Nowadays data is a prerequisite for any pitch to trial, ramp-up or sunset product features. Metrics inform strategic product discussions and guide key decisions on product direction. Be it A/B test results, trends of AAARR metrics, or the latest NPS report, data finds its way to board rooms and product review sessions, usually translated to a visual medium as a chart or graphical display of some sort.
However, despite its omnipresence, it is often misrepresented, misunderstood or both. That is so because we easily fall prey to cognitive and perceptive biases when interpreting data as well as when presenting it to others. This is specially the case when data is visualised and often happens by accident; deception does not require intention.
In this talk, I’ll explore common pitfalls of data visualisation and provide guidelines on how to spot distortions in how data is presented, how to prevent them, and how to design visualisations that are simple, effective, and fit for purpose.