4.00 Understand promotion and intermediate uses of marketing- information.

Research Design Define the following terms: research design, descriptive design, exploratory design, causal design.  Research design - a formal plan of action for a research project  A design is used to structure the research, to show how all of the major parts of the research project - - the samples or groups, measures, treatments or programs, and methods of assignment -- work together to try to address the central research questions

Research Design  Descriptive design - to identify the cause of something that is happening find out what age group is buying a particular brand of cola, whether a company’s market share differs between geographical regions or to discover how many competitors a company has in their marketplace  Exploratory design - This genre of research simply allows the marketer to gain a greater understanding of something that s/he doesn’t know enough about  Differing mainly in design from descriptive research, exploratory research is used principally to gain a deeper understanding of something. The design is far more flexible and dynamic than that of descriptive research

Research Design  Causal design - explores the effect of one thing on another and more specifically, the effect of one variable on another  if a clothing company currently sells blue denim jeans, causal research can measure the impact of the company changing the product design to the color white  causal research is a way of seeing how actions now will affect a business in the future &Itemid=64

Research Design  Describe general purposes of marketing research (e.g., explain, predict, monitor, discover, test hypotheses).  Explain the relationship between the research design and the purpose of the research.  The design is based on what is being researched, so the two must be matched in order to succeed  Determining the research purpose sets the stage for the rest of the research plan

Research Design  Discuss the purposes of using descriptive research.  To find out why (the root cause)  Explain the purposes of using exploratory research.  To learn more about an issue, competitor, current customers, potential customers  To understand

Research Design  Distinguish between descriptive and exploratory research.  Descriptive helps me find out what is going on  Exploratory helps me understand something better  Describe the purposes of using causal research.  what impact a specific change will have on existing business (cause and effect)

Sources of Data  Distinguish between primary and secondary marketing research.  Describe occasions for using primary sources of marketing research data.  Discuss primary sources of marketing research data.

Sources of Data  Describe advantages/disadvantages of primary marketing research.  Explain types of primary research (i.e., quantitative and qualitative).  Explain occasions for using secondary sources of marketing research data.

Sources of Data  Describe secondary sources of marketing research data (i.e., internal and external).  Describe advantages/disadvantages with using internal sources of secondary data.  Explain reasons that businesses need to analyze external data.

Sources of Data  Explain advantages/disadvantages of secondary marketing research.  Discuss reasons for outsourcing marketing research activities.

Sampling Define the terms population, sample, probability sampling, non-probability sampling, and sampling plan.  Population – group being studied (customers)  Sample – Sub-division of the population, often easier to study

Sampling  Probability sampling – Selecting a sample based on the probability the results will apply to the whole population.  With a probabilistic sample, we know the odds or probability that we have represented the population well  Researchers must set up a process that assures that the different members of a population have an equal chance of selection  Another reason for probability sampling is the need to eliminate any possible researcher bias

Sampling  Non-probability sampling – does not involve random selection  nonprobability samples cannot depend upon the rationale of probability theory  Sampling plan – bases it decision on a sample of the lot, not the entire lot  Lot is a group or population

Sampling Discuss the advantages of using a sample to represent the population.  There are often difficulties measuring whole populations because: -  The large size of many populations  Inaccessibility of some of the population - Some populations are so difficult to get access to that only a sample can be used. E.g. prisoners, people with severe mental illness, disaster survivors etc. The inaccessibility may be associated with cost or time or just access.  Destructiveness of the observation- Sometimes the very act of observing the desired characteristic of the product destroys it for the intended use. Good examples of this occur in quality control. E.g. to determine the quality of a fuse and whether it is defective, it must be destroyed. Therefore if you tested all the fuses, all would be destroyed.  Accuracy and sampling - A sample may be more accurate than the total study population. A badly identified population can provide less reliable information than a carefully obtained sample.

Sampling  Explain when it is appropriate to use a sample of the population.  We obtain a sample of the population for many reasons as it is usually not practical and almost never economical to test the whole population  Distinguish between probability and non- probability sample designs.  The difference between nonprobability and probability sampling is that nonprobability sampling does not involve random selection and probability sampling does probability sampling

Sampling  Explain types of non-probability sample designs  Accidental, Haphazard or Convenience Sampling – “man on the street”  Purposive Sampling - usually would have one or more specific predefined groups we are seeking

Sampling  Describe types of probability sample designs.  Simple Random Sampling - akin to pulling a number out of a hat  Stratified Random Sampling - dividing the population into subgroups based on variables known about those subgroups, and then taking a simple random sample of each subgroup  Cluster Sampling -useful for those who know little about the population they’re studying. First, the researcher would divide the population into clusters (usually geographic boundaries). Then, the researcher randomly samples the clusters  Multistage Sampling - the most complex sampling strategy. The researcher combines simpler sampling methods to address sampling needs in the most effective way possible

Sampling Explain types of sampling bias/errors.  Sampling error can make a sample unrepresentative of its population. Sampling error comprises the differences between the sample and the population that are due solely to the particular participants that have been selected.  Sampling bias - Sampling bias is a tendency to favor the selection of participants that have particular characteristics  Non-sampling error (measurement error) - A non- sampling error is an error that results solely from the manner in which the observations are made.

Explain types of sampling bias/errors. Cont.  The interviewers effect - No two interviewers are alike and the same person may provide different answers to different interviewers  The respondent effect – Participants may deliberately give incorrect answers (for many reasons). This type of error is the most difficult to prevent because it results from out right deceit  Knowing the study purpose - Knowing why a study is being conducted may create incorrect responses

Sampling  Discuss the purpose of sampling plans.  Allows the study to meet the objective by sampling the correct population  Explain the components of a sampling plan.  Accurate representation of the total population being studied - the sample should be representative so that the researcher can make accurate estimates of the thoughts and behaviors of the larger population  Sampling unit—determining who is to be surveyed  Sample size—determining the number of people to be surveyed  Sampling procedure—determining how the respondents should be chosen  Objective selection  Objective testing