Common chatbot user questions and great questions for onboarding survey: how to unlock real user insights with conversational AI surveys

When launching a chatbot, knowing the common chatbot user questions your audience expects to ask is essential. The best way to uncover these insights is through great questions for onboarding survey that feel like natural conversations.

Understanding user expectations is at the heart of creating a successful chatbot experience. An AI survey during onboarding surfaces these expectations naturally—letting users share what matters to them in their own words. With a conversational survey made using flexible tools like Specific’s AI survey generator, you get past surface-level answers and discover what users genuinely want from your chatbot.

Why traditional surveys fail to capture chatbot expectations

Traditional survey forms fall short when it comes to capturing the nuances of what people expect from a chatbot. Static forms can't adapt to each user's background, goals, or technical comfort level. Many users aren't even sure what chatbots can do—and won't realize what they want until a conversation brings it out.

In my experience, the "why" behind user expectations is often missing. When survey forms stop at superficial answers, teams risk misunderstanding the true needs behind user questions. That's where real-time follow-ups matter.

And remember: mental models of chatbots differ wildly. What feels "smart" or "obvious" for one user might feel uninspired to another. Traditional forms treat everyone the same and end up missing the mark.

Traditional surveys	Conversational surveys
Rigid, one-size-fits-all questions	Adapts in real time to users’ responses
No follow-up or clarification	Dynamic probing reveals deeper insights
Limited to user’s own stated ideas	Encourages users to reflect and expand
Low engagement, often feels like a chore	Feels like a genuine chat, raising completion rates

This isn’t just preference—77% of customers believe chatbots will transform their expectations of companies in the next five years, and users’ needs are varied and evolving fast [1]. That’s why a conversational approach unlocks richer, truer understanding.

Essential onboarding questions to understand chatbot expectations

After running countless user interviews and onboarding surveys, I’ve found that certain question types consistently reveal the most actionable insights for chatbot development. Here’s what I always include—and why:

Prior experience questions: “Have you used chatbots before? What worked, and what frustrated you?” Mapping user history surfaces their mental models and sets the stage for meaningful follow-ups. If someone’s only experience is a customer support bot, their expectations for helpfulness or tone may differ from those using next-gen AI assistants.

Use case discovery questions: “What would you most like to achieve using this chatbot?” This open invitation lets users surprise you with needs you may not have considered. The conversation can pivot easily to confirm specifics with AI-powered probes, ensuring you capture every relevant scenario. Learn more about automatic AI follow-up questions and how they deepen these answers.

Communication preference questions: “Do you prefer short, direct responses, or more detailed explanations?” Communication style is personal—let users tell you what feels natural. The AI can adjust to ask precision clarifiers or example-based questions until it’s clear what each respondent actually wants.

Feature expectation questions: “Are there specific features or topics you wish the chatbot could help with?” Early in onboarding, nudging users to share their feature wish-list means you can validate roadmap priorities against real user desire, not hunches.

By letting the AI ask context-sensitive follow-ups, each of these question types uncovers more than a checklist of needs—it maps the full user journey from hope to possible frustration.

Building your chatbot expectation survey with AI

With Specific, I get to skip the slog of question-by-question survey editing. Using the AI survey builder, I just describe what I want—“draft a chatbot onboarding survey that explores user expectations”—and it handles the rest. Natural language prompts make setup feel like chatting to a research partner, not wrestling with forms.

Draft a chatbot onboarding survey that discovers users’ prior chatbot experience, preferred use cases, ideal conversation style, and hoped-for features.

Design a conversational onboarding survey to identify common questions users want to ask a chatbot, with AI follow-ups for unclear or incomplete answers.

You can match the survey tone to your brand—friendly, concise, formal, playful, whatever fits your audience. The probing depth setting means you decide how much the AI should chase the details: one gentle reply, or several follow-up questions digging into root causes and examples.

For reach, I like to send surveys via a Conversational Survey Page—just a shareable link, no embed needed. And worldwide teams shouldn’t sweat language barriers: Specific’s multilingual support means users can answer in their preferred language, and insights stay centralized, translation headaches-free.

Turning user expectations into chatbot features

I don’t just collect onboarding survey data—I mine it for actionable trends that shape actual chatbot development. Specific’s AI survey response analysis tools reveal recurring themes in seconds. I use the response analysis chat as my insight engine, filtering by attributes, segments, or just plain curiosity.

What are the most frequent feature requests from new chatbot users?

Which conversation styles do expert chatbot users prefer, based on onboarding survey feedback?

Insights like these guide not only the chatbot’s core feature set but also its personality, language patterns, and built-in flows. If 64% of customers cite 24/7 service as the main benefit of chatbots [3], that's a cue for emphasis on availability in your own product roadmap.

You’ll also want to run ongoing onboarding surveys as your product and user base evolves. Expectations shift fast—especially as more people (67% globally this year [2]) interact with chatbots. Using AI-powered analysis gives you a living map of what matters most, now and in the future.

Start learning what your users really want

Don’t guess at what your users expect—discover it directly from them. The conversational approach captures what static survey forms miss: nuance, surprise, and the “why” behind every need. It empowers you to build a chatbot people love, with confidence. Ready to create your own survey? Start with user onboarding—real insights are waiting.