Q01
Message
All templatesCustomer Experience
Chatbot-to-Agent Handoff CSAT & Experience Survey
Evaluates customer satisfaction and friction points during chatbot-to-human-agent transfers, measuring ease of transition, context retention, agent effectiveness, and reuse intent to guide support escalation optimization.
Sample questions
A preview of what’s in the template. Every question is editable before you launch.
22 questions · ~10 min
Q02
Multiple Choice
Where did this support conversation begin?
- Website chat widget
- Mobile app chat
- Messaging app (e.g., WhatsApp, Messenger)
- SMS/text
- Social media chat
- Voice/phone IVR with bot
- I don't remember
- Other (please specify)
Q03
Opinion Scale
How easy was the transition from chatbot to human agent?
Scale: 1 – 7
Min:Very difficultMax:Very easy
Q04
Opinion Scale
How effective was the human agent at addressing your issue after the handover?
Scale: 1 – 7
Min:Not at all effectiveMax:Extremely effective
Q05
Opinion Scale
Overall, how satisfied were you with this entire support experience (chatbot and human agent combined)?
Scale: 1 – 7
Min:Very dissatisfiedMax:Very satisfied
Q06
Long Text
What one change would have most improved the handover experience for you?
Q07
Dropdown
In which region do you currently live?
- Africa
- Asia
- Europe
- Latin America/Caribbean
- Middle East
- North America
- Oceania
- Prefer not to say
Q08
Message
Thank you for your time. Your feedback will directly help improve future chatbot-to-human handover experiences.
Q09
Dropdown
Approximately when did this handover occur?
- Within the last 7 days
- 8–14 days ago
- 15–30 days ago
- 31–90 days ago
- More than 90 days ago
- I'm not sure
Q10
Dropdown
Approximately how long did you wait between the chatbot and the human agent?
- No wait (immediate)
- Less than 1 minute
- 1–3 minutes
- 4–5 minutes
- 6–10 minutes
- 11–20 minutes
- More than 20 minutes
- I don't remember
Q11
Multiple Choice
Was your issue resolved by the end of the conversation?
- Yes, fully resolved
- Partially resolved
- No, not resolved
- Not applicable
Q12
Multiple Choice
Thinking about timing, would you have preferred the handover to happen…
- Sooner than it did
- Later than it did
- Timing was about right
- No preference
Q13
AI Interview
Based on your survey responses, we'd like to explore your handover experience in a bit more detail. Please share your thoughts openly—there are no right or wrong answers.
Q14
Dropdown
What is your age?
- 18–24
- 25–34
- 35–44
- 45–54
- 55–64
- 65+
- Prefer not to say
Q15
Multiple Choice
How did the transfer to a human agent happen?
- I asked to speak to a person
- The bot suggested transferring
- It happened automatically when the bot couldn't help
- I was offered a choice of agents or channels
- I'm not sure
Q16
Opinion Scale
To what extent did the human agent appear to have the context of your chatbot conversation (e.g., your issue, steps already taken)?
Scale: 1 – 7
Min:No context at allMax:Full context
Q17
Multiple Choice
What, if anything, did you have to repeat to the human agent? (Select all that apply)
- Name or account details
- Order/case number
- Problem description
- Steps already tried
- Files or screenshots
- Nothing had to be repeated
- Other (please specify)
Q18
Opinion Scale
How likely are you to use this chatbot again for future support needs?
Scale: 1 – 7
Min:Not at all likelyMax:Extremely likely
Q19
Multiple Choice
How do you describe your gender?
- Woman
- Man
- Non-binary
- Prefer not to say
Q20
Opinion Scale
How clearly were you informed about what would happen during the transfer (e.g., expected wait, what the agent would know)?
Scale: 1 – 7
Min:Not at all clearlyMax:Extremely clearly
Q21
Opinion Scale
How seamless did the overall handover feel?
Scale: 1 – 7
Min:Not at all seamlessMax:Completely seamless
Q22
Opinion Scale
Overall, how would you rate the handover from chatbot to human agent?
Scale: 1 – 7
Min:Very poorMax:Excellent
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 sequence tracking the handoff itself — where the conversation started, how the transfer happened, and how long the wait was — not just generic support satisfaction
- Measures context retention explicitly (whether the agent seemed to know the chatbot conversation) and asks what customers had to repeat, isolating the exact friction points of handoffs
- Pairs standard opinion-scale ratings (transition ease, seamlessness, agent effectiveness, overall satisfaction, reuse intent) with an AI follow-up interview that adaptively probes the open-text answer about what would improve the handover
- Ends with an auto-generated report from per-response quality scoring, so low-effort or contradictory answers can be flagged rather than taken at face value
SurveyMonkey
Customer Support Satisfaction Survey TemplateA general-purpose customer support CSAT template rather than one built around chatbot-to-agent transfer moments. Useful as a broad satisfaction baseline but doesn't isolate handoff-specific friction like context loss or transfer timing. Fielding-ready as a static form.
