IB Business Management SLTopic 4 — Market ResearchPaper 1 & 2Core skill~8 min read
Choosing a Sample
No business can ask everybody. So it asks a few hundred people and treats their answers as if they speak for thousands. That leap is called sampling, and it works beautifully — right up until the few hundred people are the wrong few hundred.
📚 What you need to know
Sampling means getting opinions from a selected group of people in order to draw conclusions about the market as a whole.
The population in research is the group the business is interested in — not the population of a country.
In general, the larger the sample, the more likely the results reflect the whole market.
Quota sampling sets proportions for each group in advance.
Random sampling gives every member of the population an equal chance of selection.
Convenience sampling uses whoever is easiest to reach and willing to take part.
The method chosen depends on time, knowledge of the population and the skills of the researchers.
Why sample at all?
Asking every customer would be perfectly accurate and completely impractical. It is expensive and time-consuming to collect data from a whole market, so researchers design a sample instead: a smaller group chosen carefully enough that its answers can be extrapolated to everyone else.
That word matters. Extrapolating means taking what a few hundred people said and assuming it is true for the rest. If the sample is well chosen, the assumption is reasonable. If it is not, the business makes a big decision on the strength of the wrong people’s opinions.
Everything on this page is about that first arrow: how the five dots get chosen, and how much you can trust them afterwards.
Population does not mean a country. A research population is only the group the business has an interest in. For a university open day it might be sixteen to eighteen year olds within two hours’ travel — a few thousand people, not sixty million.
The three methods you need
Quota sampling
The researcher decides in advance what proportion of the sample should come from each group, then fills those quotas. The aim is a sample whose make-up mirrors the real population.
Quota sampling is fast because the researcher can stop as soon as each box is ticked — but who goes into each box is still the researcher’s choice, which is where bias creeps in.
Random sampling
Every member of the population has an equal chance of being selected, usually by picking names at random from a complete list. A gym drawing 150 members at random from its membership database is doing exactly this.
Random removes the researcher’s own bias completely, because nobody chooses who is picked. But “random” and “representative” are not the same thing — a random draw can easily produce 150 people who all joined in the last month.
Convenience sampling
The researcher uses whoever is easiest to reach and willing to take part: shoppers in the queue, regular customers during a quiet hour, followers on the firm’s own social media. It is quick and nearly free, and it is the weakest of the three, because the people who are easy to reach are rarely typical.
Method
Advantages
Disadvantages
Quota sampling
Quick and easy to obtain, and the sample structure matches the population on paper
Not random, so there is a real risk of bias in who is chosen for each quota
Quota sampling
Useful when the firm knows its market well
The firm must already understand the population in order to set the proportions
Random sampling
Simple to design and interpret, and free from researcher bias
The sample selected may still not be representative of the market
Random sampling
Anyone in the population can be asked, so the process is fair
A complete and accurate list of the population is needed, which many firms do not have
Convenience sampling
Respondents are readily available, so it is fast and cheap
Heavily biased if the people asked are already known to the researcher
Convenience sampling
Large amounts of information can be gathered quickly
Unlikely to represent the market as a whole, so conclusions are shaky
Notice that every method has the same core weakness in different clothing: the sample might not look like the market. Quota risks it through the researcher’s choices, random risks it through luck, convenience risks it through who happens to be standing there.
Choosing between them
There is no best method, only a best method for this firm, this budget and this deadline. Three factors decide it:
🧩 How to pick a sampling method in an exam answer
Time available. If the firm has very little time, a random sample is usually quickest to organise, because no groups have to be defined first.
Knowledge of the target population. If the firm knows its customers well, a quota sample gives structured data that lacks obvious bias and can be read with insight.
Skills of the researchers. If the people running the research lack experience, a convenience sample is at least simple to run and easy to interpret — accepting that the data is weaker.
Then judge it. Say what the chosen method will not tell the firm, and what it should do to check the result.
WORKED EXAMPLE
A city bus company wants to know whether passengers would pay more for a faster express route. It has three weeks and no list of its passengers. Recommend a sampling method. [6 marks]
Step 1: rule out what cannot workRandom sampling needs a complete list of the population. The company has no passenger database, so it cannot give everyone an equal chance of selection.Step 2: choose between the remaining twoConvenience sampling at one bus stop would be fastest, but it would mostly catch people who already use that route at that time of day.Step 3: recommend and justifyQuota sampling at several stopsThe company knows roughly how its passengers split between commuters, students and off-peak travellers, so it can set quotas for each and survey across different stops and times. Three weeks is enough to fill them.Step 4: judge the weaknessInterviewers still choose who to approach inside each quota, which can bias the result — people in a hurry get skipped, and they are exactly the ones most likely to pay for a faster route.
💡 Exam tip
Define the population first in your answer. It shows you understand that research targets a specific group, not everyone.
Use the constraints in the stimulus. No customer list rules out random; no time rules out big quota studies. Ruling methods out is a strong way to justify a choice.
Mention sample size. Larger samples are more likely to reflect the market, but they cost more — that trade-off is worth a mark.
Name the bias your chosen method carries. Every method has one, and spotting it is the evaluation.
Do not confuse the sampling method with the research method. A survey is how you ask; quota is who you ask.
⚠️ Common mix-up
Assuming population means the country’s population. It is only the group the firm is interested in.
Thinking random means casual. Random sampling is a strict process needing a full list, not just stopping people in the street — that is convenience sampling.
Believing a bigger sample fixes bias. Asking two thousand of the wrong people is still the wrong answer, just more expensive.
Saying quota sampling removes bias. It controls the proportions; the researcher still chooses individuals.
Confusing sampling with the method of research. Sampling decides who; surveys, interviews and focus groups decide how.
Forgetting response rates. Poor response is common with random samples, which quietly reintroduces bias.
Up next: Product and the Product Life Cycle — the first of the seven Ps, and the model that explains why a product’s marketing has to change as it ages.
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