Understanding Surveys using Highlight Tables

Surveys on topics such as customer satisfaction are rich with qualitative data, but analysis often requires quantitative comparisons, aggregation, etcetera. Steve Wexler, Director of Research at the eLearning Guild, discusses how some straightforward techniques in Tableau lead to "visualizations that people can grok from the back of a conference room."

The first samples of customer survey results that Steve demonstrated used stacked bar charts to reveal the proportion of responses in each of the categories, such as "Disagree" or "Strongly Agree". Sorting the data on one of the categories could reveal strong customer preference across a range of products, for example. However overall customer satisfaction should take into account all categories, and stacked bar charts made the remaining categories difficult to visually compare. The root of this problem is the qualitative nature of the data.

Steve tackled this challenge by building calculated fields to convert responses into quantitative values on a 0-5 scale, known as a Likert scale. This allows for aggregation such as averages to measure responses across a range of questions. To demonstrate this, Steve showed results from the eLearning Guild research which compared corporate plans / progress in developing mobile learning platforms versus these corporations' opinions of the value of mobile learning.

To render this in a way that could be grokked from a distance, Steve turned to a data visualization known as highlight tables. Like heatmaps applied to textual tables, highlight tables quickly identify the magnitude of values in each cell. While one dimension separates responses to each question, the second dimension of the table could be used in many ways: for example to aggregate responses by company size, by mobile platform preference, or by the company's plans for mobile learning. In interacting with the audience, Steve demonstrated that the survey response trends and correlations are clearly visible.

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