Q01
Message
All templatesIndustry-Specific
Forced-Choice Agreement Survey (No Neutral Option)
Measures agreement with a set of statements using an even-numbered rating scale that removes the neutral midpoint, forcing respondents to lean agree or disagree rather than sit on the fence. Built for HR, product, and policy teams who want to reduce central-tendency bias in attitude research. The AI follow-up digs into the concrete reason behind each respondent's strongest lean and what would change their mind.
Sample questions
A preview of what’s in the template. Every question is editable before you launch.
11 questions · ~6 min
Q02
Multiple ChoiceRequired
In the last 30 days, how often did you interact with (replace with the product, policy, or team being evaluated)?
- Not at all
- A few times
- Weekly
- Almost daily
Q03
MatrixRequired
For each statement, choose the response that comes closest to how you feel. There is no middle option — pick the side you lean toward.
4 rows × 4 columns
- (Replace with Statement 1 — e.g., 'This policy is clearly communicated')
- (Replace with Statement 2 — e.g., 'This policy is applied fairly')
- (Replace with Statement 3 — e.g., 'This policy makes my day-to-day work easier')
- (Replace with Statement 4 — e.g., 'I would recommend keeping this policy as-is')
Columns: Strongly disagree · Disagree · Agree · Strongly agree
Q04
Multiple Choice
Which one of those statements did you feel most strongly about, in either direction?
- (Replace with Statement 1)
- (Replace with Statement 2)
- (Replace with Statement 3)
- (Replace with Statement 4)
Q05
Rating ScaleRequired
Overall, how strongly do you agree that (replace with the topic, e.g., 'the current policy') is working well?
Range: 1 – 6
Min:Strongly disagreeMax:Strongly agree
Q06
Ranking
Rank these statements from the one that matters most to you personally to the one that matters least.
- (Replace with Statement 1)
- (Replace with Statement 2)
- (Replace with Statement 3)
- (Replace with Statement 4)
Drag to rank
Q07
AI Interview
Identify which statement the respondent leaned most strongly toward, agree or disagree, and reconstruct the concrete reason behind that lean — a specific incident, comparison, or outcome, not a general attitude. If they strongly disagreed with any statement, ask what specific, realistic change would move them to agree. If every lean was mild, probe which single change would most increase their overall agreement.
Q08
Long Text
Anything about (replace with the topic) that these statements didn't capture?
Q09
Multiple Choice
Which team or department are you part of?
- (Replace with Department A)
- (Replace with Department B)
- (Replace with Department C)
- Prefer not to say
Q10
Multiple Choice
How long have you been in your current role?
- Less than 6 months
- 6 months to 2 years
- 2 to 5 years
- More than 5 years
- Prefer not to say
Q11
Message
That's everything — thank you for being direct with us! Your responses feed into a report on where opinion is genuinely split versus where most people lean the same way.
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
- Uses an even-numbered agreement scale with no neutral midpoint, built specifically to reduce central-tendency bias rather than being a generic Likert template
- After the matrix, an AI follow-up interview asks the respondent to explain the concrete reason behind their strongest lean and what would change their mind
- Includes a ranking question to surface which statement matters most personally, plus role/tenure questions for segmenting HR, product, or policy feedback
- Ends with an auto-generated report pulling together the rating, ranking, and open-ended reasoning instead of leaving analysis to the researcher
QuestionPro
Even Likert Scale Survey Questions TemplateThis is the closest conceptual match, offering a template built around the even-point (forced-choice) Likert scale to avoid neutral responses. It's a static question set aimed at general attitude research rather than a specific HR/product/policy workflow. No adaptive follow-up is mentioned, so any 'why' behind a respondent's answer isn't captured within the tool.
What it does well
- Purpose-built around the even-scale/no-neutral-option concept, matching the core methodology
- Backed by a large, established survey platform with broad question-type support
- Likely customizable in wording and number of scale points
Where it falls short
- No adaptive AI follow-up interview to probe the reasoning behind a strong lean
- No mention of automated per-response quality scoring
- No transparent, published prompt methodology for how any AI features (if present) operate
SurveyMonkey
Likert Scale Survey TemplateA general Likert scale template from a mainstream survey platform, useful as a starting point for attitude measurement but not specifically framed around removing the neutral midpoint. It's a standard fielding-ready template rather than one engineered for central-tendency bias reduction or department-specific attitude research.
What it does well
- Widely recognized, easy-to-deploy template on a mature survey platform
- Likely supports standard Likert scale customization (labels, number of points)
- Good baseline choice for teams already using SurveyMonkey for other research
Where it falls short
- No indication it defaults to an even-point, forced-choice scale — neutral option likely included by default
- No adaptive AI interview or voice AI follow-up to explore respondent reasoning
- No automated quality scoring or transparent AI prompt documentation
SurveySparrow
Free Likert Scale Questionnaire TemplateA free, general-purpose Likert scale questionnaire template geared toward business use cases broadly, not specifically toward forced-choice/no-neutral designs. It appears to be a static, ready-to-use form rather than one built to actively investigate the reasoning behind strong opinions.
What it does well
- Free and positioned specifically for business questionnaire use
- Likely offers a conversational/chat-style survey format, which SurveySparrow is known for
- Simple to customize statement wording for different business contexts
Where it falls short
- No stated support for an even-numbered, no-neutral scale specifically designed to reduce central-tendency bias
- No adaptive AI or voice interview component to dig into the 'why' behind strongest agreement/disagreement
- No automated per-response quality scoring or published AI prompt transparency
Frequently asked questions
What questions are in the “Forced-Choice Agreement Survey (No Neutral Option)” template?
The template includes 11 ready-to-use questions, starting with: “Thanks for sharing your honest reactions to a few statements below. Your responses are completely confidential and anony…” · “In the last 30 days, how often did you interact with (replace with the product, policy, or team being evaluated)?” · “For each statement, choose the response that comes closest to how you feel. There is no middle option — pick the side yo…”. The full set is previewed above, and every question is editable.
How long does this survey take to complete?
Respondents typically finish the 11 questions in about 6 minutes.
Can I customize this template?
Yes — every question, answer option, and the ordering is editable before you launch. You can add or remove questions, or ask the AI editor to rework the survey around your research goal.
Is this template free to use?
Yes. Open it in the editor and start customizing right away — no account required to try it, and the free plan covers launching your survey.
Ready to launch?
Open this template in the editor. Every part is yours to change before the first respondent sees it.
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