Market Research flashcards

Market Research

• Market research involves collecting, recording, and analyzing data about customers, competitors, and the market to inform business decisions.

• It helps in understanding customer characteristics, purchasing habits, and motivations.

Uses of Market Research:

• Measuring customer reactions to:

  • New products

  • Different price levels

  • Alternative forms of promotion

  • New types of packaging

  • Online distribution

Purposes of Market Research:

• Identify Main Features of the Market:

  • Overall size: Determine if the market is worth entering.

  • Growth: Assess if the market is expanding or shrinking.

  • Competitors: Analyze the number and strength of competitors.

• Reduce Risks of New Product Launches:

  • Research potential demand to assess the likelihood of success.

  • Testing the likely sales success of proposed new products is the most important purpose of market research.

  • Although no research can be 100% accurate, it significantly improves the chances of success.

*New Product Development (NPD) Support:

*   **Identify Consumer Needs and Tastes**: Primary and secondary research.
*   **Product Idea and Packaging Design**: Testing with consumer groups.
*   **Brand Positioning and Testing of Advertising**: Pre-testing product image and ads.
*   **Product Launch and After-Launch Period**: Monitoring sales and consumer response.

• Identify Consumer Characteristics:

  • Establish consumer profiles, including wants and needs.

  • Target products to appropriate market sectors based on age, income, and social class.

• Explain Patterns in Sales of Existing Products and Market Trends:

  • Analyze sales declines or increases using market research data.

  • Example: Gap used market research to analyze a 4% sales decline in 2019 despite global coding sales increasing, and used the data to try and reverse the sales trend.

• Predict Future Demand Changes:

  • Forecast changes in demand levels for existing products.

  • Example: Travel firms investigate social and income changes to predict future holiday demand.

• Assess Popular Designs, Promotions, Styles, and Packaging:

  • Consumer testing of products and promotions.

  • Consumer-test different versions of products or advertisements before final decisions.

  • Incorporate consumer responses into the final product.

• Market research is important for developing a new marketing strategy for an existing business.

• New enterprises should also undertake market research as the data collected will form an important part of the business plan.

Primary vs. Secondary Research

• Primary Research: First-hand data collection directly related to the business's needs.

• Secondary Research: Use of existing data originally collected for another purpose.

• Businesses often start with secondary research due to lower cost and quicker availability.

• Secondary research assesses main market features. If the market appears too small or competitive, primary research might be skipped.

• Positive secondary research results lead to a detailed primary data collection program.

Usefulness of Secondary Research Data

• Provides information about:

  • Population

  • Economy

  • Market conditions

  • Major trends

• Helps identify key areas for primary research.

• Acts as a baseline to compare primary research data.

• Often uses large samples, increasing accuracy and reliability.

• Many sources are available online.

• A good option when time and finances are limited.

• The vast amounts of publicly available data online on websites, social media posts, retail purchase records and healthcare records are also called big data.

• Multiple sources allow cross-checking for accuracy.

Main Sources of Secondary Data

• Government: Population censuses, vehicle registrations, social trends, family expenditure patterns.

• Local Government: Number of local households, occupations, ethnic origins.

• Trade Organizations: Industry-specific publications (e.g., hotel and car retailing).

• Market Research Agencies: Mintel, Euromonitor; provide detailed market intelligence reports.

• Internal Company Records: Customer sales records, feedback, daily sales figures.

• Company Reports and Accounts: Competitors' end-of-year accounts.

Limitations of Secondary Research Data

• Data may be outdated.

• Data may not be specific to the business's needs.

• Access may be restricted or expensive.

• Primary research is still needed for specific consumer profiles and preferences.

• Big data analysis can be costly.

Usefulness of Primary Research Data

• Useful for:

  • Completely new markets with no secondary data.

  • Collecting data for specific business purposes.

  • Gathering qualitative data to support quantitative data.

  • Focusing on market reactions to business changes (e.g., lower prices, increased advertising).

  • Gaining information from a specific target group.

  • Rapidly changing markets where up-to-date data is essential.

  • Cross-checking data for accuracy.

Primary Data Collection Methods

• Questionnaire: Postal, in-store, online, mobile.

• Questionnaires can include detailed, open questions which give qualitative and quantitative data.

• Interview: Face-to-face, mobile.

• Interviews allow personal contact with respondents. Follow-up questions can be asked.

• Observation: Observing consumer behavior in-store.

• If people know they are being observed, they could behave differently.

• Test Marketing: Specific geographical area.

• The results might indicate whether the national launch of a new product will achieve sales targets.

• Focus Groups: Discussions with potential or existing consumers.

• Focus groups encourage debate between consumers about a product or advertisement. Discussion is observed and recorded.

Key Terms

• Qualitative Data: Non-numerical data providing insight into consumer motivations and opinions.

• Quantitative Data: Numerical results from research that can be statistically analyzed.

Limitations of Primary Research

• Sample selection influences data accuracy.

• Start-ups may lack finances for detailed research.

• New businesses have no customers yet to gain important data from.

• Data collection and analysis can be time-consuming.

Market Research Developments

• Businesses increasingly use electronic means for data collection.

• Retailers use loyalty card schemes to gather data on consumer purchases, age, gender and possibly their income.

