level data.

Loop level data differs from our current respondent-level structure. Instead of one row per respondent, the data is restructured so that each participant has multiple rows - one for each loop iteration they were shown. An additional column is added to indicate which loop option each row corresponds to. If the loop includes a single-choice Question A with three loop iterations (Loop 1, Loop 2, and Loop 3), the data file will contain only one column for Question A. If Respondent 1 is shown the loop 2 and 2, their data will appear in two separate rows - one for each loop iteration - with a new column called CurrentLoop specifying whether the row is for Loop 1 or Loop 2. In addition, the order in which loops were presented to participants will be captured in a column called LoopPosition.

Using the same example as above, Respondent ID 1358065 appears in two rows because this respondent was shown two loops: Harvest Mart and The Green Cart, as indicated in the CurrentLoop column. Harvest Mart appears first, followed by The Green Cart, as shown in the LoopPosition column. Now, there is a single column for Shopping Experience, with data from all loops stacked together. This respondent answered “Somewhat satisfied” for Harvest Mart and “Very satisfied” for The Green Cart.



4. AI Coding & OE Data Visualization

For open ended questions within a loop, you can visualize results by individual loop iterations. This applies to all types of analysis including Summary and AI Coding.





However, when creating and managing codes for these looped OE questions, you can do so across all loop iterations at once rather than separately for each loop. This helps save time and effort.
On the AI Coding interface, you can also export the OE data in Stacked (Loop Level) format by selecting the corresponding option.



5. SmartSummary Page

Looped questions are not supported on the SmartSummary page in the current version.


Link to other dashboard features:
To learn more about filters, click the article here.
To learn more about variables, click the article here.
To learn more about crosstabs, click the article here. 
To learn more about participant info, click the article here.
To learn more about data export, click the article here.



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