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Question Types

Conjoint Analysis Survey Design

Design conjoint tasks for preference experiments with randomized attributes, levels, and choice-based outcomes.

When To Use Conjoint

Conjoint questions support choice-based preference experiments in social science research surveys. Use them when respondents should compare alternatives made from randomized attributes, such as candidates, policies, products, jobs, messages, neighborhoods, or institutional profiles. A conjoint question can also hold a single alternative — useful when the goal is to show respondents one profile description to read or react to (a vignette), rather than ask them to choose between options.

Block Builder: Conjoint

A conjoint task is strongest when each attribute and level maps to a clear research hypothesis. Keep the table (or vignette) readable so respondents can compare alternatives without fatigue.

How It Supports Research Design

  • Alternative columns represent the options respondents choose between. Use a single column to display one profile without a forced choice.
  • Attribute rows define the features shown for each alternative.
  • Level options are randomly drawn for each respondent task.
  • Prohibited combinations stop specific attribute-level pairs (or larger sets) from ever being drawn into the same alternative, so the design never produces implausible profiles.
  • Number of tasks controls how many times the choice set is repeated (fresh levels each time, one task per page).
  • Uneven level weights let researchers sample some levels more often when the design requires it.
  • Row and column order controls help reduce presentation effects.
  • Display as Table or Vignette switches between the attribute-by-alternative grid and a descriptive paragraph per alternative, shown in a box or styled like plain question text.
  • Allow selecting an alternative controls whether the table or vignette is clickable. It turns off automatically for a single-alternative design (there is nothing to compare), and can be set either way regardless of alternative count.
  • Balance combinations across respondents rotates every respondent through a shared, evenly balanced sequence of valid attribute-level combinations instead of independent random draws, when the design is small enough to guarantee that balance.

Configure It In Domandata

  1. Step 1: Open Block Builder. Open the survey, stay on Block Builder, and add the block where the conjoint task should appear.

    Step 1: Open Block Builder

  2. Step 2: Add the question. Choose Conjoint from the question type selector.

    Step 2: Choose Conjoint question type

  3. Step 3: Name alternatives. Label the columns, such as Candidate A and Candidate B, so respondents understand what they are comparing. Add only one column instead if you want to display a single profile for respondents to read rather than choose between.

    Step 3: Name alternatives

  4. Step 4: Add attributes, levels, and any prohibited combinations. Add each attribute row and at least two level options for that attribute. Below the attribute rows, use Prohibited Combinations to keep specific level pairs — a price and a location that would never realistically co-occur, for example — from ever being drawn into the same alternative.

    Step 4: Add attributes and levels

  5. Step 5: Set task count and display controls. Choose how many choice tasks each participant sees (for example, 5 repeats, each on its own page). Turn on attribute names, row order controls, column order controls, or level weights only when they match the randomization design. Under Display as, choose Table for the standard grid or Vignette for a descriptive paragraph per alternative — shown in a box, or styled like plain question text. Allow selecting an alternative controls whether the table or vignette is clickable; it turns off by itself for a single-alternative design, and can be switched either way manually.

    Step 5: Set display controls

  6. Step 6: Balance combinations across respondents (optional). Turn on Balance combinations across respondents to rotate every respondent through a shared, evenly balanced sequence of valid attribute-level combinations instead of independent random draws. The options panel shows the exact number of valid combinations and whether the design is small enough to balance exactly — above that limit, Domandata falls back to standard randomization automatically.

    Step 6: Balance combinations across respondents

  7. Step 7: Preview random draws. Open Preview several times to inspect table (or vignette) readability, mobile layout, and assignment variation.

    Step 7: Preview random draws

Balance combinations across respondents caps out at a few thousand valid combinations — enough for most conjoint designs, but a large design (many attributes with many levels each) will exceed it. When that happens, the question keeps working normally with standard per-respondent randomization; nothing breaks and nothing needs to be reconfigured.

Preview: Try a Conjoint Task

Conjoint: Respondent View

Choose between candidates to see how a discrete choice task appears to respondents.

Data And Export Notes

Conjoint exports the selected alternative and the assignment information needed to analyze which levels were shown, regardless of whether the design is displayed as a table or a vignette — the underlying assignment data is the same either way. When Allow selecting an alternative is off (the default for a single alternative), there is nothing for the respondent to click, so no selected-alternative value is recorded; the shown profile still exports through the assignment snapshot. Preserve the design once live data collection begins. If the conjoint appears inside a larger experiment, use experimental conditions to control which blocks respondents see.

Export: Data and Files

Related Help

  • Vignette Experiment Example
  • How to Randomize Treatment Conditions
  • Randomize Survey Questions and Answer Options
  • Export Survey Data to Stata, R, and Python
  • Ranking Survey Questions

More Survey-Experiment Methods

How to randomize treatment conditions, design conjoint and vignette experiments, and run a list experiment — then keep the assignment in the export.

  • How to Randomize Treatment Conditions — Create condition sets for random assignment, stratified assignment, or routing based on an earlier variable.
  • How Randomization Works in Survey Experiments — Understand even (block/balanced) vs. random (independent) assignment and where each choice appears across the app.
  • Vignette Experiment Example — Build a vignette experiment with a single-alternative conjoint, Display as Vignette, and exported attribute levels.
  • List Experiment Question — Run a list experiment with a control list, a treatment list, Flow assignment, and a count — then export the assigned arm.
  • Online Survey Experiments — Design online experiments with random assignment, treatment blocks, manipulation checks, quotas, and usable exports.
  • Sample Allocation Across Condition Arms — Plan arm sizes, assignment percentages, stratification, and quota targets before collecting responses.
  • Begin a Survey With Different Conditions — Drag a Logic Split from the Block Bank to assign respondents to two, three, or more paths before the first question.
  • Randomize Survey Questions and Answer Options — Randomize questions, answers, rows, columns, or sliders when order effects could shape responses, and keep randomization order in export.

Frequently Asked Questions

How do I design a conjoint analysis survey?

Add a conjoint question, define attributes and levels, set how many tasks each respondent sees, and preview random draws. Export the chosen alternative plus the attribute-level combinations that were shown.

Can a conjoint question display a vignette instead of a table?

Yes. Use one alternative and Display as Vignette to show a randomized profile paragraph. The export still records the levels that appeared, even when the respondent is not asked to click a choice.

What does the conjoint export include?

Choice outcomes plus the attribute-level combinations shown, so the preference experiment can be estimated without reconstructing tasks by hand.