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Question1: How can a researcher ensure that the target audience interprets the questions the same way? What role does grammar play?

Question2: What are some common methods used in data analysis? When would you use each one?

Question3: Have you ever seen or used a semantic differential scale? What are some advantages or disadvantages of this scale?

Question4: Recall the readings and activities you have completed this week and research a TED Talk or other academic video that applies to one or more of your weekly objectives. Post a link to the video in your discussion thread

· What do you find interesting or surprising about the information in the video?

· How does it relate back to your weekly objectives?

Question5: What role does Excel play in data analysis?

Question6: What are some problems with data analysis and research? How can data be manipulated?

Question 7: After reading about Best Buy, research how another company such as Amazon builds customer share and loyalty.

Assignment 1:

resources:  The Market Research Toolbox, Ch. 11, The Market Research Toolbox, Ch. 14, and 15-minute Oil Change Data Set

Scenario: An oil change company is looking for ways to increase customer flow and revenue for the business. The company leaders have hired you to the company's market research consultant. 

Using raw data, determine two descriptive statistics regarding the oil change company that can be used to attract customers.

Write a 525- to 700-word paper in which you:

· Explain the descriptive statistics determined and their direct use in attracting customers.

· Analyze additional information needed to develop a better marketing strategy.

· Assess how you would collect this additional information.

Format your paper consistent with APA guidelines.

Assignment 2:

Scenario: Select a Fortune 500 company of your choice, and look for ways to increase customer flow and revenue for the business. The company leaders have hired you to be the company's market research consultant. 

Prepare a 7- to 10-slide Microsoft® PowerPoint® presentation, with speaker notes.

Address the following in your presentation:

· Provide four facts about the company using descriptive statistics.

· Conduct market research to determine additional business opportunities.

· Recommend two marketing strategies based upon the additional secondary research you conducted.

Format your presentation consistent with APA guidelines. 

Assignment 3:

Write a 525- to 700-word Market Research Implementation Plan based on the scenario you selected in your Week 2 Learning Team Assignment: Market Research Implementation Plan: Problem Identification and Project Outline.  

Continue and revise the previous paper to address the following in your plan:   

· Describe your business scenario.

· Explain secondary market research concerning and applied to the selected scenario.

· Discuss the research design used in your project, such as qualitative, quantitative, or mixed.

· Develop at least one data collection instrument to address your market research scenario.

· Recommend sampling procedures for the implementation of the instruments.

· Create figures and tables to demonstrate marketing information.

· Develop a timeline for implementation

· Create an Executive Summary to place at the beginning of the plan.

Format your paper consistent with APA guidelines.

The company that I we will be speaking on is Uber. Uber is a ride sharing app that is in most major city in the United States. Uber started in San Francisco and has branched out too many other cities. There are many different factors that go into the decision of where Uber can be successful. Uber needs to know the population of a city to be able to justify operating in that city. Not enough people in a city would not make it worth an individual to sign up for Uber and become a driver. Uber also needs to know everything it can about alternative modes of transportation already in existence in the city. Uber will also want to know what the density of the city and how far apart all main destination are, for example airports and the downtown areas, to be able to hire the correct number of drivers.

Population

Population data is an easy one to obtain but it is not a tell all piece of data. Market researches will obtain this information through city records and census records. We can not simply look at a population and assume what percentage would use Uber. After knowing the population, we must determine the diversity in the population. Uber’s main customer base is people going out and drinking and using Uber for a safe ride home. A retirement city like Palm Spring or some cities in Florida with a high occupancy of elderly people might not be the best fit for Uber. Also knowing the density of the city is crucial for the success for Uber. If a city is to spread out it would not be worth the time, gas, and money for either Uber driver or customer to use Uber.

