Elements of an Analytical Model and Methods of Marketing Research
Short Answers:
Marketing Research Essays
• 10 points each
• Submission should be more of a narrative explain the concepts and their application as opposed to only bullets. You can use bullets – but they should be explained
• Up to a page for each one – 10 font 1.5 spacing
• Submit to Blackboard
PLEASE ONLY USE COURSE MATERIALS
1. What are the major elements and purpose of an analytical model and how can it be used in marketing research? What type of variables are on model and how are the relationships among the variables explained in a model?
2. Define the main types of error in marketing research that comprise “total error.” Define the types of subject response error and mitigation strategies to handle these types of error in survey research. In general, how can survey research error be mitigated?
3. What are the pros and cons of observation research? Define, and provide an example, of the types of observation research approaches. Finally, how can content analysis and forensics observation methods be used in research.
4. Discuss the value, use, and purpose of interviews and focus groups in marketing research. How might you set-up and manage a focus group to understand consumer’s opinions and attitudes who just spent the day at Disneyworld?
Marketing Research
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Question 1
An analytical model is a tool that organizes elements of data and determines how those elements relate to one another. Unlike most other models that do not depict reality, analytical models are used to represent actual data. There are four major elements of an analytical model. The first is a scenario-based element that focuses on and analyses a particular scenario. The second is flow-oriented, which focuses on the flow of events from start to finish. The third is class-based which focuses on grouping related activities together. The last is behavioral, which aims at categorizing concepts with similar characteristics together. An analytical model aims to solve a challenge or answer a set of questions quantitatively. An analytical model may serve to solve various aspects of marketing dynamics in marketing. It may also be used to answer questions such as how many, where, and how often. The other purpose of the analytical model is to help the researcher easily understand or even visualize the relationships between the various variables in the dynamics of marketing research.
A variable refers to one of the building blocks of the analytical models. The best way to define a variable is the items that can be measured. Since variables can be measured, the researcher attempts to manipulate the variables in such a manner to obtain desired results. There are two main types of variables. These are dependent and independent variables. The relationships in a model are explained in terms of the variables. The model works in such a way that others determine certain variables. Take, for instance, price as a variable. Several factors may determine the cost of an item in the market. These factors are referred to as variables. The factors that determine the price may include transport expenses, location of the business, the type of the item being sold, and the relationship between the buyer and the seller. Based on these observations, it is proper to conclude that the relationships between variables on a model are explained in terms of other variables.
Question 2
The total error refers to the discrepancy between the true value and the value that one has obtained in the research project. Many forms of errors can lead to this kind of discrepancy. Although these errors are numerous, they can be broadly categorized into two main groups. These are sampling and non-sampling errors. Sampling errors are those that reflect the difference between the estimate that is derived from a sample and the true value. There are various types of sampling errors. These include variance, relative standard error, and confidence interval error. Moreover, multiple types of errors can cause a non-sampling error. These include the failure to identify the target population and the inadequate survey population. Non-response bias can also be another reason for the non-sampling error. Other reasons for non-sampling errors include the respondent's bias, processing errors, and misinterpreting the results found. Misinterpreting the results is a very common form of non-sampling error that can significantly affect the total error. There are various types of subject response errors. One such error is the coverage error. This error occurs when there is a lack of correspondence between the sampling method used and the target population. The error can simply be mitigated by ensuring that there is direct correspondence. The second kind of subject response error is sampling. This kind of error occurs when the size of the sample is too small to make any meaningful inference. The best way to mitigate this error is to ensure that the sample is adequate to make an inference. The third kind of error is the measurement error. This error occu...