3.1 Why Consumer Behavior Matters
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Explain the importance of understanding consumer behavior and describe how marketers use behavior insights to design products, messaging, and experiences.
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Compare low-involvement and high-involvement buying decisions and outline the five-step consumer decision-making process.
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Describe the key factors that shape buying behavior—including cultural, social, psychological, personal, and situational influences—for both individual consumers and businesses (B2B).
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Apply the principles of segmentation, targeting, and positioning (STP) to identify meaningful customer segments and develop effective marketing strategies.
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Evaluate how usage situations and emotional factors impact segmentation success, drawing lessons from real-world brand examples and cautionary tales.
Why do people buy what they buy? And why do they stay loyal to some brands while ditching others? These questions are at the heart of The study of how people (or businesses) make decisions about what to buy, when to buy, how much to buy, and why., the study of how people (or businesses) make decisions about what to buy, when to buy, how much to buy, and why.
As marketers, we don’t just guess what customers might want. We analyze their behavior so we can do the following:
Why it matters: Understanding consumer behavior lets us influence it—whether that’s getting someone to try a new product, remain loyal to a brand, or even advocate for it.
Strategy in Action: Netflix Knows What You’ll Watch Next
Netflix doesn’t just recommend random shows; it collects detailed data on what you’ve watched, what you’ve searched for, and even when you tend to binge. If you usually watch thrillers late at night but prefer light-hearted comedies on weekend mornings, Netflix adjusts its suggestions to match your habits. This behavior data allows Netflix to predict what you’re most likely to enjoy next and keep you watching longer.
Why does this matter?
Reducing The rate at which customers cancel subscriptions. is critical for streaming services. By offering highly personalized recommendations, Netflix has successfully kept viewers engaged and reduced cancellations. Subscribers who receive personalized suggestions are 75% more likely to stay than those who don’t engage with personalized content.
Krysik, A. (2024, August 28). Inside the Netflix Algorithm: AI Personalizing User Experience. Stratoflow. https://stratoflow.com/how-netflix-recommendation-system-works/
Bhagyashree. (2025, April 30). How Netflix Uses Big Data to Personalize Your Viewing Experience. PromptCloud. https://www.promptcloud.com/blog/netflix-big-data-for-personalized-viewing-experience/
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