Final Report - Marketing Research.pdf

8/17/2019 Final Report - Marketing Research.pdf

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RESEARCH MVP’S PRESENTS: APPLE IOS VS. ANDROID

“Do UCF students prefer IOS (Apple) software or Android software, and why?”

Andrew Bagli

Theresa Joseph

Jordan Jorgensen

Jon Perales

Misha Kittilson

Natalie Alzate

Patrick Vaughn

Lionel Galvez

Katie Dewall

Caleb Stokes

Talitha Milton


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INTRODUCTION:

According to US News & World Report, in the past 4 years both cellphone and

smartphone ownership has risen dramatically in the United States. In 2011, 80% of Americans

owned a cellphone while only 35% owned a smartphone; however, in 2015, 92% owned a

cellphone and 68% owned a smartphone. This reflects a nearly doubling of the number of

people owning a smartphone in only 4 years. Among college students, the mobile market is

dominated between users of the Google software Android and the Apple's IOS software.

According to the Pew Research Center, 77% of 18-29 year olds own a smartphone, therefore

pinpointing the more popular software is essential to marketers trying to reach this

demographic. With the smartphone market continually expanding and being primarily used by

18-29 year olds, the significance and managerial implications of this research lies in

understanding the current generation's preference of Android or IOS software, which the

Research MVP’s sought to do by randomly surveying 200 UCF students. In addition to figuring

out which of the two softwares are more popular, we also decided to find out what specific

factors made consumers choose one software over the other.

Our research question was defined as: “Do UCF students prefer IOS (Apple) software or

Android software and why?” However, before proceeding with designing our research, we

evaluated whether our research idea was a good and feasible one. To test if our research idea

was good and feasible, we had to ask four questions. The first question to be asked: “Is there a

clear answer?” There is not a clear answer to our research question because students at UCF

have both IOS and Android operated phones. The next question: “Are there managerial

implications?” The intent of our research is to provide managers with information about why

consumers prefer the competitor’s software and decide how they are going to attract more

consumers to use their software. The data is expected to help identify and focus resources on

those consumers most likely to buy a product and to evaluate how that product best meets the


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consumer’s needs. The third question: “Is it easily understood?” Yes, the question is clear and

easily understood. The final question: “Is it a feasible research idea?” We determined that our

idea is feasible as we would be able to gather the information in a reasonable amount of time by

surveying 200 UCF students to collect our data.

With such strong and divided opinions about which phone is the best from the college

generation, the Research MVP’s were puzzled over what factors determine preference for each

brand. Both software platforms have the same basic functions so there had to be other factors

that made one more appealing to consumers. It was crucial to understand where these two

softwares may differ to gain an understanding of why one may have an edge over the other.

The IOS software's proprietary license is configured so that its features are pre-set in a secure,

user-friendly manner. In this way, Apple is able to control how they want their product to be

used while still meeting all of the user's needs. Its interface uniformity generally limits

customization to minor cosmetic adjustments such as wallpapers. Their app market is tightly

controlled which results in a user experience that is typically more secure and higher quality,

delivering consistent performance. In contrast, Android is an open source model which allows

for heavy user customization including the use of 3rd party features from outside developers.

These features could include wallpapers, widgets, and external app markets which make for a

greater number of apps than those available on IOS devices. Because of this, the Android

software has a more personalized experience and can be adjusted to be unique to each

individual user. The Android software is available on numerous devices from several different

mobile phone companies as opposed to the IOS software being exclusive to Apple's family of

products. Android devices are typically less expensive and more widely available than IOS

devices. With less availability, Apple has had to create a captivating marketing strategy

including advertisements and promotions to appeal to a wide audience of consumers. This

strategy is designed to counter the market's general reliance of Android as a default operating

system for mobile devices.


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These various differences in software led us to deduce and isolate three main factors

that influence a consumer's decisions. The first of these were consumer's preference of

simplicity or customizability. The second was pricing of the device. Were consumers more

drawn to a more available and inexpensive product, or is consumers willing to pay more for a

higher quality product? The third was whether a specific style of promotion and marketing

strategy greater captures consumers’ attention. We also chose to research general

demographic factors including age and gender. In sum: these independent variables were all

chosen with intuition in mind of how they affect the dependent variable to avoid spurious

association.

