April 16, 2023
System 1, developed by Kahneman (2011), Thinking Fast, and Slow – refers to the brain’s processing of information quickly, instinctually and emotionally, and this is usually done unconsciously. The opposite of System 1 is System 2, which is responsible for slow, conscious, logical and deliberative thinking.
The book Thinking, Fast and Slow, Kahneman, a Nobel Prize-winning psychologist, examines how cognitive biases and heuristics shape our decisions, often leading to errors in judgment. The book blends psychology and behavioural economics to reveal the limits of rationality. It’s an insightful guide to understanding human thought processes, decision-making flaws, and how to think more clearly.
System 1 research is any method which taps into unconscious thoughts, emotions or behaviours, which would otherwise be inaccessible. System 1 Research Methods include EEG, fMRI, eye-tracking, IAT, IRT, facial emotion analysis, and biometric measurements such as GSR and heart rate variability.
The majority of our thoughts, decisions and behaviour are governed by our unconscious, system 1 processing. They rely on gut instinct and are done automatically and with little to no effort. This is because our minds simply could not process the massive amounts of information that we encounter in our daily lives, so it is automated.
It is therefore essential to understand this System 1 to reveal unconscious thoughts, decisions and biases that lead consumers to make certain decisions.
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Heuristics are mental shortcuts used to simplify decision-making. Common types include availability, representativeness, anchoring, and affect heuristics. They help speed up judgments but can lead to cognitive biases. Heuristics are essential in everyday thinking, user experience design, and behavioral research, highlighting how humans process information under uncertainty or limited time.
Data science is the practice of extracting meaningful insights from large and complex datasets using statistical analysis, programming, and machine learning. In market research, it helps identify patterns, predict behaviours, and support data-driven decision-making across customer segmentation, trend analysis, pricing strategies, and campaign optimisation.