How does the AI conversation work?

Our AI agent uses natural language processing to understand responses and ask intelligent follow-up questions. It adapts to each respondent's style, clarifying vague answers and encouraging detailed responses. The conversation flows naturally, just like chatting with a real person.

What makes conversational surveys better than traditional forms?

Conversational surveys capture 10x more qualitative data because respondents express themselves naturally. Traditional forms limit responses to predefined options, while our AI can explore nuances, clarify ambiguities, and adapt to individual communication styles.

Can I try it before committing?

Yes! We offer a free plan that lets you test all features with up to 10 responses. No credit card required. You can upgrade to a paid pack anytime to get more responses.

How long does it take to set up a survey?

Most surveys can be set up in under 10 minutes. Simply define your goals, add your questions, and our AI will handle the conversation flow. You can preview and test the experience before launching.

What languages are supported?

Our AI currently supports 25+ languages including English, Spanish, French, German, Chinese, Japanese, and more. The AI automatically detects the respondent's language and continues the conversation in that language.

Survey Analytics Complete Guide: How to Analyze Survey Responses and Extract Insights

Survey analytics is a crucial stage in understanding your audience and extracting meaningful insights from their responses. The platform offers several levels of analysis — from individual respondent reports to aggregated results and AI-generated insights. This guide walks you through all available analytics tools and how to use them effectively.

1. Basic Survey Statistics and Respondent Dialogues

When you open a survey, the platform displays an overview with key metrics:

Survey status — Active, Paused, or Closed
Number of participants
Completion rate
Number of questions

This high-level survey summary helps you quickly evaluate engagement and participation.

Survey analytics dashboard showing respondent list

1.1 Respondent Analytics — List of All Participants

Below the summary, you'll find a respondent table showing:

Name
Status: Started / In Progress / Completed
Start date
Last activity
Number of messages in the conversation
Number of reports generated for this respondent

This is the first layer of respondent analytics, providing quick visibility into who completed the survey and how they interacted with the AI agent.

1.2 Opening a Respondent Profile

Click any respondent to open their detailed profile.

The Dialogue tab displays:

the full conversational transcript,
all questions from the AI agent,
the respondent's answers,
contextual follow-ups,
both numerical and open-text responses.

This transcript is essentially a structured interview, allowing you to understand not only the respondent's answers but also their reasoning, tone, and motivations — something traditional forms cannot capture.

2. Micro-Analytics: Individual AI Reports for Each Respondent

Each respondent has a dedicated Response Analytics tab. This is where you can generate personalized AI reports based on their full conversation.

Micro-analytics help you deeply analyze a single user's feedback, emotions, and behavior patterns.

2.1 Available AI-Generated Reports

There are five types of reports you can create:

📊
General Report

A universal summary of the conversation, including key insights, emotional analysis, and major takeaways.

👥
HR Report

Designed for HR professionals:

•engagement and motivation indicators,
•burnout or turnover risks,
•individual strengths,
•actionable HR recommendations.

🎯
Manager Report

For team leads and people managers:

•high-level summary,
•productivity and motivation signals,
•actionable next steps,
•suggested topics for 1-on-1 meetings.

💡
Product Report

Focused on product discovery and user research:

•user pain points,
•UX insights and feedback,
•feature requests,
•a prioritized product backlog.

📋
Business Analyst Report

Ideal for BA and technical teams:

•functional and non-functional requirements,
•User Stories and acceptance criteria,
•risks and open questions,
•clarifications needed for scoping.

2.2 How to Generate Reports

To generate a report:

Open the respondent list.
Click the respondent's name.
Go to the Response Analytics tab.
Select the report type → click Generate.

Each report is dynamically created by the AI based on the entire conversation context.

3. Macro-Analytics: Aggregated Insights for the Entire Survey

For high-level survey data analysis, go to the Survey Analytics tab.

Macro-analytics consolidate all responses and provide an overview of patterns, trends, and numerical distributions.

3.1 Analytics for Scale and Multiple-Choice Questions

Two question types are supported:

Scale Questions (1–10)

For each question, you'll see:

•average score,
•median score,
•total number of responses,
•distribution across the scale.

