What Is An Online Survey Experiment?
An online survey experiment assigns respondents to different conditions inside a survey, then measures outcomes after treatment exposure. Domandata supports this workflow with blocks, Flow, random assignment, condition arms, quotas, preview paths, and exportable condition data.
The critical pieces are the treatment blocks respondents see, the assignment rule that chooses the arm, the outcome questions that follow exposure, and the export fields that prove which path each respondent took.
Flow: Conditions and Routing
Build The Experiment Structure
Step 1: Build the study sections. In Block Builder, create blocks for consent and screening, treatment materials, outcomes, demographics, and end screens.
Step 1: Add study section blocks
Step 2: Add treatment material. Use Content Blocks or media stimuli for treatment text, images, videos, vignettes, or instructions.
Step 2: Add a content block for treatment material
Step 3: Add outcome measures. Place outcome questions after the treatment blocks they are meant to evaluate, and keep primary outcomes close to the exposure.
Step 3: Choose outcome question type
Step 4: Open Flow. Create experimental conditions and name each arm clearly.
Step 4: Open Flow and create conditions
Step 5: Set assignment rules. Configure random percentages, stratification, or by-variable assignment with your sample allocation plan in mind.
Step 5: Set assignment rules
Step 6: Preview each arm. Use Preview to confirm respondents see the intended treatment, outcomes, and end screen.
Step 6: Preview each experiment arm
Add Checks And Sample Controls
Use comprehension, attention, or manipulation checks when your protocol calls for them. If each arm needs a target sample size, set quotas for condition arms. For expected cell sizes, review sample allocation before publishing.
- Comprehension checks: place them after instructions or treatment material when respondents must understand the task before continuing.
- Manipulation checks: decide whether they are diagnostic, an outcome, or an exclusion rule before launch.
- Quotas: set arm-level targets only after you know the total sample size and expected screen-out rate.
- Fallback paths: create clear routes for ineligible and quota-full respondents so they do not enter outcome blocks by mistake.
Deploy: Quota Settings
Export For Analysis
Exports should include respondent answers, condition assignments, quota-relevant fields, and any randomized display order that affects interpretation. Document treatment labels, assignment probabilities, quota rules, manipulation checks, and exclusion rules in your codebook.
Before launch, submit at least one test response per arm and confirm the exported condition field is readable enough for the analyst to distinguish treatment, control, and any secondary arm without opening the Flow diagram.
Export: Condition Assignment Data