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Flight Booking Chatbot Usability & Trust Survey

Evaluates how well an airline or travel site's AI chatbot handles real booking, change, and support tasks — covering task completion, trust, and where users bail out to a human. An AI follow-up interview reconstructs exactly what happened in the respondent's most recent chatbot session, not just how they'd rate it in hindsight.

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Sample questions

A preview of what’s in the template. Every question is editable before you launch.

12 questions · ~7 min
Q01
Message

Thanks for trying out our flight booking assistant! We'd like to hear about your most recent interaction with it — what worked, what didn't, and where it could do better. This will take about 5 minutes.

Q02
Multiple ChoiceRequired

What were you trying to do the last time you used the chatbot?

  • Book a new flight
  • Change or cancel an existing booking
  • Check flight status or gate information
  • Ask about baggage, seats, or fees
  • Request a refund or file a complaint
  • Something else
Q03
Opinion ScaleRequired

How easy was it to get what you needed from the chatbot in that interaction?

Scale: 1 – 7
Min:Very difficultMax:Very easy
Q04
Multiple ChoiceRequired

How did that interaction end?

  • The chatbot fully resolved it
  • The chatbot partially helped, and I finished the rest myself online
  • I gave up on the chatbot and called or messaged a human agent
  • I abandoned the task entirely
Q05
Rating ScaleRequired

How well did the chatbot understand what you were asking, even when you phrased it in your own words?

Range: 1 – 5
Min:Frequently misunderstood meMax:Understood me every time
Q06
MatrixRequired

How much do you agree with each statement about the chatbot?

5 rows × 5 columns
  • It gave accurate flight information and prices
  • It responded quickly enough
  • It was clear about what it could and couldn't help with
  • I trusted the information it gave me
  • It made handing off to a human easy when needed
Columns: Strongly disagree · Disagree · Neutral · Agree · Strongly agree
Q07
AI Interview

Reconstruct the respondent's most recent chatbot interaction step by step: what they typed or said first, how the chatbot responded, and the exact moment (if any) where it broke down or forced a workaround. If they say they gave up or switched to a human, get the specific request that failed and what they wish the chatbot had said or done instead. If they say it fully resolved their task, probe what almost went wrong or felt uncertain along the way.

Q08
Opinion ScaleRequired

How likely are you to use this chatbot again the next time you need help with a flight?

Scale: 0 – 10
Min:Not at all likelyMax:Extremely likely
Q09
Best–Worst Trade-off (MaxDiff)

Which of these improvements would make the biggest difference to your experience with the chatbot?

  • Better understanding of complex or multi-part requests
  • Faster response times
  • Clearer explanation of prices and fees
  • Remembering my past trips and preferences
  • Easier handoff to a human agent
  • Support for more languages
  • More proactive alerts about delays or changes
  • Ability to handle multi-city or group bookings
Pick best & worst per setBest:Most impactfulWorst:Least impactful
Q10
Multiple Choice

In the last 12 months, how often have you flown?

  • Not at all
  • 1-2 times
  • 3-5 times
  • 6 or more times
  • Prefer not to say
Q11
Multiple Choice

Which age range best describes you?

  • Under 18
  • 18-24
  • 25-34
  • 35-44
  • 45-54
  • 55-64
  • 65 or older
  • Prefer not to say
Q12
Message

That's everything — thank you for the detailed feedback! Your responses will go straight to the team improving the flight booking assistant's accuracy and handoff process.

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

  • Uses an AI follow-up interview to reconstruct the respondent's most recent chatbot session step by step, capturing what actually happened rather than a hindsight rating.
  • Pairs that reconstruction with quantitative measures — an ease-of-use opinion scale, an understanding rating, a trust/agreement matrix, and a max-diff on potential improvements — for both depth and comparability.
  • Directly asks how the interaction ended, isolating the exact moment users bail out to a human agent rather than just an overall satisfaction score.
  • Segments results by recent flight frequency and age range so completion and trust patterns can be broken out by traveler type.

SurveySparrow

Flight Booking Chatbot Template | Automate Travel Queries

This is a fielding-ready conversational chatbot/survey template aimed at automating flight booking queries, making it a genuine adjacent offering. It's built around SurveySparrow's chat-style UI and automation, but it reads as a general query/booking flow rather than a dedicated instrument for probing trust and bail-out points. No indication it reconstructs a specific past chatbot session in the respondent's own words.

What it does well

  • Conversational, chat-style question format that feels native to a chatbot context
  • Backed by an established CX/survey automation platform with broader workflow integrations
  • Likely quick to deploy for general travel query handling

Where it falls short

  • Relies on fixed branching logic rather than adaptive AI follow-up questions generated from the respondent's own answers
  • No mechanism to reconstruct the respondent's actual most recent chatbot session step-by-step
  • No published per-response quality scoring or transparent prompt methodology

QuestionPro

Airline's flight experience survey template

A fielding-ready survey template from an established research platform, but it targets overall airline flight experience rather than chatbot task completion or trust specifically. Useful as a general travel-satisfaction benchmark, though it isn't purpose-built to isolate where chatbot interactions succeed, fail, or escalate to a human. Content appears to be static questions rather than an adaptive interview.

What it does well

  • Covers broad airline flight experience touchpoints beyond just digital self-service
  • Part of a mature survey platform with standard reporting and analytics
  • Ready to deploy without custom build work

Where it falls short

  • Not specific to chatbot usability, so it likely misses granular task-completion and bail-out-to-human moments
  • Static question set with no adaptive AI probing based on individual responses
  • No session reconstruction or transparent prompt disclosure for how follow-up questions are generated

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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