Group
Group blocks are organizational containers that allow you to structure your survey content and control how blocks are presented to respondents. This is a block in which other blocks (questions, transitions, etc.) can be nested. Groups provide powerful features for randomization, iteration, and experimental design, making them essential for complex survey structures.
Group types
There are 3 distinct group types available: Group, Loop, or Cell Allocation. Each serves different organizational and experimental purposes:
Default group (group type)
The "group" type group is a simple container that allows you to include other blocks inside it. It serves to organize these blocks and can also display their content in a random order.
Block rendering options
In a default group, you can control how blocks are presented to respondents:
Default order
Blocks are rendered in the order they appear in your survey structure.
Random order
Blocks are presented in random order to reduce order bias.
Random block presentation helps eliminate order effects and provides more reliable data by ensuring that block position doesn't influence responses.
Selected number of blocks
You can configure the group to show only a selected number of blocks from the available blocks, useful for:
- Reducing respondent fatigue
- Creating shorter survey versions
- Implementing partial block rotation
This feature is particularly useful for A/B testing scenarios where you want to show different subsets of content to different respondents.
Loop group
The loop allows you to repeat the nested blocks inside it a number of times equal to the number of defined iterations. Loop groups enable iterative presentation of content, perfect for repeated measurements or multi-stimulus evaluations.
Iteration creation
In this example, each block nested in the loop will be executed twice, as there are two iterations.
Create iterations that repeat the contained blocks multiple times, with each iteration potentially having different variables and images.
Add iteration | Add variable
Variable functionality
The advantage of the loop lies in its ability to ask similar questions while using different variables.
For example, in the first iteration, variable 1 will take the value "Brand 1" and variable 2 will take the value "car". This allows you to create dynamic content that changes with each iteration.
Loop groups support iteration variables that can be referenced throughout the loop content.
See the referencing page for detailed information on using iteration variables within your survey content.
Iteration images
Within a loop, you have flexible options for image handling:
Image selection options
When working with blocks inside a loop, you can choose between:
- Importing an image: Use a standard uploaded image
- Using iteration image: Use images specific to each iteration
Iteration images allow you to show different visual stimuli for each loop iteration, essential for product testing, ad evaluation, or concept research.
Iteration order options
Control how iterations are presented to respondents:
In order
Iterations are presented in the sequence you defined.
Random
Iterations are presented in random order to reduce order bias.
Experimental plan
Iterations follow a predefined experimental design plan for sophisticated research methodologies.
Experimental plan ordering allows for complex research designs including Latin squares, balanced incomplete block designs, and other advanced experimental structures.
Cell allocation group
Cell allocation allows the creation of multiple cells, which enables the generation of different versions of the questionnaire while maintaining homogeneous samples through pairing.
Cell configuration and pairing
Set up multiple cells (groups) within the cell allocation group:
- Define the number of experimental cells needed
- Each cell acts as a separate group container
- Respondents are automatically assigned to cells
Pairing functionality
Pairing takes into account previous responses to ensure that respondents allocated to different cells share similar characteristics, in order to avoid any bias in the study.
This sophisticated pairing system:
- Analyzes respondent characteristics from previous questions
- Distributes respondents across cells to maintain balance
- Reduces potential bias by ensuring comparable groups
- Maintains sample homogeneity across experimental conditions
Cell display order
It is possible to choose the order in which the cells are displayed:
Defined order
Cells are presented in the sequence you specified during setup.
Random order
Cells are assigned randomly to provide additional randomization.
By pairing
Cell assignment follows the pairing algorithm to optimize sample balance.
Experimental design benefits
Cell allocation groups enable:
- Between-subjects experimental designs with balanced samples
- Random assignment with intelligent pairing
- Bias reduction through demographic balancing
- Complex multi-factor experimental setups with controlled variables
Use cases:
- A/B testing with balanced demographic groups
- Control vs. treatment group studies with matched samples
- Multi-condition experimental research with bias control
- Comparative evaluation studies requiring sample homogeneity
Cell management
Each cell within the allocation group can contain:
- Different sets of questions
- Unique content variations
- Distinct stimuli or materials
- Separate experimental conditions