MKTG90011 · Marketing Research
Secondary and Qualitative Research
Before you spend a cent collecting your own data, exhaust what already exists. Secondary data was collected earlier for a different purpose (sales/CRM records, ABS census, IBISWorld, Euromonitor); primary data you collect now for this question. Secondary sources are cheap and fast, frame the problem, and — crucially — supply validated scale measures from the literature, but they may be dated or a poor fit. The literature review tells you what is already known and lets you build a conceptual model: name the dependent variable, the independent variables, and write directional hypotheses linking them. When the problem is still fuzzy, qualitative / exploratory research — in-depth interviews, focus groups, observation, projective techniques — gets the why before you measure the how much. It is inductive (data builds theory), surfaces respondents' own language, and generates the hypotheses that later quantitative work confirms.
What this chapter covers
- 012.1 Primary vs secondary data — the cost/speed/recency/fit trade-off
- 02Internal vs external vs syndicated sources
- 032.2 The literature review → locating validated scale measures
- 04Conceptual model: DV, IV(s) and directional hypotheses
- 053.1 Qualitative / exploratory research — purpose and logic (inductive)
- 06In-depth interviews vs focus groups vs observation / ethnography
- 07Thematic analysis: transcribe → code → themes
Worked example: build a conceptual model and a hypothesis
- +1(a) Name the variables. The DV (what you explain) is subjective wellbeing; the IV (what you explain it with) is perceived social support.
- +1(b) Write a directional hypothesis. H₁: Higher perceived social support is associated with higher subjective wellbeing — note the direction (+), not just “they are related”.
- +1Ground the constructs. A literature review supplies validated multi-item scales for both constructs, so you measure them properly rather than inventing items.
- +1(c) Sequence the work. If the constructs are well established, lead with secondary work (literature) to borrow scales; if the construct or its drivers are unclear, run qualitative work first to surface them, then test quantitatively.
Key terms
- Secondary data
- Data collected earlier for a different purpose — internal (sales, CRM), external (ABS, IBISWorld) or syndicated (Roy Morgan, Euromonitor). Cheap and fast, but possibly dated, an imperfect fit, and not under your control.
- Primary data
- Data you collect now, specifically for this research question — your survey, interviews or experiment. Tailored, current and exclusive, but expensive and slow.
- Conceptual model
- A diagram naming the dependent variable, the independent variables, and the hypothesised links between them — the engine room of the project, built from the literature review.
- Directional hypothesis
- A testable statement that specifies the sign of a relationship (e.g. “higher X is associated with higher Y”), not merely that two variables are related. It is what later statistical tests confirm or reject.
- Thematic analysis
- The standard way to make sense of qualitative data: transcribe the interviews/focus groups, code the text into recurring labels, then group codes into themes that answer the research question.
Secondary and Qualitative Research FAQ
Why use secondary data before collecting my own?
Because it is cheaper, faster, frames the problem and — most usefully — supplies validated scale measures from the literature, telling you what is already known before you build a survey. The trade-off is fit and recency: it was collected for someone else's purpose, so it may be dated or not quite match your question.
When do I use qualitative research rather than a survey?
When the problem is still fuzzy. Qualitative / exploratory work (interviews, focus groups, observation) clarifies why things happen, surfaces the constructs and respondents' own language, and generates hypotheses. It is inductive and hypothesis-generating; surveys come later to confirm at scale.
What is the difference between a focus group and an in-depth interview?
An in-depth interview probes one respondent in detail — best for sensitive topics or expert depth. A focus group runs a small moderated group (typically 6–10) so members spark ideas off each other — best for surfacing a range of views and group dynamics. The moderator's job is to keep discussion on-brief without leading it.
How do qualitative and quantitative research fit together?
Sequentially: qualitative is inductive and exploratory (build understanding, generate hypotheses); quantitative is deductive and confirmatory (test those hypotheses on a large sample). In the project you run qualitative work first to shape the survey, then quantitative tests on the survey data.
Exam move
Keep two grids straight for the exam: primary vs secondary (along cost, speed, fit and recency) and qualitative vs quantitative (inductive/exploratory vs deductive/confirmatory). Practise writing a clean directional hypothesis from a conceptual model — name the DV, the IV, and the sign — because short-answer items ask exactly that, and the same move opens your project. Learn which qualitative method fits which goal (depth interview vs focus group vs observation) and the thematic-analysis sequence; these are conceptual marks you can bank without any calculation.
