Workplace Diversity, Equity & Inclusion Experience Survey
Measures how included, fairly treated, and heard employees feel across backgrounds, and prioritizes where DEI investment would have the most impact. An AI follow-up interview digs into specific belonging or fairness experiences behind the scores instead of leaving them as abstract ratings.
Sample questions
A preview of what’s in the template. Every question is editable before you launch.
Overall, how much of a sense of belonging do you feel at this organization?
How much do you agree or disagree with the following statements about your day-to-day experience at work?
- I am treated fairly regardless of my background
- I have the same opportunities for advancement as my colleagues
- My opinions are heard and valued in team decisions
- I can be my authentic self at work without hiding parts of who I am
In the last 12 months, have you personally experienced or witnessed unfair treatment at work based on a personal characteristic (e.g., race, gender, age, disability, religion, sexual orientation)?
- Yes, I experienced it
- Yes, I witnessed it happen to someone else
- Both experienced and witnessed it
- No
- Not sure
How confident are you that senior leadership is genuinely committed to building a diverse and inclusive workplace, beyond stated policies?
If you witnessed discrimination or exclusionary behavior at work, how comfortable would you be reporting it?
- Very comfortable
- Somewhat comfortable
- Somewhat uncomfortable
- Very uncomfortable
- Not sure who I would report it to
Which of these actions would do the most to improve diversity and inclusion here? Pick the most and least impactful in each set shown.
- More diverse hiring pipelines
- Manager training on inclusive leadership
- Clearer, more transparent paths for promotion
- Employee resource groups or affinity networks
- Regular pay equity audits
- Flexible work arrangements
- Anonymous, trusted reporting channels
Explore the respondent's belonging score and any reported experience of unfair treatment in concrete detail: ask for a specific recent moment that shaped that score, what happened, how it was (or wasn't) addressed, and what a good response from a manager or leadership would have looked like. If they said they experienced or witnessed discrimination, gently probe whether they reported it and why or why not. If their belonging score was high, ask what specifically makes them feel included so it can be replicated for others.
Almost done — these last questions are optional and help us see whether experiences differ across groups. Skip anything you'd rather not answer.
Which gender identity do you most identify with?
- Woman
- Man
- Non-binary
- Prefer to self-describe
- Prefer not to say
Which race or ethnicity do you identify with? (Select all that apply)
- American Indian or Alaska Native
- Asian
- Black or African American
- Hispanic or Latino
- Native Hawaiian or Other Pacific Islander
- White
- Two or more races
- Prefer to self-describe
- Prefer not to say
Which age range do you fall into?
- Under 25
- 25-34
- 35-44
- 45-54
- 55-64
- 65 or older
- Prefer not to say
Do you identify as a person with a disability?
- Yes
- No
- Prefer not to say
Thank you for sharing this — including the harder parts. Your answers are combined with your colleagues' anonymously to identify patterns and shape concrete steps in our diversity and inclusion plan.
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
- Goes beyond a single belonging score with an AI follow-up interview that explores the specific fairness or exclusion experience behind a respondent's rating, instead of leaving it as an abstract number.
- Combines quantitative measures (opinion scale on belonging, matrix on day-to-day treatment, MaxDiff prioritization of DEI actions) with qualitative depth in one flow.
- Uses plain-language chat messages to set expectations and thank respondents for sharing 'the harder parts,' which supports honest disclosure on a sensitive topic.
- Collects demographic breakdowns (gender, race/ethnicity, age, disability) as clearly optional, so equity-gap analysis can be layered onto the belonging and fairness data without forcing disclosure.
Jotform
Questionnaire for Equity & Managing Diversity at workplace Form TemplateA static, customizable form template built on Jotform's general-purpose form builder rather than a dedicated survey research platform. Good for quick data collection and easy drag-and-drop editing, but not designed for probing open-ended fairness or belonging experiences in depth.
What it does well
- Highly customizable via Jotform's drag-and-drop form builder
- Easy to embed, share, and integrate with other Jotform workflows/apps
- Low barrier to quickly stand up a basic diversity questionnaire
Where it falls short
- Fixed set of questions with no adaptive follow-up to explore individual belonging or fairness stories
- No published methodology on question design or scoring rigor
- No voice interview or guided task/screen-share option for richer qualitative context
SurveySparrow
Workplace Diversity Questionnaire TemplateA conversational-style survey template that presents questions one at a time, giving it a friendlier feel than a traditional form. It still relies on pre-written questions rather than an AI that adapts follow-ups to each respondent's specific answers.
What it does well
- Conversational, one-question-at-a-time UI that can feel less clinical than a grid form
- Template is ready to field with minimal setup
- Part of a broader employee-experience template library for reuse across HR programs
Where it falls short
- No adaptive AI interviewing — the same fixed question sequence is shown to every respondent regardless of their score
- No automated per-response quality scoring or transparent prompt disclosure
- No voice-based interview option for capturing nuance beyond text/multiple-choice
QuestionPro
Workplace diversity survey templateEnterprise-oriented survey template backed by QuestionPro's broader analytics and reporting suite, suitable for tracking diversity metrics over time. It is a structured questionnaire, not an interview format, so open-ended experiences are captured only as free-text fields rather than explored dynamically.
What it does well
- Backed by established analytics/reporting dashboards for tracking DEI metrics over time
- Template fits within a larger workforce/employee-experience survey ecosystem
- Likely supports segmentation and cross-tabulation of demographic data
Where it falls short
- Static question set with no AI-driven follow-up probing on individual fairness or belonging incidents
- No transparent, respondent-facing publishing of interview prompts/methodology
- No guided screen-share task or voice interview capability
SurveyMonkey
Diversity Survey TemplateA widely used, expert-reviewed template on a mature survey platform, useful as a baseline DEI questionnaire. Like other form-based tools it presents a fixed question set to all respondents, with no mechanism to adaptively dig into the reasoning behind a low belonging or fairness score.
What it does well
- Backed by SurveyMonkey's broad survey methodology expertise and large user base
- Easy integration with SurveyMonkey's existing analysis and benchmarking tools
- Simple to deploy at scale across large organizations
Where it falls short
- No adaptive AI follow-up interview — respondents who report unfair treatment get no further probing on specifics
- No automated quality scoring of individual responses
- No voice AI interview or guided task/screen-share option
Ready to launch?
Open this template in the editor. Every part is yours to change before the first respondent sees it.