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How to analyze churn data and make data-driven decisions
The importance of customer feedback
How to improve customer experience
Line Charts, Circles and Bars 📈📊
An experiment was done to find out whether these styles(bar charts, line charts, scatterplots, and plain text) differ in how "casual" they make the data appear to people.
4 correlations were chosen to display visually. 4 different visualizations for each scenario.
Each participant saw 4 styles one representation of each scenario.
After they controlled for the relative plausibility of each scenario, the type of style didn’t observably impact ratings
For the causal statements: Participants rated information they saw in bar charts as the most causal and scatter plots as the least causal
4
13 reads
MORE IDEAS ON THIS
More Aggregation, More Assumptions of Causality
The same experiment was done, this time they developed bar charts, line charts, and scatterplots with three different levels of aggregation.
This time the type of chart had only a small effect on participants’ ratings of causality. Much more significant, however, was the effect of aggregati...
4
9 reads
Correlation isn't causation
According to new research from the Kellogg School, how data are visualized can significantly impact our interpretation of what we’re seeing sometimes for the worse. Our efforts to simplify charts by grouping data into smaller numbers of “buckets” (say, two bars on a chart as opposed to ten) seeme...
3
21 reads
How to Visualize Responsibly
Be mindful when you aggregate, because the assumption people have may become a causal one. So think carefully about how you present your data and maybe iterate with your own design team or with your data analysts so people don’t misinterpret what you’re trying to say.
Even the most sophisti...
3
14 reads
Related collections
More like this
More Aggregation, More Assumptions of Causality
The same experiment was done, this time they developed bar charts, line charts, and scatterplots with three different levels of aggregation.
This time the type of chart had only a small effect on participants’ ratings of causality. Much more significant, however, was the effect of aggregati...
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