Visual Reasoning Strategies for Effect Size Judgments and Decisions
Alex Kale, Matthew Kay, and Jessica Hullman
Copilot can do a better job at visualizing uncertainty. Specifically when it comes to:
significance (or lack thereof) based on number of impressions
dealing with bad/uncertain data (e.g. ""unknown"" placement type)
predicting future results- “how likely are you to hit your goal”, “how likely are you to deliver in full”
The last point specifically sparked some discussion- maybe something similar to the NYTimes needle visualizations (link) could be used.
Our problem: uncertainty is a hard topic for our hands on keyboard users. We should expect some pushback from users when it comes to visualizing this as real advertiser money is on the line. Traders tend to anchor to a single number and are less comfortable with ranges. How can we could better manage user expectations and build trust while incorporating uncertainty?
Introduce users to new chart types, color scales, etc. that studies have shown to be more effective?Meet them where they are visualizing data with chart types they are used to?
We landed on a gradual introduction of new visualization techniques as well as always providing information on why certain changes were made.