SurveyMonkey Click Map Question

Using image answer options for richer survey insights.

challenge

Images in survey questions

Using images in survey questions is an effective and engaging way to get opinions from your respondents.
A heatmap question is a common research tool that allows survey respondents to provide feedback on an image. The respondent is asked to click anywhere on an image, giving feedback or reactions. Heatmaps are a form of visual storytelling, helping researchers instantly understand respondents' perceptions.

The applications for heatmap questions are practically limitless, but the most popular use cases are Ad Testing, Logo Testing, Packaging Testing and Prototype testing. This survey feature is critical for market research surveys and usability testing.

How might we help researchers collect precise insights from clicks on image-based questions?

The limitations of Heatmap survey questions

When doing our initial research, we learned that researchers often struggle with precision visualizing the responses to heatmap survey questions.

That is because, traditionally, heatmap visualizations use colour variations to show the magnitude of the data. Usually, hot colours (red, orange, yellow) represent a higher density of clicks, whereas cold colours (green, blue) lower the density of clicks. Additionally, the colours show as blurred areas over the image to illustrate a smooth transition from one place to another.

But traditional heatmap visualizations are not suitable for when researchers want to know precisely where the respondent clicked. Another problem is that some critical data get lost in the transitions from one colour to another.

Traditional heatmap visualizations fail to provide, at a glance, precise information about respondents' clicks.

SurveyMonkey Click Map Question Type

Based on the research, our challenge was to create an alternative question type that offered both an at-glance view of the total clicks and a precise view of each response.

Like a heatmap, the Click Map questions let researchers get feedback directly on an image. Researchers can add an image to their survey and ask respondents to click a particular spot on the image. For example, uploading a product picture and then asking people to click the part of the package that is most appealing to them.

However, when analyzing the results, each response to a Click Map question shows a dot over the image. That way, the researcher knows precisely where the respondent clicked. Moreover, clicking on one of the dots takes the researcher to the responses this person gave to all the other survey questions.

Adding a Clickmap question to a survey is easy and straightforward.

When analyzing a Click map question, the researcher can see precisely where the click is and trace that click to the individual response.

Future improvements

The Click map question was a successful addition to all SurveyMonkey's image-based question types. Survey creators reported a positive experience and really enjoyed the analysis capabilities this new question type offered. Building on offering precise insights from an image-based question and responding to user feedback, the team started to explore future improvements to the Click map.

Image regions
Allowing survey creators to define regions to images unlocks countless possibilities for the click map question type. For example, defined areas make it possible for researchers to break down the analysis in clicks per area, and that's powerful for testing iterations of the same image.

Another possibility is to combine defined regions with advanced logic features such as branching. That way, if the respondents click on a specific area, they may skip certain questions or pages. Another example of how regions can enhance the respondent experience is follow-up questions. As illustrated with the design below, a follow-up question pops up after the respondents click on the image. The respondents can provide more details about their choice with quick react buttons and an open-ended text box.

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© Dan Bianchi, 2024

© Dan Bianchi, 2024

© Dan Bianchi, 2024