AI analysis overview
The AI Analysis feature helps admins quickly understand, categorize, and analyze large volumes of resident input. It works for both ideation and surveys, offering:
Qualitative analysis: Summarizing textual input from ideas, comments, or survey responses
Quantitative analysis : Exploring correlations between demographics, tags, and survey responses
ℹ️ Access to this feature depends on your plan.
AI analysis interface
The interface has four main columns:
Tag Management: Create and manage tags to group inputs
Input List: Shows all contributions to analyze
User & Filter View: View anonymized user responses, apply filters, or drill into comments
Summaries & Questions: Summarize filtered inputs or ask AI for insights
How to use AI analysis?
Go to the project’s Insights
Click the AI Analysis widget in the top right
Optionally:
For surveys: Go to an open question and click Explore for a specific questions
Add follow-up question within the AI analysis Ask a Question
Use Filters to use the AI functionality within a specific context (e.g., filter on demographics, timestamps, a specific answer to a question, ...)
ℹ️ Engagement level filter is only available for ideation/proposals projects
Tagging methods in AI analysis
Tagging helps cluster and interpret user input. The tool supports:
Fully automated tagging: AI assigns common tags.
By label: Create your own tags.
By example: Provide manual examples to teach AI tagging.
Sentiment tagging: Mark input as positive or negative.
Language detection: Identify the input language.
Manual tagging: For full control, you can tag every input manually.
What are auto insights?
Auto‑Insights connects tags, demographics, and survey questions to uncover patterns.
Displays key correlations (e.g., which age group engages with which tag)
Includes a heatmap view, with boxes marked if a correlation is statistically significant
Unit of analysis can be switched between:
Inputs (contributions)
Likes
Dislikes
Participants
Difference:
In ideation, Auto‑Insights connects demographics to tags
In surveys, Auto‑Insights links demographics, tags, and survey questions
You can get into the auto-insights by pressing explore below the demographic information of the AI tool interface.
Why is human oversight recommended?
The Summarize and Ask a Question tools generate quick insights but require human oversight.
Summaries include clickable references to original inputs for transparency
Overloading the AI with too many inputs can reduce accuracy—filters & tags help
Missing in-line references may happen for reasons like:
Contextual relevance (references not needed)
Balancing readability (avoiding excessive citations)
System refinements (constantly improving)
Hallucinations: While rare, the AI might occasionally generate information that was not explicitly present in the original dataset.
Exaggeration: The AI might emphasize certain themes or ideas more than others, potentially skewing the overall interpretation.
Biases: Results may contain various biases. These can arise, for example, from unbalanced data in the model’s training, differences in language and expression, and a lack of contextual understanding. In particular, irony, sarcasm, dialect, youth slang or context-sensitive phrasing may be misinterpreted.
⚠️ Summaries are not 100% accurate. Always cross-check key findings with the original data.
AI Masterclass
For a complete demonstration of our AI Analysis tool, check out the recording of our AI Masterclass. Select your language for the appropriate recording.