• Social media platforms are transforming market research, using software to understand thoughts, ideas, and emotions from videos, images, text, and sound.

• Online marketing allows firms to conduct research projects for just a few thousand dollars, taking advantage of pre-prepared questionnaires, with the results coming in within a few days.

• Mobile surveys can use pre-recorded messages and questions to which people respond by using numbers on the keypad or speaking the answers. These results are then automatically presented and analyzed electronically.

• Global spending on market research increased by over 5% to US82 billion in 2019.

Sampling

• Sampling involves selecting a group of respondents from a larger population.

The Need for Sampling

• It is often impossible to collect evidence from the total population because that market is so extensive that contacting everyone in it would be too expensive or time-consuming, or because it is impossible to identify everyone in that market.

• The larger the sample, the more representative of the total population it is likely to be. Greater confidence can then be placed in the final results.

Limitations of Sampling

• Sample Size: Small samples may not represent the target population.

• A sample of 10 people is unlikely to be sufficient.

• A sample of 1000 will give more accurate results than one of 100, especially if the questions are being focused on particular age or income groups. Once a sample of 100 has been broken down into, say, ten different age groups, then there will only be ten respondents from each age group. This could be too few.

• Cost and time are the two major constraints.

• Sampling Bias: Results from a sample may be different from those that would have been obtained if the whole target population had been questioned. This is called sampling bias.

• Statisticians often aim to achieve a 95% confidence level in their results, which means that the results can be relied upon in 19 cases out of 20. Generally, the larger the sample size, the greater the chance that this 95% confidence level will be met.

Market Research Data

• Once research has been completed, it needs to be analysed in ways that make it useful to business decision makers.

Reliability of Data Collected

• Primary and secondary data can be unreliable and a poor basis for decisions.

• Secondary data can be unreliable for reasons already referenced - it may be out of date, not specific to the needs of the business, incomplete or variable

• Researchers may not use the most appropriate methods of sampling

Reasons Why Primary Data May Be Unreliable

• Sampling Bias

• Questionnaire Bias: This may occur when questions tend to lead respondents towards one particular answer. Because of this, the results are not a completely accurate reflection of how people act or of what they believe. As an example of a leading question could be "Which of the following factors best explains why you prefer Chocko bars to other manufacturers chocolate bars?" The question already assumes that the respondent prefers Chocko bars.

• Other forms of bias: These might include the respondent not answering in a very truthful way, perhaps because they do not want to admit to spending so much on music downloads or clothes.

Analysis of Quantitative Data

• Interpreting and analysing quantitative or numerical data can start with an attempt to identify key features of the data. Basic statistical techniques can be used.

Averages

• An average is a frequently used measure of a set of data.

• Averages tell us something about the central tendency of data. There are several different types of average that can be calculated from any set of data. The three most frequently used are:

  • the arithmetic mean, often abbreviated to just 'the mean'

  • the mode

  • the median

Arithmetic Mean

• Arithmetic mean: the value calculated by totaling all the results and dividing by the number of results.

• Mean = \frac{\sum x}{n}

Mode

• Mode: the value that occurs most frequently in a set of data.

• The mode can be of limited value. It would be wrong to assume from the results above that the average listening time had increased by two hours. The mode is also meaningless where the data contains results that only occur once (that is when there is no most frequently occurring item)

Median

• Median: the value of the middle item when data has been ordered or ranked. It divides the data into two equal parts.

• median= \frac{number \, of \, values +1}{2}

• When there is an even number of values, the mean of the middle two results will give the most accurate measure of the median.

Measures of Dispersion or Spread of Data

*Range
*Range: the difference between the highest and lowest value.

• range = highest \, result - lowest \, result

Analysis of Qualitative Data

• Qualitative research aims to understand why consumers behave in a certain way or how consumers might react to the launch of a new product. The answers to qualitative research are based on opinions, attitudes and beliefs. For that reason, qualitative data cannot be analysed using statistical techniques.

• Coding: the process of labelling and organising qualitative data to identify the main themes and the links between them.

• This process assigns labels to key words or phrases used by consumers during the research process. These responses can then be matched against other consumer's ages or income levels to establish relationships. Analysing these relationships, for example, between 'branding' and high-income consumers, will allow the business to plan marketing strategies.

Interpretation of Information Presented

*New research data can be presented in various ways that make the information easier to understand for decision makers. Research data might be presented in many forms including tables, charts and graphs:
* Tables: allow easy reference to the data and can be used to present a mass of data in a precise way
* Pie graphs (or pie charts): are used where data needs to be presented so that the proportions of different sets of data in relation to the total are clearly shown.
* Each section of the 'pie' shows how relatively significant that part of the data is compared to the whole. Pie graphs allow easy comparison between two sets of results to see if the proportions have changed.
* The size of each section is determined by the angle at the centre of the circle. This is calculated in the following way:
* Angle \, of \, section= \frac{value \, of \, one \, section}{total \, value \, of \, all \, sections} * 360 \, degrees
* Line graphs: are most commonly used for showing changes in a variable, such as sales, over time in time series graphs (see Figure 18.5). The line graph allows easy reference to trends in the data and shows up seasonal or other fluctuations clearly.
* Bar charts: use bands of equal width but of varying length or height to represent relative values