QUESTION 1 Company sales invoices, census data, and trade association statistics are examples of: Primary data Imaginary data mines Secondary data Tertiary data Exploratory data QUESTION 2 The first step in the market research process is: Analyzing the internal company database Problem recognition Determining the appropriate research design Internal analysis Reporting and limitations of the study QUESTION 3 A major advantage of primary data collection is that it can be tailored to fit the pertinent research questions.


Company sales invoices, census data, and trade association statistics are examples of secondary data. Secondary data refers to information that is collected and compiled by others for purposes other than the current research study. It is data that has been previously gathered and is readily available for analysis. Secondary data can be obtained from various sources such as government agencies, research organizations, and commercial databases. It is a valuable resource for researchers as it can provide valuable insights and information without the need for data collection from scratch. Examples of secondary data include historical sales data, demographic information, and industry reports.

In contrast, primary data refers to data that is collected specifically for the current research study. It is original data that is obtained directly from the source, through methods such as surveys, interviews, observations, or experiments. Primary data collection allows researchers to gather data that is specifically tailored to their research questions and objectives. This data is generally more focused and specific to the research study at hand, allowing for greater control over the quality and reliability of the data.

Tertiary data, on the other hand, refers to data that has been compiled and summarized from primary and secondary sources. It is data that has undergone further analysis and interpretation to provide a broader perspective or overview of a particular subject or issue. Tertiary data can be in the form of reports, literature reviews, meta-analyses, or aggregated data sets. It provides a higher-level synthesis of existing data and can be used to support or contextualize primary and secondary data.

Imaginary data mines, as the name implies, are not real data sources and do not exist in reality. Therefore, they are not a valid example of data sources in the context of market research.


The first step in the market research process is problem recognition. Problem recognition involves identifying a need or issue that requires investigation and understanding. It is the stage where a company or researcher recognizes that there is a gap in knowledge, a problem to be solved, or an opportunity to be explored.

In order to conduct effective market research, it is important to first identify the specific problem or objective that the research aims to address. This involves clearly defining the research question or hypothesis, and understanding the context and scope of the problem. This initial step allows the researcher to establish the purpose and direction of the research, and lays the foundation for the subsequent stages of the research process.

Problem recognition is often driven by various factors such as changing market conditions, competitive pressures, customer feedback, internal performance indicators, or emerging trends in the industry. It requires a systematic and thorough analysis of the business environment, including an examination of internal and external data, discussions with key stakeholders, and a review of existing knowledge and literature.

By recognizing the underlying problem or need, the researcher can then proceed to determine the appropriate research design. This involves making decisions about the research approach, methodology, sampling strategy, data collection methods, and data analysis techniques. The research design should be aligned with the research objectives and provide a clear roadmap for conducting the study.

It is important to note that problem recognition is not a one-time event, but an ongoing process. As new information and insights are gained throughout the research process, the problem may evolve or become more refined. Therefore, it is important for researchers to continuously review and reassess the problem to ensure that the research remains relevant and meaningful.


A major advantage of primary data collection is that it can be tailored to fit the pertinent research questions. Primary data collection involves gathering data directly from the source, through methods such as surveys, interviews, observations, or experiments. This allows researchers to design the data collection process to specifically address their research objectives and requirements.

By collecting primary data, researchers have greater control over the type and quality of data collected. They can determine what specific information is needed, how it should be collected, and what data collection methods are most appropriate. This enables researchers to gather data that is highly relevant to their research questions and provides detailed insights into the phenomenon under study.

Tailoring primary data collection to fit the research questions also allows for greater flexibility and customization. Researchers can design survey questionnaires or interview guides that specifically target the variables and concepts they are interested in. They can also adapt their data collection methods as needed throughout the research process, based on emerging findings or changing research requirements. This flexibility ensures that the data collected is focused, accurate, and comprehensive.

Furthermore, primary data collection offers researchers the opportunity to directly engage with participants and gather data in real-time. This allows for richer and more nuanced data, as the researcher can ask follow-up questions, probe for deeper insights, or clarify any ambiguities. It also enables researchers to establish a rapport with participants, which can enhance data quality and encourage greater participation and cooperation.

However, it is important to acknowledge that primary data collection typically requires more time, effort, and resources compared to secondary data analysis. Primary data collection involves various logistical considerations such as sample selection, data collection instruments, data management, and data analysis. It can also be influenced by various factors such as respondent bias, researcher bias, or ethical considerations. Therefore, researchers need to carefully plan and execute primary data collection to ensure reliable and valid results.