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
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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