The big idea: Primary or secondary is about WHO collected the data. Qualitative or quantitative is about WHAT KIND of data it is.
They are separate questions, so they make a grid. Primary research can be either kind, and so can secondary.
Two axes, four cells, and a real example in each. Step through to see why the two questions cannot be collapsed into one.
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The statement calls research an ongoing activity throughout the process. It is not a chapter at the start of a folder — it is what you do every time a decision cannot be made from what you already know.
| Stage | What you research there | Type |
|---|---|---|
| Empathize | Who the users are, what really happens on the ward, what already exists | Primary observation and interviews; secondary standards and statistics |
| Define the project | Anthropometric reach data, hygiene regulations, comparable products | Mostly secondary, to set numbers you cannot measure yourself |
| Ideation | How other industries solve the same problem; what materials allow | Secondary, plus product analysis of unrelated products |
| Designing a solution | Whether the model meets each criterion, with real users | Primary, and increasingly quantitative |
| Presenting | The measurements that prove each criterion was met | Primary and quantitative |
The order that saves time: Secondary first, primary second.
Find out what is already known — it is fast and free — then spend your limited hours of primary research on the questions nobody has answered for your users and your context.
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Qualitative — the why
- Reasons, feelings, priorities, and the words users use
- Explains a behaviour you have already seen
- Finds problems you had not thought to ask about
- But: cannot tell you how COMMON any of it is
Quantitative — the how many
- Times, counts, dimensions, forces, percentages
- Shows how widespread a problem is
- Lets you prove an improvement by measuring twice
- But: never explains itself
A number plus a reason: "Nine of the twelve patients could not reach the water jug, and every one of them said they would not press the call button for a drink."
The number makes it matter. The reason tells you what to change. Either half alone is a weaker finding.
What secondary data cannot do: It was collected to answer somebody else's question, about a population that is probably not yours.
Use it to set context, to find numbers you cannot measure, and to check whether what you found is normal — never as a substitute for talking to your own users.
The limits of qualitative data
Subjective
It is built on personal opinions and feelings, so it is less reliable and another team may not get the same result.
Small samples
Interviews and focus groups reach only a few people, so the findings are hard to generalise to the whole target market.
Slow and costly
Setting up and running sessions with many stakeholders takes time and money, which limits how many can be held.
Hard to compare
Answers in words cannot be averaged or graphed directly: they must be coded first, and the coding is itself a judgement.
How this is tested — distinguishing primary from secondary and qualitative from quantitative, and saying what each is for. It comes up two ways:
Paper 1 — multiple choice
- Classify a named source as primary or secondary.
- Identify which type of data a stated finding is.
Paper 2 — analysing a product
- Explain what primary and secondary research each contribute to a named product.
- Justify collecting quantitative as well as qualitative data.
The trap: Treating primary as a synonym for qualitative. A stopwatch and a tally chart are primary AND quantitative, and a published case study is secondary AND qualitative.
A team redesigning a hospital bedside table uses both primary and secondary research. Explain what each contributes, giving an example of qualitative and of quantitative data from each.
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