Here's a full walk-through of your slide deck, page by page, with simple explanations and examples for each idea. This whole chapter is about how companies do research to understand customers. Before diving in, here's the big picture: the chapter walks through 5 main steps of doing consumer research, in order. I'll point out which step each page belongs to as we go.
The 5 steps are: (1) decide what you want to find out, (2) check if the answer already exists somewhere, (3) plan how you'll collect new data, (4) actually collect that new data, and (5) study the data and report what you found.
This is just the cover slide: "Chapter 2 — The Consumer Research Process." It tells you the whole chapter is about the steps companies follow when they want to learn something about their customers, like what they like, why they buy certain things, or how they feel about a product.
This page introduces the two big "families" of research methods you'll see throughout the chapter.
Qualitative research (Interpretivism) means talking to people in depth to understand their feelings, habits, or experiences. It explores new ideas rather than testing fixed ones. The catch is that since you only talk to a small number of people, you cannot say "this is true for everyone" — the results cannot be generalized to a bigger population. "Interpretivism" simply means: human feelings and experiences are complicated, so you need to listen and interpret meaning, not just count numbers.
Quantitative research (Positivism) means collecting numbers from a large group of people so you can predict how customers in general will react — for example, how they'll respond to an ad, a discount, or a new package design. It's called descriptive/empirical because it's based on actual measured data, not opinions. Since you ask many people, the results CAN be generalized to the larger population. "Positivism" means: you believe you can measure things about people scientifically, almost like measuring temperature with a thermometer.
A simple example to compare them: if a tea company asks 1,000 people "Rate our new tea flavor from 1–5" and finds 70% gave it a 4 or 5, that's quantitative — a number you can apply to all tea drinkers. If instead they sit down with 8 people and have a long conversation about their childhood memories of drinking tea with family, that's qualitative — rich and personal, but you can't say all tea drinkers feel exactly this way.
This is the very first step, and the slide calls it the hardest one. A "research objective" is simply a clear, written statement of exactly what you want to find out. If this is vague, the whole research project becomes a waste of time and money.
For example, a bad research objective is "Let's find out what people think about juice" — too broad, no clear direction. A good research objective is "Do people aged 18–25 prefer mango juice over orange juice, and how much are they willing to pay for it?" Writing the objective down clearly keeps everyone focused and avoids spending money chasing the wrong questions later.
Secondary data is information that already exists — it was collected by someone else, for some other purpose, but you can still use it to help your current research. It can come from:
Example: before a tea company spends money on a brand-new survey, they might first check government reports on national tea consumption (external) and look at their own sales numbers from the last five years (internal). This is usually cheaper and faster than collecting brand-new data, so it's done early to avoid wasting money.
Step 3 is about planning how you'll collect brand-new data — called primary data because it's collected directly, for this specific research, unlike secondary data which already existed.
Page 5 — Qualitative Research Design. This page lists four qualitative methods, which are explained one by one in the next few pages: depth interviews, focus groups, projective techniques, and metaphor analysis. Metaphor analysis means asking people to express feelings using sounds, music, drawings, or pictures instead of words — useful when feelings are hard to put into plain language. For example, asking someone to pick a piece of music that matches "how using this brand of phone makes you feel."