Q01
Message
All templatesIndustry-Specific
Mentorship Advocacy & Sponsorship Impact Survey
Measures whether a mentorship program is producing real advocacy — introductions, nominations, and sponsorship — not just advice conversations. Built for program owners and L&D teams, with an AI follow-up that surfaces a concrete story of advocacy (or the lack of it) behind the numbers.
Sample questions
A preview of what’s in the template. Every question is editable before you launch.
13 questions · ~7 min
Q02
Multiple ChoiceRequired
What is your role in the mentorship program?
- Mentee
- Mentor
- Both (mentor to some, mentee to others)
Q03
Opinion ScaleRequired
How likely are you to recommend this mentorship program to a colleague?
Scale: 0 – 10
Min:Not at all likelyMax:Extremely likely
Q04
MatrixRequired
Thinking about your primary mentorship relationship, how much do you agree with each statement?
4 rows × 5 columns
- My mentor/mentee actively advocates for my career growth
- My mentor/mentee has connected me to people or opportunities I wouldn't have found on my own
- My mentor/mentee gives me visibility with leaders who influence my career
- I feel comfortable asking my mentor/mentee to advocate for me publicly
Columns: Strongly disagree · Disagree · Neutral · Agree · Strongly agree
Q05
Multiple ChoiceRequired
In the last 6 months, which of these have you done for your mentee, or received from your mentor?
- Recommended them for a project or stretch assignment
- Introduced them to a leader or key contact
- Nominated them for an award, promotion, or program
- Publicly praised their work in a meeting or to leadership
- Wrote or gave a reference/recommendation
- None of these
Q06
RankingRequired
Rank these in order of what makes mentorship advocacy most valuable to you, from most to least important.
- Introductions to influential people
- Public recognition or endorsement
- Being recommended for opportunities
- Skill-building guidance
- Emotional support and encouragement
Drag to rank
Q07
AI Interview
Probe the reasoning behind the respondent's likelihood-to-recommend score by asking for one specific, recent example of mentorship advocacy — a real introduction, nomination, or recommendation that happened (or should have happened but didn't). If they scored low, dig into what advocacy was missing or what made it feel unsafe to ask for it. If they scored high, ask what tangible outcome resulted from that advocacy.
Q08
Opinion ScaleRequired
How satisfied are you with the level of support you receive in advocating for your own career growth through this program?
Scale: 1 – 5
Min:Very dissatisfiedMax:Very satisfied
Q09
Point AllocationRequired
Thinking about a typical mentorship conversation, how do you split the time across these activities? Numbers should add up to 100.
- General career advice
- Skill-building or feedback
- Networking or introductions
- Emotional support
- Active sponsorship (recommending, nominating, vouching)
Allocate 100 points
Q10
Multiple Choice
What gets in the way of advocating more actively for your mentee or receiving more advocacy from your mentor?
- Not enough time together
- Unclear what 'advocacy' should look like
- Lack of trust or relationship depth
- Limited organizational support or incentive
- Not sure who to introduce them to
- Nothing gets in the way
Q11
Multiple Choice
How long have you been part of this mentorship program?
- Less than 3 months
- 3-6 months
- 6-12 months
- More than 1 year
- Prefer not to say
Q12
Multiple Choice
Which best describes your current level?
- Individual contributor
- People manager
- Senior/Director level
- Executive
- Prefer not to say
Q13
Message
Thank you for sharing this — it genuinely helps. Your responses will be combined with others to identify where the program is building real advocacy and where mentors and mentees need more support to make it happen.
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 satisfaction scores with a matrix and multiple-choice questions that ask specifically about introductions, nominations, and sponsorship behaviors in the last 6 months — not just 'advice given.'
- Includes an AI follow-up interview that probes the reasoning behind each respondent's likelihood-to-recommend score, surfacing a concrete story of advocacy (or its absence) rather than leaving the number unexplained.
- Uses a constant-sum question to quantify how mentorship time is actually split, and a ranking question to reveal what respondents value most about advocacy — giving program owners prioritization data, not just sentiment.
- Segments by role and program tenure (mentor/mentee, level, time in program) so L&D teams can see whether advocacy gaps cluster in specific cohorts, then auto-generates a report combining these responses.
SurveyMonkey
Mentorship And Advocacy Survey Template & QuestionsA ready-to-field static template covering mentorship and advocacy themes, backed by SurveyMonkey's established survey infrastructure and distribution tools. It appears to rely on fixed question sets without any mechanism to dynamically probe individual responses. Good for benchmarking general sentiment, but less suited to uncovering the specific story behind a low or high score.
What it does well
- Fielding-ready template on a mature, widely-used survey platform
- Likely benefits from SurveyMonkey's broad distribution and analysis tooling
- Simple setup for teams wanting a quick, standard mentorship survey
Where it falls short
- No adaptive AI follow-up to probe the reasoning behind a recommendation or satisfaction score — all respondents get the same static questions
- No voice AI interview or guided task/screen-share option for richer qualitative capture
- No published methodology on how quality or sentiment scoring (if any) is calculated
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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