Typically, this section might address areas relating to (in no particular order):

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• statistics: split testing, correlation, metric selection, P values, qualitative vs quantitative...

• data collection: server side tagging, privacy, user consent, ITP, cross device, marketing attribution, voice of customer, question framing,...

• the tech stack: BigQuery, SQL, Python, Looker, GDS, GA4, [Google] Tag Manager,...

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There is something else that underpins all of the above, human decision-making bias.

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As analysts, data scientists, managers, directors etc, we all exhibit cognitive bias in our decision-making. It's inescapable, and it is the single most likely attribute that can lead us to make poor decisions.

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Confirmation bias is common in much of what we do as stakeholders.

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Anchoring bias and egocentric bias prevent us from taking on board new evidence and adjusting our position in order to make better decisions. They are present in all hierarchical organisations.

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These biases are often interlinked. Being aware of them can help us mitigate their impact and lead to better decision making based on currently available evidence.