How to Do Market Research for a Business – These days, a lot of people are looking at doing startups. If you have a good idea, you have a good chance being catapulted to fame and wealth. But, you have to start by doing your homework, and that includes doing market research on the particular industry that you want to go into. In this case study, we learn about how to do market research for startups, as well as how to do market research for businesses .
If your startup is to succeed, you need to determine whether or not there is a demand for what you’re selling. And, if you need help with that, take a look at this case study on how you can do market research for startups .
Table of Contents
1: Problem Definition
Define the problem and research objectives. The first step in any marketing research study is to define the problem, while taking into account the purpose of the study, the relevant background information, what information is needed, and how it will be used in decision making. This stage involves discussion with the decision makers, interviews with industry experts, analysis of secondary data, and, perhaps, some qualitative research, such as focus groups. There are three types of objectives that can be deployed in marketing research:
1. Exploratory research
- Used to better define a problem or scout opportunities.
- In-depth interviews and discussions groups are commonly used.
2. Descriptive research
- Used to assess a situation in the marketplace (i.e., potential for a specific product or consumer attitudes).
- Methods include personal interviews and surveys.
3. Causal research
- Used for testing cause and effect relationships.
- Typically through estimation.
2: Developing a research program: method of inquiry
The scientific method is the standard for investigation. It provides an opportunity for you to use existing knowledge as a starting point, and proceed impartially.
The scientific method includes the following steps:
- Define a problem
- Develop a hypothesis
- Make predictions based on the hypothesis
- Devise a test of the hypothesis
- Conduct the test
- Analyze the results
This terminology is similar to the stages in the research process. However, there are subtle differences in the way the steps are performed:
- the scientific research method is objective and fact-based, using quantitative research and impartial analysis
- the marketing research process can be subjective, using opinion and qualitative research, as well as personal judgment as you collect and analyze data
3: Statement of Research Objectives
After identifying and defining the problem with or without explanatory research, the researcher must take a formal statement of research objectives. Such objectives may be stated in qualitative or quantitative terms and expressed as research questions, statement or hypothesis. For example, the research objective, “To find out the extent to which sales promotion schemes affected the sales volume” is a research objective expressed as a statement.
On the other hand, a hypothesis is a statement that can be refuted or supported by empirical finding. The same research objective could be stated as, “To test the proposition that sales are positively affected by the sales promotion schemes undertaken this winter.”
Example of another hypothesis may be: “The new packaging pattern has resulted in increase in sales and profits.” Once the objectives or the hypotheses are developed, the researcher is ready to choose the research design.
4: Choose your sample
Your marketing research project will rarely examine an entire population. It’s more practical to use a sample – a smaller but accurate representation of the greater population. To design your sample, you’ll need to answer these questions:
- Which base population is the sample to be selected from? Once you’ve established who your relevant population is (your research design process will have revealed this), you have a base for your sample. This will allow you to make inferences about a larger population.
- What is the method (process) for sample selection? There are two methods of selecting a sample from a population:
1. Probability sampling: This relies on a random sampling of everyone within the larger population.
2. Non-probability sampling: This is based in part on the investigator’s judgment, and often uses convenience samples, or by other sampling methods that do not rely on probability.
- What is your sample size? This important step involves cost and accuracy decisions. Larger samples generally reduce sampling error and increase accuracy, but also increase costs. Find out your perfect sample size with our calculator.
5: Data Collection
This step revolved around obtaining the information that you will need to solve the issue or problem identified. Data collection involves a field force or staff that operates either in the field, as in the case of personal interviewing (in-home, mall intercept, or computer-assisted personal interviewing), from an office by telephone (telephone or computer-assisted telephone interviewing), or through the mail (traditional mail and mail panel surveys with recruited households).
6: Data Preparation and Analysis
Analysis of data is a process of inspecting, cleaning, transforming, and modeling data with the goal of highlighting useful information, suggesting conclusions, and supporting decision making. Data analysis has multiple facets and approaches, encompassing diverse techniques under a variety of names in different business, science, and social science domains. Data mining is a particular data analysis technique that focuses on modeling and knowledge discovery for predictive rather than purely descriptive purposes. Marketers use databases to extract applicable information that identifies customer patterns, characteristics and behaviors.
Business intelligence covers data analysis that relies heavily on aggregation and focusing on business information. In statistical applications, some people divide data analysis into descriptive statistics, exploratory data analysis (EDA), and confirmatory data analysis (CDA). EDA focuses on discovering new features in the data and CDA focuses on confirming or falsifying existing hypotheses. Predictive analytics focuses on application of statistical or structural models for predictive forecasting or classification. Text analytics applies statistical, linguistic, and structural techniques to extract and classify information from textual sources, a species of unstructured data. All are varieties of data analysis.
During this phase of the research process, data is carefully edited, coded, transcribed, and verified in order for it to be properly analyzed. Statistical market research tools are used. The validity of the results is also assessed to confirm how well the data measures what it is supposed to measure. Oftentimes, the research team will arrange a debriefing session with the client to review highlights from the data and brainstorm potential ideas on how the findings can be implemented. This typically happens when a client hires a market research company and they want to remain thoroughly involved in the research process.
Helpful tips to keep in mind during data analysis:
- Communicate the results.
- Try to avoid bias when interpreting data.
- Just because results fail to confirm original hypotheses, does not mean the research results are useless.
7: Formulating Conclusion, Preparing and Presenting the Report
The final stage in the marketing research process is that of interpreting the information and drawing conclusion for use in managerial decision. The research report should clearly and effectively communicate the research findings and need not include complicated statement about the technical aspect of the study and research methods.
Often the management is not interested in details of research design and statistical analysis, but instead, in the concrete findings of the research. If need be, the researcher may bring out his appropriate recommendations or suggestions in the matter. Researchers must make the presentation technically accurate, understandable and useful.
Conclusion
Everyone has a startup idea in them . You may have a great idea to solve a problem you experience, or you might want to disrupt the current market to make it better for everyone. But before you commit your time, energy, and resources into your idea, take the time to do your homework. After all, there’s no point in jumping into something and failing if it doesn’t do well.