What it does well
- Established survey platform with broad distribution and panel options
- Simple to deploy for general support CSAT tracking
- Familiar respondent experience for standard rating-scale questions
Where it falls short
- No chatbot-to-human handoff specific questions (transfer method, wait time, context retention)
- Static question set with no adaptive follow-up probing on open-ended answers
- No per-response quality scoring or automated interview-style report
SurveySparrow
Customer Support Agent Feedback TemplateFocused on rating human agent performance, which overlaps with the post-handoff portion of our template but doesn't address the chatbot side or the transfer experience itself. A ready-to-use conversational-style template, not a chatbot handoff diagnostic.
What it does well
- Conversational survey format that can feel more engaging than plain forms
- Targeted at agent-level feedback, useful for coaching support staff
- Quick to launch as a standard template
Where it falls short
- No coverage of the chatbot leg of the journey or the transfer moment itself
- No adaptive AI interview to dig into why a handoff felt rough
- No transparent scoring methodology or automated quality flagging of responses
Jotform
200+ Customer Satisfaction Evaluation FormsThis is a template directory/category page listing many generic satisfaction forms, not a single fielding-ready survey about chatbot-to-agent handoffs. Useful only as a starting point requiring significant customization to reach handoff-specific coverage.
What it does well
- Large library offering many form styles and layouts to start from
- Drag-and-drop form builder for quick customization
- Wide range of general CSAT question templates available
Where it falls short
- No template specifically addresses chatbot-to-human transfer friction points
- Purely static form fields with no adaptive follow-up interviewing
- No built-in per-response quality scoring or auto-generated experience report
QuestionPro
Customer Support Service Evaluation Survey TemplateA general support service evaluation template covering typical CSAT dimensions, but not built around the chatbot-to-agent handoff journey specifically. Solid as a broad service quality check rather than a friction-point diagnostic for escalations.
What it does well
- Established enterprise survey platform with reporting dashboards
- Covers general service quality dimensions applicable across support channels
- Template is ready to deploy without heavy customization
Where it falls short
- No questions targeting handoff mechanics (transfer trigger, wait time, context transfer)
- No adaptive AI-driven follow-up interview on open responses
- No transparent per-response scoring or voice-based interview option
Frequently asked questions
What questions are in the “Chatbot-to-Agent Handoff CSAT & Experience Survey” template?
The template includes 22 ready-to-use questions, starting with: “Welcome, and thank you for participating in this survey about your experience with chatbot-to-human-agent transfers in c…” · “Where did this support conversation begin?” · “How easy was the transition from chatbot to human agent?”. The full set is previewed above, and every question is editable.
How long does this survey take to complete?
Respondents typically finish the 22 questions in about 10 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.
Related templates
More studies on similar topics.
Customer Experience
Coffee Shop Customer Experience & Loyalty Survey
Captures how customers rate your drinks, wait time, staff, and atmosphere on their most recent visit, plus their likelihood to return. An AI follow-up digs into the specific moment that shaped their rating so you know exactly what to fix or protect.
View templateCustomer Experience
Chatbot-to-Agent Handoff Fairness & Trust Survey
Measures perceived fairness, transparency, and trust impact when customers encounter a chatbot before reaching a human agent. Designed for post-interaction feedback to diagnose friction in chatbot routing and escalation workflows.
View templateCustomer Experience
Marketing Chatbot Experience & Effectiveness Survey
Measures how well your website or marketing chatbot resolves visitor questions, builds trust, and moves people toward a purchase or signup. An AI follow-up interview reconstructs the respondent's most recent chatbot conversation in detail, surfacing exactly where it helped or broke down. Built for marketing and CX teams evaluating a live chatbot deployment.
View templateCustomer Experience
Post-Support CSAT & Resolution Quality Survey
Measures customer satisfaction, resolution effectiveness, agent performance, and customer effort after a support interaction to identify actionable service improvements.
View templateCustomer Experience
Customer Support Agent Interaction Feedback
Captures how a specific customer support interaction went — channel used, resolution, effort, and how the agent performed on key behaviors — with an AI follow-up that digs into the real reason behind the satisfaction score, not just the number. Built for support ops and CX teams tracking agent quality over time.
View templateCustomer Experience
Customer Contact & Support Channel Experience Survey
Captures how customers actually reach you for help, how easy and effective that contact was, and which channels they'd pick again — with an AI follow-up that reconstructs their most recent support interaction in detail instead of relying on vague satisfaction ratings.
View template