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A Matrix Rating question allows respondents to rate several items using the same rating scale. In the Analysis section, Enquete helps you review these results in different formats so you can compare how each item performed across the scale.
In the example shown, respondents were asked to rate the effectiveness of different treatments they received. This type of analysis is useful when you want to compare multiple items in one question instead of reviewing them one by one.
At the top right of the analysis panel, Enquete provides four views:
Heatmap
Grouped Bar
Averages
Table
Each view helps you analyse the same data in a different way.
Use Heatmap to quickly spot where responses are concentrated across items and rating values.
Use Grouped Bar when you want a clearer comparison of response counts for each rating across all items.
Use Averages to identify the overall average score for each item more quickly.
Use Table when you want a more exact breakdown of counts and values.
The Heatmap shows the relationship between each item and each rating value. The rows represent the items, and the columns represent the rating scale.
Each cell shows how many respondents selected that rating for that item. This helps you identify where the highest concentration of responses appears.
In this example:
Lifestyle changes received ratings across all values, with more responses at 1 and 3
Therapy also shows responses spread across the scale
Medication has its strongest concentration at 2
This makes it easier to compare patterns across all items in one view.
At the top right of the chart area, the three-line menu icon allows you to download the current chart.
Depending on the available options, you can export it as:
PNG
CSV
SVG
This is useful when you want to include the analysis in a report, presentation, or external review.
To interpret Matrix Rating results, first compare how each item performs across the rating scale.
Look for where responses are most concentrated. If an item receives more responses in the higher rating values, it usually means that item was rated more positively. If responses cluster around lower values, it may indicate weaker performance or lower satisfaction.
Then compare the items against each other. This helps you see which item performed best overall and which item may need more attention.
The different views support different types of interpretation:
Heatmap helps you spot response concentration quickly
Grouped Bar helps compare items more visually
Averages helps identify overall performance faster
Table helps verify exact counts
When analysing a Matrix Rating question, pay attention to:
which items receive more high ratings
which items receive more low ratings
whether responses are concentrated or spread across the scale
whether one item clearly performs better or worse than the others
whether the averages match the detailed response distribution
This helps you understand not only the score pattern for each item, but also how the items compare with one another.