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Analysing the results of ranked questions
Analysing the results of ranked questions

Learn how to use and analyse answers from the ranked question type

Parm Bansil avatar
Written by Parm Bansil
Updated over a week ago

Ranking questions are used to show consumer preferences for a set list of answers. In this example we've asked consumers to rank the topics they are interested in following on social media, with their favourite at the top and their least favourite at the bottom. There were ten answers to be ranked, so the scale will go from 1 (their favourite topic) to 10 (their least favourite topic). 

The default view presents the results in a table format, with the average rank on the left. Here food had an average rank of 3.9 (on our 1-10 scale). These averages alert us to the range of results. A tight range, for instance the most preferred topic scoring 3 and the least preferred scoring 5, would tell us there is not a large preference for one topic, they all scored similarly on average. As the favourite topic is ranked at 3.9 and the least favourite scored 6.6, we know there’s a relatively large preference for the favourite and adversity to the least favourite. 

Next to the average rank, you can see the percentage of people who put each topic in each position. Each horizontal row adds up to 100% of respondents, so looking across the top row for ‘Food’, 19.4% of people ranked food as their favourite topic, 19.1% as their 2nd favourite topic, 15.8% as their 3rd favourite, and so on. Each vertical row also adds up to 100% of respondents, so you can easily read down how each topic fared in each of the positions.

If you filter by demographic or by answer, this will update the average rank given by that specific group of people, and coloured arrows indicate whether these selected people ranked them higher than the average of the entire sample (in which case there will be a green arrow), or lower than the average (in which case there will be a red arrow). 

Here we can see that when you toggle the demographics to include only females, females ranked food, fashion, design & art higher than the sample as a whole did.

You can also change your default view to a stacked bar chart, which gives a more visual representation of your results. If you don't want to see all 10 ranks, you can decide to hide certain items from the chart by clicking on the legend items. You can also easily download the chart as a .png file.

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