Q01
Message
All templates
MaxDiff Feature Prioritization Survey
Force real trade-offs with best-worst scaling: respondents pick the most and least valuable feature in rotating sets, then an AI interviewer probes the reasoning behind their top pick. Produces a true preference ranking instead of everything-is-important rating inflation.
Sample questions
A preview of what’s in the template. Every question is editable before you launch.
8 questions · ~5 min
Q02
Multiple ChoiceRequired
How long have you been using our product?
- Less than 3 months
- 3–12 months
- 1–3 years
- More than 3 years
- I don't use it yet
Q03
Multiple ChoiceRequired
Which best describes your role when using the product?
- I use it hands-on every week
- I use it occasionally
- I manage people who use it
- I evaluate or purchase tools like this
Q04
Best–Worst Trade-off (MaxDiff)Required
From each set, choose the feature that would be MOST valuable to you and the one that would be LEAST valuable.
- Deeper integrations with the tools you already use
- Faster performance and load times
- Advanced analytics and reporting
- Collaboration and shared workspaces
- Mobile app experience
- AI-assisted automation of repetitive steps
- More granular permissions and admin controls
- Offline access
Pick best & worst per setBest:Most valuableWorst:Least valuable
Q05
Opinion ScaleRequired
How satisfied are you with the product as it exists today, before any of these improvements?
Scale: 1 – 7
Min:Very dissatisfiedMax:Very satisfied
Q06
AI Interview
Explore why the respondent's most-valued feature matters to them: what job they are trying to get done, what they do today without it, what it costs them in time or workarounds, and what would make the feature a disappointment if built poorly. Also probe whether their least-valued pick is genuinely unimportant or just not relevant to their role.
Q07
Long Text
Is there a feature we didn't list that would beat everything you just ranked? If so, what is it and what would it let you do?
Q08
Message
That's everything — thank you! Your trade-offs go straight into our roadmap prioritization. The AI report will combine everyone's picks into a ranked list with the reasoning behind it.
What’s included
AI follow-ups
Adaptive probes on open-ended answers that pull out detail a static form would miss.
Attention checks
Built-in safeguards against rushed answers and low-quality respondents.
AI-drafted copy
Wording, ordering, and branching written by the AI — tuned to your research goal.
Auto report
Themes, quotes, and a plain-English summary write themselves once responses come in.
How it compares
We reviewed the closest templates from other survey tools. Here’s what they do well — and where this template goes further.
Why this template
- Best-worst trade-offs arrive with the why: an AI interviewer probes the reasoning behind each respondent's top pick, so the ranking ships with its evidence
- Usage and role screeners are built in, so preference rankings can be cut by segment without extra setup
- A final open question asks what would beat everything listed — catching the option your item list missed
- Every prompt and model setting is visible and logged, and the report assembles ranks plus reasoning automatically
QuestionPro
MaxDiff SurveysA marketing/overview page positioning MaxDiff as a more discriminating alternative to rating and ranking scales, and cheaper than conjoint. It names concrete outputs (utility scores, share-of-preference) and use cases (new-feature research, market segmentation) but stops short of showing a real sample question set or result visuals, functioning as an intro rather than a ready-to-field template.
What it does well
- Explicitly names the core analytical outputs: utility per attribute and Share of Preference calculation
- Supports unlimited attributes with random sub-selection and rotation across choice sets
- Frames MaxDiff correctly against alternatives (better discrimination than derived-importance rating scales; cheaper than conjoint)
- Ties the method to specific business use cases (new product features, market segmentation)
Where it falls short
- No adaptive AI follow-up to ask why a respondent picked an item as best or worst, so the 'why' behind the utilities is never captured
- No voice-interview option; the method is a silent forced-choice grid only
- No visible sample question or transparent methodology walkthrough on the page itself; users are pushed to separate help docs
- No auto-generated narrative report shown; outputs are described as raw utility/share numbers a researcher must interpret
QuestionPro
MaxDiff Analysis survey questionThe feature-level page for MaxDiff as a question type, distinct from the survey overview. It includes a worked credit-card preference example, five use cases, and an anchored-MaxDiff option, making it more concrete than the overview page, but it still defers setup mechanics and utility-calculation details to help documentation.
What it does well
- Includes a concrete worked example (credit-card feature preference) so users can see the best/worst task shape
- Offers anchored MaxDiff, letting scores be interpreted on an absolute good/bad threshold rather than only relatively
- Enumerates five distinct use cases (consumer testing, real estate, packaging, attribute testing) to guide adoption
- Rotates answer combinations across respondents to improve data quality and engagement
Where it falls short
- No conversational probe on the chosen best/worst item, so motivations behind preferences stay hidden
- No transparent prompt or methodology exposed in-product; calculation details live in external help files
- No auto-generated report; the page frames output as data a researcher analyzes downstream
- No multilingual or voice administration described for the choice tasks
Ready to launch?
Open this template in the editor. Every part is yours to change before the first respondent sees it.