User experience feedback

Felicity Wild
Saturday 21 November 2015

Here at the Digital Communications team we believe in taking a user-centred approach to our work, and we’ve written a lot about this.

We endeavour to put the user at the centre of our decision making process with a focus always on what people need, not what the organisation needs.

Collecting user experience feedback

An important element of this approach is collecting user experience feedback on new products to evaluate the extent to which our designs are successfully meeting user needs.

Our chosen tool for collecting user experience feedback is Survey Monkey, a web-based survey solution. We have used this recently to great effect in collecting feedback from prospective postgraduate students on factors influencing their decision on where to study, and also from current students who downloaded the Orientation 2015 app developed by Student Services.

Analysing the results

What makes Survey Monkey particularly useful is the wide range of filtering and reporting functions on offer, allowing you to interrogate survey data in a variety of different ways.

For a quick overview you can view a simple summary of survey data or raw responses – sample size will dictate which of these is the most useful. There is also the option to isolate individual responses to investigate any outliers or anomalies in your data.

Depending on your purpose, there are also various functions available to drill down further into your data, including rules to filter and compare in order to explore trends and patterns.

Creating custom reports

When analysing your survey results, you can use rules to create custom views of your data. These can be saved within Survey Monkey or exported as custom charts and data tables.

  • Filter: this allows you to focus on a specific subset of your data based on certain criteria such as respondent metadata.
  • Compare: select two or more answer choices for a given question to see a side-by-side comparison of how people who selected those answer choices answered the rest of the survey.
  • Show: only display the results from certain questions of the survey.
An example of compare view

Basic statistics

Survey Monkey can also run some basic statistical analysis on your survey data, these include:

Statistic Description
Minimum and maximum     The lowest and highest value, or answer choice, selected by at least one respondent.
Mean The average of all responses.
Median The midpoint at which all responses are evenly divided above or below. If there is an even number of responses, the median is the average of the middle two answer choices.
Standard deviation The amount of spread or distance from the mean.

For more sophisticated statistical analysis of survey data, however, specialist software such as SPSS is necessary.

Text analysis

Responses to open-ended questions can be categorised (by keywords) and you can also create a word cloud (or cloudview, as Survey Monkey calls it) with larger text signifying word importance.

An example of cloudview
An example of cloudview

Cloudview is not based on word frequency, but rather distinguishing words. For example, if 100 people responded with “I like…”, the important word would be what follows, rather than taking the phrase “I like” as important or unique.

The importance of analysing user feedback

Sample size, question types and survey objectives will all dictate which of these functions are most useful, but the importance of analysing survey data should never be overlooked. Moving beyond simple comparisons can illuminate patterns and trends that are not immediately obvious and help to draw valid conclusions on the extent to which user needs are met – an essential part of a user-centred approach to design.

Related topics

Share this story

Leave a reply

By using this form you agree with the storage and handling of your data by this website.