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Select the type of research method you want to use.
Choose the statistical framework for your study.
Add and organize your survey questions below.
Build the factor structure, control task design, and generate respondent-ready conjoint tasks.
Define the exact factor structure after global settings are saved.
Pages and choice structure need to be fixed before factor authoring unlocks.
Keep the response cap next to the conjoint setup so it stays visible before distribution.
Set survey metadata first. This controls the question volume and page plan.
Keep attributes between 4 and 8 for stable matrix configurations.
Each attribute should contain at least 2 levels, capped dynamically under 5 items for response fidelity.
Configure the MaxDiff task design, manage the item list, and generate respondent-ready best-worst choice tasks.
Define the MaxDiff title, instructions, task count, and item density.
Use 4-6 items per task so best-worst discrimination stays readable.
Target roughly 3 appearances per item across the full task set.
Use at least 6 items for a stable MaxDiff exercise and avoid repeating wording.
Add the statements or attributes respondents will rank as best and worst.
Live design coverage for the current MaxDiff configuration.
Use concise item wording so the tradeoff is easy to scan.
Keep item count high enough for coverage, but avoid duplicates or near-duplicates.
Use the preview modal to verify the best-worst table before publishing.
Set the response cap here before moving to distribution. This can still be edited later.
Structure the feature list and prepare the functional-dysfunctional evaluation flow.
Keep feature wording short and singular.
Every feature will be evaluated with a functional and dysfunctional framing.
Structure the standard price sensitivity meter, tune the wording to your category, and keep the four price thresholds analytically clean.
Optional builder metadata for the pricing exercise and respondent framing.
Keep the four prompts ordered from cheapest threshold to highest threshold.
Avoid inserting value claims or promotional language inside the price questions.
Only adapt wording when the product context truly requires it.
These four prompts feed the classic price sensitivity meter.
Build a clean ascending price ladder, define the purchase-intent framing, and keep the study ready for revenue curve analysis.
Frame the purchase-intent question and define the price ladder context.
Use an ascending ladder with distinct prices only.
Five to seven price points usually gives cleaner demand curves than just two or three.
Keep prompt wording neutral so responses reflect willingness to pay, not brand persuasion.
Add price points in ascending order. Distinct values only.
Live diagnostics for spacing and analysis readiness.
Define the offer set, choose the portfolio size to optimize, and prepare a clean reach-and-frequency style feature exercise.
Define the respondent framing and the number of items to optimize in the final portfolio.
Use distinct, independently meaningful features or offers.
Portfolio size should never exceed the number of configured items.
TURF works best when every feature has a clear yes-or-no relevance interpretation.
Add each feature or concept that could contribute incremental reach.
Live builder diagnostics for reach-model readiness.
Choose how you want to share and collect survey responses.
Review your survey setup before publishing it live.
Triggers a validation check across your questions text blocks and choice arrays to ensure flawless formatting before going live.
Live Rendering & Layout Integrity Evaluation Buffer