Multiple Choice Questions

Displayed metrics include:

•number of respondents per answer choice,
•percentage distribution,
•visual charts for quick interpretation.

This helps you instantly understand overall preferences and sentiment.

3.2 AI Insights — Automated Findings From All Survey Data

This is one of the most powerful features of the platform.

AI Insights analyze:

scale ratings,
multiple-choice selections,
open-text answers,
respondent explanations,
emotional tone,
and the full conversational context.

When you click Generate Insights, two analytical blocks appear:

🔍
Key Findings — Critical Observations

This section highlights the most important insights across the entire survey. Each finding includes:

•severity level (Critical / High / Medium / Low),
•a concise explanation,
•number of mentions supporting the insight.

AI may detect:

•missing data or insufficient sample size,
•contradictory responses,
•unusually strong or weak patterns,
•lack of qualitative explanations,
•important behavioral or emotional cues.

Example:
Critical: The dataset is too limited to form generalized conclusions; additional responses are required.

These findings help you instantly grasp the reliability and interpretability of your data.

📈
Identified Trends — Patterns and Recurring Themes

AI scans all responses and reveals trends backed by evidence from dialogues.

Each trend includes:

•a title,
•a clear description of the pattern,
•evidence (quotes or numerical data pulled directly from conversations).

This transparency allows you to understand not only what the trend is, but why it appears.

Example:
High scale ratings lack supporting qualitative explanations — motivations remain unclear.

These trends are especially valuable for research, HR analytics, and product discovery, where qualitative insights drive decision-making.

3.3 Regenerating AI Insights

Click Regenerate Insights to:

refresh results after new responses are submitted,
obtain alternative interpretations,
update insights when survey structure changes.

AI reanalyzes the entire dataset and generates refined findings.

3.4 Segment-Based Insights — AI-Driven Audience Segmentation

In addition to statistical charts and AI-generated findings, the platform also provides Segment-Based Insights — an advanced macro-analytics feature that automatically groups respondents into meaningful segments based on their behavior, priorities, and conversation patterns.

This tool helps you understand not just what respondents said, but which types of users exist within your audience and how they differ.

How segmentation works

AI analyzes:

response patterns,
tone and intent in dialogues,
shared frustrations or motivations,
common priorities and decision criteria,
behavioral signals from the conversation flow.

Based on these patterns, the system groups respondents into distinct clusters and generates insights for each segment.

What each segment includes

Every identified group displays:

Segment name (e.g., "Technical Complainers", "Efficiency Seekers")
Number of respondents in the segment
Short behavioral profile explaining their characteristics
Key Insights, highlighting:
- •what motivates them,
- •what blocks them,
- •what could improve their satisfaction,
- •what they value most.

Example:

•Technical Complainers — users limited by technical issues but likely to become advocates if stability improves
•Efficiency Seekers — goal-oriented users wanting better filtering and faster matching
•Communication Focused — users frustrated by message organization and notification clarity

These insights help teams understand why different groups behave differently.

Why Segment-Based Insights matter

This feature adds a new dimension to macro-analytics:

Product teams spot clusters with distinct needs and can prioritize improvements.
Marketing teams get clearer user personas for targeted messaging.
HR and research teams can differentiate sentiment across internal groups.
Executives gain a strategic view of audience segments and what drives each group.

Segmentation transforms raw survey responses into structured personas, making strategic decision-making faster and more evidence-based.

Conclusion: Multi-Level Analytics for Deep Understanding

The platform's analytics capabilities combine individual respondent insights with aggregated survey-wide data, powered by AI that understands both quantitative metrics and qualitative context.

From reading detailed conversation transcripts to generating specialized reports for HR, product, or business analysis — the platform gives you complete visibility into your survey data.

Whether you're conducting employee engagement surveys, product research, or customer discovery, these analytics tools help you extract actionable insights that drive better decision-making.

Ready to unlock deeper insights from your surveys?

VibeSurvey's analytics tools help you understand not just what respondents say, but why they say it. Start getting actionable insights today.