Competition

Knowing your competition is important when venturing your company into new territory. Information about how many people use public transportation will be valuable data. This will give Uber an estimate of how many people are already using alternative forms of transportation. Figuring out how many taxi services and cars are out on the road. Knowing how many people and how busy a taxi service is will be difficult because taxi companies swill not just hand over this information. There are other ways to go about trying to estimate though. Every taxi must be documented and registered with the city they operate. This means that it is public record to know how many taxi cabs there are in any given city. Knowing this data, one could extrapolate how busy and how much a population of the city uses alternative modes of transportation.

Terrain of the new Environment

Uber being a ride sharing app must know the terrain of the environment they are about to venture into. For example, If there is one airport in the city located a significant distance from down town this must be taken into consideration. Uber must meet right in the middle of customer needs and driver needs to be successful. If a lot of the main destination like bars, malls, airports, and downtown areas are to spread out it will make it difficult for a company like Uber to be successful. For example, an optimal drive, an Uber driver would pick up a passenger from downtown and drive them to the airport then pick up another customer then drive them back to down town. This would be an example of the best-case scenario. In a city not populated enough or a city spread to wide this would be very difficult to achieve.

UBER

Everyone needs a safe ride to his destination despite the circumstances whether drunk, poor or from a far location. Customers require drivers to be careful and to provide their services according to their terms and conditions. Thus, a business scenario named Uber was developed first at San Fransisco in the United States of America. A research was carried out on how to help people with better means of transportation. It was due to the rise of heavy traffic, underperforming public means of transport and sometimes the diversity of the population (Cohen, Hahn, Hall, Levitt & Metcalfe 2016). Uber’s primary objective was to fulfil the needs of the customers’ transportation especially those from different parts of the country. It thought of an easier way of reaching out to them; e.g. by calling them via the telephone numbers. For instance, it was very hectic for someone in the downtown to acquire a taxi service to take him or her to the airport. Therefore, Uber came to the rescue by picking up and dropping off passengers from various locations. Different secondary market search considerations have been put into contemplation in the application of Uber. For instance, the population has played a major part in determining the success or failure of Uber business. It mostly considers an area that is densely populated to obtain as many customers as possible. Imagine a case where there would be less population, wouldn’t that be a major loss? Therefore, a place that is highly populated is essential in determining the number of drivers to hire and how much profit they will make at a specific period. In addition to that, competition is a point to put in the picture. One will have to learn their operations such as what makes them thrive or what their weaknesses are. They have to learn to be able to strategise plans to beat them and win over more customers. The terrain is another important part because Uber business cannot thrive in a place where the city is spread out. It has to improve the user productivity while at the same time attaining profits. It would be a loss to use much fuel to pick someone from suburbs to the airport without having an assurance of getting another customer from the airport to the suburbs (Cohen et.al 2016).

The mixed research design was used in the Uber business scenario because it provides a better understanding of the application of business. It enables one to focus on what was missed out in both the qualitative and quantitative research designs (Zikmund, Babin, Carr & Griffin 2013). For instance, it was possible to estimate the risk involved in the business by compiling the close-ended information from the like those of measuring attitudes and the open-ended information from the interviews and focus groups. If one method were used, it would be difficult to discover the weaknesses of the Uber business, i.e. requires much persuasiveness.

The use of questionnaires was one way of data collection. It is essential because it outlines all the interesting questions that one needed to know. It was then distributed to various people and the results obtained were analyzed. Credible answers were obtained and thus acquiring a genuine response to the business outcome. It enabled the actors to understand the weaknesses and strengths of the business. Interviews were also conducted to establish a person’s perceptions about the business scenario. It is also essential because the customers were enlightened on the primary objective thus developing a positive attitude towards the Uber business. They were able to comprehend differently and decipher a different opinion from other competitive means of transportation.

References

Cohen, P., Hahn, R., Hall, J., Levitt, S., & Metcalfe, R. (2016). Using big data to estimate consumer surplus: The case of uber (No. w22627). National Bureau of Economic Research.

Zikmund, W. G., Babin, B. J., Carr, J. C., & Griffin, M. (2013). Business research methods. Cengage Learning.