ANALYSIS:

It is important to study the relationship between the dependent variable and the

independent variables to find specific managerial implications for a research question. For our

research, our dependent variable is what phone software a student prefers, IOS or Android. Our

independent variables are the price of the phone, the influence of promotions, simplicity vs.

customization, age, gender, and the school year of the student. We wanted to study the

relationship between the dependent variable and these independent variables because we

wanted to see what phone companies should focus on in their advertisements that are

significant and effective when targeting UCF students.

We accumulated 200 UCF students’ responses to a survey we created that addresses

our research objective to collect our primary data. We utilized an online survey

via SurveyMonkey.com as well as a physical survey via the simple random method to collect

our data. The target population of our research is the UCF Student Body (approximately 60,000

students) and our sample size was determined as 200. Therefore, by using the simple random

method, over the course of a few days we stood at the Student Union and passed our surveys

to every 300th student exiting the building. Our survey consisted of eight questions formatted

https://www.surveymonkey.com/https://www.surveymonkey.com/https://www.surveymonkey.com/https://www.surveymonkey.com/


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respectively in open-ended, closed-ended, quantitative/scalar rating and demographic

responses (see Appendix A for survey questionnaire). Our participants varied in age (from 18 -

26) and grade level, and were 66% male and 33% male (see Appendix B for graphical displays

of response demographics). Our data was very intriguing - we found that 68% of the students

surveyed preferred IOS software and 32% preferred Android. When analyzing the qualitative

response to the first open ended question of our survey (“What are the three most important

features you consider when deciding what kind of phone to purchase?”), many students

mentioned price, operating system, and overall user friendliness.

After collecting our data, we checked the collinearity between each of the independent

variables to make sure there was not a collinearity problem in our data. Collinearity dilutes the

effect of the independent variables and exists when variables are very similar and have a high

correlation. After checking the variables, we found that none of our independent variables had a

number higher than .3, therefore there were no variables were highly correlated and we did not

have to drop any variables (see Appendix C for respondent data snapshot and collinearity

output table).

Based on our regression output, we found that R2 is .132, which means that 13% of the

variation of the dependent variable can be explained by the significant independent variables,

which are price and simplicity/customization (see Appendix D for regression output) . Although

this percentage is fairly low, if we had more time and resources to research this idea more

thoroughly the R2 would have been higher. We also could increase the R2 if we added more

independent variables to research and add to our data. If we were researching this idea for a

company and had a larger research group and more survey participants, the R2

would have

been significantly higher.

We found in our regression output that the two independent variables that were most

significant were the price and simplicity/customization (see Appendix D for regression output).

These were the only two variables that had a p-value less than .5 (which is the standard number


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used to find the significance of a variable), but we found that simplicity/customization was most

significant of all the independent variables because it had a p-value less than .01 (which is the

standard number to find if a variable is even more significant than others). The coefficients of

the independent variables explain which attributes are favored towards the IOS (0 value) or

Android (1 value) dependent variables. From our data, if a survey respondent chose the

significant independent variable of price as most important (0.0642 coefficient), then that

consumer favors the Android software (1 value) (see Appendix D for coefficients on regression

output). If a survey respondent chose the significant independent variable of customization as

most important (0.2734 coefficient), then that consumer favors the Android software (1 value).

After analyzing the qualitative data from our survey in addition to the regression output

and finding which independent variables were significant and insignificant, we were able to draw

managerial implications. Our data can help managers and decision makers market their phones

more effectively toward their target customers, especially when it comes to simplicity versus

customization. Since the data proved that this category was most significant in the regression, it

is a reliable source for managers to look at to better understand the reasons why the customers

value when choosing between buying an iPhone or Android phone. Managers can focus their

advertisements and even design of future products with this information in mind. Apple is

historically a brand known for its simplicity while Android is built on user customization so this

information allows these brands to promote this aspect within their advertisements as our

research proves this factor is very important in making a purchasing decision.

Another significant variable in the regression was price of the device. Although this was

not as significant as the simplicity/customization variable, this was not a surprising piece of

information as many consumers are fiscally conscious; however, it still provides valuable

insights for decision makers. Price being an important factor in a consumer’s buying decisions

means that Apple and Android can both structure and advertise their prices to best appeal to

consumers. For example, Apple does not give discounts on their products meaning it is the


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same price wherever you were to buy the product whereas, Android products are usually slightly

less expensive and can go on sale. Therefore, if Apple sees a lull in sales they could potentially

increase sales by providing the product at a slightly lower price to better compete with Android.

