Welcome to Marketing Research!
Hey there! Ever wondered how companies like Nike decide on the colour of their next sneaker, or how your favourite bubble tea shop comes up with a new flavour? They don't just guess! They use a secret weapon called Marketing Research.
In this chapter, we're going to be business detectives. You'll learn how companies gather clues (data) about their customers, competitors, and the market. This is a super important skill because good research leads to smart decisions, and smart decisions lead to successful businesses. Let's dive in!
Part 1: What is Marketing Research and Why Bother?
What is Marketing Research?
Think of Marketing Research as the process of gathering, analysing, and interpreting information about a market. It's like a business's eyes and ears, helping it understand what's happening in the world outside its own office.
Analogy: Imagine you want to cook dinner for your friends. You wouldn't just cook what you like, right? You'd probably ask them what they like to eat, if they have any allergies, or what they're in the mood for. That's a simple form of marketing research! You're collecting information to make a better decision (and a better dinner!).
The Importance and Major Objectives
So, why do businesses spend time and money on research? Because making decisions without information is just guessing, and guessing is risky! Research helps businesses to:
- Reduce risk when launching new products.
- Spot new opportunities and trends (like the growing demand for plant-based food).
- Understand their customers better.
- Keep an eye on their competitors.
The major objectives of marketing research are to find answers to important questions, such as:
1. Who are our customers? (e.g., Are they teenagers? Office workers?)
2. What do they want? (e.g., Do they prefer quality or low price?)
3. Will they buy our new product? (e.g., Testing a new spicy chicken burger idea before launching it.)
4. How effective is our advertising? (e.g., Did people see our latest YouTube ad and did it make them want to buy?)
Key Takeaway for Part 1
Marketing research is the systematic collection and analysis of data to help businesses make informed decisions. Its main goal is to understand the market and customers to reduce risk and find opportunities.
Part 2: Designing Your Research - The Detective's Toolkit
Now that we know the 'what' and 'why', let's learn the 'how'. Designing a research project involves two key decisions: how to collect the data, and who to collect it from.
Step 1: Collecting the Clues (Data Collection Methods)
First, we need to understand that there are two main types of data a business can collect. Don't worry, it's a simple idea!
Primary Data: Freshly Gathered Information
Primary data is brand new information that you collect yourself, for your specific research purpose. It's fresh and tailored to your exact needs.
Analogy: Primary data is like cooking a meal from scratch with fresh ingredients you just bought from the market.
Common methods to collect primary data include:
- Surveys (Questionnaires): Asking a set of questions to a group of people. This can be done online (Google Forms), on the street, or by phone. Example: A bus company uses a survey to ask passengers about the cleanliness of its buses.
- Interviews: Having a more in-depth, one-on-one conversation to get detailed insights. Example: A skincare brand interviews five regular customers to deeply understand their morning routines.
- Observation: Watching how people behave in a natural setting, without asking them questions. Example: The manager of a 7-Eleven watches which snacks customers pick up most frequently from the shelves near the cashier.
Secondary Data: Using Existing Information
Secondary data is information that already exists because someone else collected it for a different purpose. It's often quicker and cheaper to get.
Analogy: Secondary data is like using a recipe from a cookbook. Someone else has already done the work of creating and testing it.
Common sources of secondary data include:
- Internal Sources (from inside the company): Past sales figures, customer complaint records, and other company reports. Example: A restaurant looks at its sales records to see which dishes were least popular last year.
- External Sources (from outside the company): Government statistics (like the census), industry reports, university research, and news articles. Example: A new toy shop owner reads a government report on the birth rate in Hong Kong to estimate the size of their market.
Quick Review: Primary vs. Secondary Data
Primary Data:
What is it? New data collected by you.
Pros: Specific to your needs, up-to-date.
Cons: Can be slow and expensive to collect.
Secondary Data:
What is it? Existing data collected by others.
Pros: Fast and cheap to obtain.
Cons: May not be specific enough, could be outdated.
Step 2: Who to Ask? (Sampling Techniques)
It's usually impossible to survey everyone in your target market (this entire group is called the population). Imagine trying to ask every teenager in Hong Kong about their favourite video game! Instead, researchers select a smaller group, called a sample, to represent the whole population.
Analogy: You don't need to drink the whole pot of soup to know if it's salty. You just taste a spoonful (the sample) to judge the whole pot (the population). The key is to get a good, representative spoonful!
Here are three basic ways to choose your sample, as required by the DSE syllabus.
Random Sampling
This is the gold standard for being fair and unbiased. In random sampling, every single person in the population has an equal chance of being selected.
- How it works: Think of it like a lucky draw. You could put everyone's name in a hat and draw them out, or use a computer to generate a list of random student ID numbers to survey.
- When to use it: When you need a highly accurate, unbiased representation of the population and you have a complete list of everyone in it.
Convenience Sampling
This is the easiest and fastest method. In convenience sampling, you select respondents who are simply easy to access.
- How it works: Asking your classmates, interviewing the first 50 people who walk out of an MTR exit, or posting a survey link on your social media feed.
- When to use it: When you need quick, cheap results and are less concerned about them being perfectly representative of the entire population. It's great for initial ideas but can be very biased.
- Common Mistake Alert! Do not confuse random sampling with convenience sampling. Just picking people "randomly" on the street is NOT random sampling, because not everyone in the population had an equal chance to be on that street at that time. It's convenience sampling!
Stratified Random Sampling
Don't worry if this sounds tricky at first! It's a smart way to make sure your sample is balanced. With stratified random sampling, you first divide the population into different sub-groups (called 'strata'), and then you perform random sampling within each group.
- How it works (step-by-step):
1. Divide (Stratify): A university wants to survey students about online learning. They know male and female students might have different opinions. The population is 60% female and 40% male. So, they divide all students into two strata: 'female' and 'male'.
2. Randomly Sample: They want a final sample of 100 students. To make it representative, they randomly select 60 female students from the 'female' group and 40 male students from the 'male' group.
- When to use it: When the population has important and distinct sub-groups and you want to ensure each group is properly represented in your sample.
Did you know?
Political polls that predict election results often use stratified random sampling. They divide the population by age, gender, and location to make sure their sample accurately reflects the diversity of the voters!
Key Takeaway for Part 2
Designing research involves choosing data collection methods (fresh primary data or existing secondary data) and sampling techniques. The three key sampling methods are Random Sampling (everyone has an equal chance), Convenience Sampling (choose who is easy to reach), and Stratified Random Sampling (divide into groups, then sample randomly from each group).
You've Got This! A Final Summary
Great job! You now understand the fundamentals of marketing research. You've learned that it's a crucial tool for businesses to make smart, data-driven decisions. We've covered:
- The importance and objectives of research – to reduce risk and understand customers.
- The two main types of data: primary (new) and secondary (existing).
- The basic principles of sampling and three key techniques: random, convenience, and stratified random.
Keep these concepts in mind, and you'll start seeing marketing research everywhere you go. You're well on your way to thinking like a true business strategist!