Turn map comments into actionable insights

Asking respondents to mark places on a map and explain in their own words what's going on there is one of the most common ways to use Maptionnaire. With hundreds or thousands of map comments, reading them one by one isn't realistic. The analysis tool helps you find the hotspots, understand what people say about them, and share the results, often in minutes rather than days.

This article walks through the whole process. Each step links to a detailed how-to.

1. Look at the map responses

  1. Go to Analyze > Map responses and toggle on the map questions you want to look at. The number next to each question shows how many responses it received.

    Map questions toggled on in Map responses
  2. Click any point, line or area to read the comment and the pop-up answers attached to it.
  3. Zoom in on a busy area and check the Respondents tab next to Map responses. It shows how many individual people left the responses visible on screen, so you can tell a real hotspot from one very active respondent. Count the number of map responses

    Map responses and Respondents counts for the visible area
  4. If you find spam or responses that shouldn't be included, click them and select Hide response or Hide all responses from this respondent. Hide individual map responses from view

2. Find the hotspots

All of these are in the Tools menu in Map responses. Pick the one that matches your data:

  • Cluster analysis (points): groups points that sit close together into clusters, and tells you who made them and what they talk about, compared with the rest of the data. The best starting point for most map comment questions. Cluster analysis
  • Corridors (lines): traces the routes where many drawn lines run close together, such as popular or problematic walking and cycling routes. Corridor analysis
  • Heatmap (points): shows the densest concentrations of points on a color scale. A quick visual for reports. Create a heatmap
Clusters generated from map point responses

For Pop-up map or Select map questions, the map already shows how many times each feature was selected as a choropleth map. Analyze Pop-up map or Select map responses

Tip: lowering the opacity of points also makes hotspots stand out, as overlapping points show up in a deeper color. Change the color, size, opacity and icons of points, lines, and areas

3. Find out what people said about a hotspot

Click the arrow next to a cluster or corridor to see what sets it apart: the profile of the respondents and the themes in their answers, compared with the overall dataset.

Cluster details compared with the overall dataset

To dig deeper into one place, narrow all your charts down to it. You have two options:

  • Save the cluster or corridor as a view. Click Save as new view, then go to Charts and add any questions. The charts and open comments now show only responses related to that cluster.
  • Draw a spatial filter. Open Filters, click Draw on the map, draw a border around the area and click Apply. Use this for any area you choose, such as an intersection or a park. Spatial filters
Drawing a spatial filter on the map

Either way, you can now see who the respondents in that area are (for example, residents or business owners) and how they answered every other question in the survey.

4. Make sense of the comments with AI

In Charts, the comments attached to map points, lines and areas appear as a list, just like open-text questions. With large numbers of comments, AI does the heavy lifting:

  • AI tagging: open the comment question in Charts and click Generate tags. The AI finds the 5–10 most common themes and tags every comment with them. Review and edit the tags, or type in your own set of tags and re-tag. Tags also work as a map filter, so you can show only the comments about, say, "unsafe crossings". Tag open responses with AI
  • Ask questions about your data: add the questions you want to analyze to your view, then open Tools > Ask questions about data and ask, for example, "Summarize the main concerns people have about this area". The AI only reads what's in your current view, with your filters applied, so combine it with a spatial filter or a saved cluster to ask about one place. To include pop-up questions, toggle on the map layer in Map responses first. Use AI to summarize survey responses
  • Sentiment analysis: a quick look at whether comments are positive, neutral or negative. It uses Amazon Comprehend, not Claude. Analyze open text responses (with AI)
Generate Tags button and tagged responses

You can also tag map responses by hand: click a point, line or area, type a tag under Tags and press Enter. Organize map responses with tags

AI tools save a lot of time, but treat their output as a draft. Check tags and summaries against the actual comments before you publish or share them, especially when a theme is based on only a few comments.

About Claude and data: AI tagging, asking questions about your data and the AI report use Claude. As of August 2026, Maptionnaire uses Claude Sonnet 4.6, running on Amazon Bedrock — the same AWS infrastructure that hosts the rest of Maptionnaire. The model does not retain your responses after processing them, and does not use them to train models. All AI processing of response data happens in the same AWS region as your data — EU data stays in the EU, US data in the US.

5. Compare groups

Do different groups point out different places? Two ways to find out:

6. Save and share your findings

For an overview of all the reporting options, see Quick guide to reporting and sharing survey data.

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