The regression also showed some insignificant variables that should be noted for

managerial implications. For example, the variables of age, gender, and class standing all were

insignificant in our regression analysis, therefore, it would not benefit the managers and

decision makers to advertise the Apple and Android products based on those variables since

there is no significant difference between a man or woman of any age buying one product over

another. Although this is a simple fact, it is worth noting as wasted targeted advertisements (in

the aspects of age, gender and class sanding) would prove as a loss in profitability for the

company as our research shows this will have no effect on the dependent variable, e.g. the

sales will not change.

CONCLUSION:

One of the most important things to consider when choosing a smartphone is what type

of operating system a phone uses. The operating system of smartphones comes pre-installed

on our phones and is what allows our phones to think and process information. We chose to

research the question “Do UCF students prefer IOS (Apple) software or Android software?”

because we were interested in finding what type of phone software students preferred. We also

wanted to research this question to see what type of managerial implications phone companies

could use to promote their products through advertisements.

After surveying 200 UCF students and collecting our data, we found that there was no

collinearity problem between our variables, which meant that we were able to use all our

independent variables. We found in our regression that the most significant independent

variable was simplicity/customization, followed by the price of a phone. After gathering this

information, we were able to draw managerial implications. Managers can examine this data


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and see that consumers value the simplicity/customization aspect of operating systems,

therefore advertisements should focus on how simple and user-friendly an Apple iPhone can be,

or how customizable an Android phone is. Managers can also see that customers take into

consideration the price of a phone, therefore Apple and Android can structure and advertise

their prices to appeal to their customers. Although the demographic variables (gender, age, and

class year) were not significant variables, managers and decision managers can look at this

data and see that including these variables in future advertisements would be a waste of time

and money for companies. Although our R2 was only .132, with more time and survey

responses our R2 would have been much higher. From our data, if a survey respondent chose

the significant independent variable of price as most important (0.0642 coefficient), then that

consumer favors the Android software (1 value) (see Appendix D for coefficients on regression

output). If a survey respondent chose the significant independent variable of customization as

most important (0.2734 coefficient), then that consumer favors the Android software (1 value).

In conclusion to our research, we found that 68% of the UCF students that were

surveyed preferred the IOS operating system, whereas 32% of UCF students preferred Android.

From our regression analysis, we found that students who preferred IOS software found

simplicity important and price unimportant, whereas students who preferred Android software

found both customization and price very important. We hope that phone companies will start

emphasizing the simplicity/customization and price aspect in promotions to boost their phone

sales in the future.


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APPENDIX A: Survey Questionnaire


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APPENDIX A (cont.): Survey Questionnaire


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APPENDIX B: Demographic Graphs

Gender of Survey Respondents

School Year of Survey Respondents


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APPENDIX C: Respondents Data Snapshot & Col linearity Output Table

Respondents Data Snapshot

Collinearity Output Table


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APPENDIX D: Regression Output

Regression Summary Output


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References

US News & World Report. (2015). Smartphones are taking over the US. Retrieved April 13,

2016 from http://www.usnews.com/news/blogs/data-mine/2015/10/30/smartphones-are-

taking-over-the-us

Pew Research Center (2013) Smartphone Ownership. Retrieved April 14, 2016 from

http://www.pewinternet.org/files/old-

media/Files/Reports/2013/PIP_Smartphone_adoption_2013_PDF.pdf
http://www.usnews.com/news/blogs/data-mine/2015/10/30/smartphones-are-http://www.usnews.com/news/blogs/data-mine/2015/10/30/smartphones-are-http://www.pewinternet.org/files/old-media/Files/Reports/2013/PIP_Smartphone_adoption_2013_PDF.pdfhttp://www.pewinternet.org/files/old-media/Files/Reports/2013/PIP_Smartphone_adoption_2013_PDF.pdfhttp://www.pewinternet.org/files/old-media/Files/Reports/2013/PIP_Smartphone_adoption_2013_PDF.pdfhttp://www.pewinternet.org/files/old-media/Files/Reports/2013/PIP_Smartphone_adoption_2013_PDF.pdfhttp://www.pewinternet.org/files/old-media/Files/Reports/2013/PIP_Smartphone_adoption_2013_PDF.pdfhttp://www.usnews.com/news/blogs/data-mine/2015/10/30/smartphones-are-

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