This article will give you tips on how to analyze responses from a user survey about onboarding experience. I’ll show you strategies and tools that make this much easier—whether you have ten or a thousand responses.
Choose the right tools for analyzing survey data
How you analyze your survey data comes down to the structure of those responses. For many surveys about onboarding experience, you’ll be dealing with both numbers and rich, text-based answers that require different approaches.
Quantitative data: Numbers and counts—for example, how many users rated your onboarding as “excellent”—are easy to summarize in Excel or Google Sheets. Just drop in your exports, create simple charts, and you’re done.
Qualitative data: Open-ended responses or follow-ups, like “What did you love about onboarding?”—that’s where things get tricky. Reading dozens or hundreds of free-text answers isn’t realistic. For this, you need AI tools that can process and summarize responses at scale.
There are two approaches for tooling when dealing with qualitative responses:
ChatGPT or similar GPT tool for AI analysis
Copy–paste your data into ChatGPT. This is the quick-and-dirty method. You grab your exported answers, paste them into ChatGPT, and start asking questions (“Find the main themes,” “Summarize the feedback on tutorials,” etc.).
The downside? Handling the data this way gets messy fast: you’ll need to be careful with formatting, context limits, and organizing outputs—especially as your surveys grow. It works for a few dozen responses, but isn’t designed for ongoing, repeatable survey analysis.
All-in-one tool like Specific
Purpose-built for AI survey analysis. Specific is built specifically for collecting and analyzing survey responses using AI. You can create your user onboarding survey and instantly analyze responses with AI, all in one place.
What sets it apart? Specific’s conversational surveys ask smart follow-up questions automatically, capturing detailed, authentic answers—the kind that drive real insight. When it’s time to analyze, AI summarizes responses, pulls out core themes, reveals sentiment, and lets you “chat” with your results (think: ChatGPT, but custom context for your onboarding data).
No more manual copy-pastes or juggling spreadsheets. If you need to tweak your survey or questions, just use the AI survey editor—change anything via chat. There’s even a feature for automatic AI follow-up questions, so you consistently get high-quality responses.
Useful prompts that you can use for user onboarding experience survey analysis
Great prompts unlock the full power of AI survey analysis. Here’s how I approach it for onboarding experience data—that way, whether you use ChatGPT or Specific, you get real insight instead of generic summaries.
Prompt for core ideas: This works for any onboarding survey with open-ended or follow-up questions. It’s the default prompt in Specific, but you can use it anywhere. Paste your data and use:
Your task is to extract core ideas in bold (4-5 words per core idea) + up to 2 sentence long explainer.
Output requirements:
- Avoid unnecessary details
- Specify how many people mentioned specific core idea (use numbers, not words), most mentioned on top
- no suggestions
- no indications
Example output:
1. **Core idea text:** explainer text
2. **Core idea text:** explainer text
3. **Core idea text:** explainer text
You’ll get a clean list of what matters most to your users—fast. But there’s a secret: AI always performs better if you provide more context. For example:
Analyze the responses from this onboarding experience survey—the users are new SaaS customers. My goal is to find what makes onboarding successful, spot pain points, and extract specific improvement ideas. Highlight anything related to feature discovery, learning curve, or support.
Prompt for follow-up: Once you have your core themes, dig deeper by asking: “Tell me more about [theme].” For example, “Tell me more about issues with feature discovery.”
Prompt for specific topic: Need to check if a topic came up? Use “Did anyone talk about [onboarding tutorial]?” Add “Include quotes” if you want direct feedback.
Prompt for pain points and challenges: When you want to know what frustrated your users most during onboarding, try: “Analyze the survey responses and list the most common pain points, frustrations, or challenges mentioned. Summarize each, and note any patterns or frequency.”
Prompt for personas: Spot different user archetypes with: “Based on the survey responses, identify and describe a list of distinct personas—similar to how ‘personas’ are used in product management. For each persona, summarize their key characteristics, motivations, goals, and any relevant patterns observed.”
Prompt for sentiment analysis: To gauge overall mood, use: “Assess the overall sentiment expressed in the survey responses (e.g., positive, negative, neutral). Highlight key phrases or feedback that contribute to each sentiment category.”
Prompt for unmet needs and opportunities: Look for hidden growth areas: “Examine the survey responses to uncover any unmet needs, gaps, or opportunities for improvement as highlighted by respondents.”
For more ideas on structuring your onboarding survey, check out what are the best questions for a user survey about onboarding experience.
How Specific analyzes qualitative data by question type
Specific’s AI doesn’t just summarize raw text—it organizes every insight by question type, making your onboarding survey analysis easier to digest and share.
Open-ended questions (with or without followups): Each open-text question gets a full summary, including all clarifying follow-up answers. You see the “big picture,” not a sea of unstructured comments.
Choice questions with followups: If your survey asks users to pick an option, then dives deeper (“Why did you choose that?”), each choice gets its own tailored summary—surface what drives preferences between different onboarding paths or features.
NPS (Net Promoter Score): Promoters, passives, and detractors each get their own breakdown. You know what delights your biggest fans and what frustrates those at risk of churning.
You can replicate this analysis in ChatGPT, but you’ll have to organize, format, and repeat prompts by hand. Specific does it automatically, saving serious analyst time.
Want to launch an onboarding NPS survey fast? Try Specific’s NPS survey builder for onboarding experience.
How to tackle context limit challenges with AI
One big challenge when using GPT-based tools: Context size limits. If you’ve got hundreds of onboarding user responses, you can’t just cram everything into ChatGPT. Here’s how Specific solves it (but you can do the same tactics manually):
Filtering: Focus the analysis on the right data. Filter survey conversations by users who replied to particular onboarding questions or chose certain answers—AI only analyzes what’s relevant.
Cropping: Narrow down which questions are sent to the AI. Crop your analysis so that only specific areas—like feedback on onboarding tutorials—get processed. This keeps your AI analysis focused and fits within context limits.
Combining both lets you scale your onboarding response insights without losing detail or running into technical walls.
Collaborative features for analyzing user survey responses
Collaborative survey analysis is a common pain point. Teams are busy, multiple people need to dig into the data, and sharing your onboarding survey findings often means endless docs, copy-pastes, or missed context.
Chat and collaborate on insights. With Specific, analyzing onboarding survey data is as simple as chatting with AI. Every team member can start their own analysis chat, apply different filters (e.g., focus on trial users or power users), and the system tracks who started each chat—keeping workflows organized.
Transparency and accountability. In multi-user chats, you see who asked what—the sender’s avatar is visible for every message. This makes it easy to keep track of conversations, splits analysis by topic (say, one chat for onboarding pain points, another for feature requests), and makes collaboration across product, customer success, and research seamless.
Deep dives, zero chaos. Team members can swap insights and follow up on each other’s AI-powered summaries, all inside the same platform—no more fragmented analysis or lost context. Need to create a new onboarding survey with lessons learned? Use the AI survey generator or the ready-made onboarding survey preset.
Create your user survey about onboarding experience now
Discover user insights instantly—launch your onboarding survey, collect deeper answers, and turn AI analysis into action in minutes with Specific.