Q01
Message
All templatesAI & Technology
Doctor Appointment Chatbot Experience Survey
Measures how well an AI scheduling chatbot helps patients book, reschedule, or get answers about medical appointments, covering task completion, trust, and friction points — with an AI follow-up interview that digs into the specific moment the chatbot helped or failed.
Sample questions
A preview of what’s in the template. Every question is editable before you launch.
11 questions · ~6 min
Q02
Multiple ChoiceRequired
What did you use the chatbot for during your most recent interaction?
- Booking a new appointment
- Rescheduling an existing appointment
- Cancelling an appointment
- Checking office hours or location
- Asking a question about insurance or paperwork
- Getting a reminder or confirmation
Q03
Opinion ScaleRequired
How easy was it to complete your task using the chatbot?
Scale: 1 – 7
Min:Very difficultMax:Very easy
Q04
Multiple ChoiceRequired
Did the chatbot fully resolve your request, or did you end up needing a phone call or staff member?
- Fully resolved by the chatbot
- Partly resolved, then I needed human help
- Not resolved — I had to start over with a person
Q05
MatrixRequired
How much do you agree with each statement about the chatbot?
4 rows × 5 columns
- It understood what I was asking for
- The information it gave me was accurate
- The conversation felt natural, not robotic
- It saved me time compared to calling the office
Columns: Strongly disagree · Disagree · Neutral · Agree · Strongly agree
Q06
Opinion ScaleRequired
How much do you trust the chatbot to correctly handle sensitive scheduling details (like appointment type, provider, or timing)?
Scale: 0 – 10
Min:Do not trust it at allMax:Trust it completely
Q07
Rating ScaleRequired
Overall, how satisfied are you with the chatbot experience?
Range: 1 – 5
Min:Very dissatisfiedMax:Very satisfied
Q08
AI Interview
Reconstruct the specific moment in the respondent's most recent chatbot interaction that shaped their satisfaction rating — what they typed or asked, how the chatbot responded, and whether it matched their expectations. If they said they needed human help, probe exactly where the handoff happened and what triggered it. If they gave low trust, ask what specifically made them doubt the chatbot's accuracy.
Q09
Multiple Choice
Next time you need to book or change an appointment, which method would you prefer to use first?
- The chatbot
- Calling the office directly
- The clinic's website or patient portal (non-chat)
- Walking in or asking in person
- No strong preference
Q10
Multiple Choice
What is your age range?
- 18-24
- 25-34
- 35-44
- 45-54
- 55-64
- 65 or older
- Prefer not to say
Q11
Message
That's everything — thank you for sharing your experience! Your answers help our clinical and product teams improve how the chatbot handles real patient requests.
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
- Includes a dedicated AI follow-up interview that reconstructs the specific moment the chatbot helped or failed, going beyond static ratings
- Combines task-completion, trust, and friction measures (opinion scales, matrix, resolution outcome) in one flow rather than a single satisfaction score
- Captures behavioral intent for the future ('which method would you prefer next time') alongside sentiment, useful for channel-strategy decisions
- Automated quality scoring and auto-generated reports summarize open-ended detail without manual coding, on a platform with a free tier and transparent $50/mo Business plan (no hidden academic tier)
SurveySparrow
Doctor Appointment Chatbot | For Hospitals & ClinicsThis is a directly comparable template aimed at hospitals and clinics evaluating their appointment chatbot. It appears to be a fielding-ready survey rather than a blog post, likely covering standard satisfaction and usability questions. It does not appear to include adaptive AI-driven follow-up probing into a specific interaction moment.
What it does well
- Purpose-built for healthcare chatbot feedback, targeted at hospital/clinic use cases
- Backed by SurveySparrow's broader survey distribution and dashboard tooling
- Likely offers standard branching logic for a structured feedback flow
Where it falls short
- No indication of adaptive AI follow-up interviews that dig into a specific chatbot interaction moment
- No published methodology or prompt transparency for how deeper insights are extracted
- Likely relies on fixed question sets rather than automated per-response quality scoring
Frequently asked questions
What questions are in the “Doctor Appointment Chatbot Experience Survey” template?
The template includes 11 ready-to-use questions, starting with: “Hi! Thanks for trying our appointment chatbot. Your responses are completely confidential and anonymized. We'd love to h…” · “What did you use the chatbot for during your most recent interaction?” · “How easy was it to complete your task using the chatbot?”. 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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