Describe a time the data showed something surprising or contradicted what people believed.

These are the most valuable analyses, and the hardest to land politically.

Structure it as:

• The belief and where it came from. Usually an assumption nobody had tested, or a conclusion drawn from an earlier report read incorrectly.
• What the data actually showed. Good examples: a channel everyone considered wasteful was driving assisted conversions; a popular page had the highest exit rate; mobile traffic was large but converting at a fraction of desktop; or a big traffic increase was bot traffic.
• How you verified before presenting. This is the important part. Check the tracking, check the date range, check for filters and bots, and see whether the pattern holds across segments. Presenting a surprising finding that turns out to be a measurement artefact is costly.
• How you presented it, and how people reacted.

Note: If the finding was resisted, say so and describe how you handled it — usually by proposing a small test rather than demanding the belief be abandoned. Letting the data settle it is far more effective than arguing.