bank of america - final

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Rollins College Professor Dr. Fetscherin

December 3rd, 2015

!Brand Report

Alexander Blessig

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Table of Contents Table of Contents .................................................................................................................... 2

1 Introduction and Objectives ........................................................................................ 3 1.1 Industry Overview ............................................................................................. 3 1.2 Brand Sentiment ............................................................................................... 3 1.3 Objectives of the Paper ..................................................................................... 4

2 Literature Review ........................................................................................................ 4 2.1 Relevance of Analysis ....................................................................................... 4 2.2 Importance of Customer Brand Relationships .................................................. 5 2.3 Brand Love and Hate ....................................................................................... 5

3 Research Method ......................................................................................................... 6 3.1 Scope of the research ........................................................................................ 6 3.2 Data Collection ................................................................................................. 7 3.3 Data Cleaning Process ...................................................................................... 7 3.4 Errors with Data ............................................................................................... 8

4 Respondent Profile ...................................................................................................... 9 5 Love and Hate of Brands ........................................................................................... 10

5.1 Hypothesis Testing .......................................................................................... 10 5.2 Brand Awareness ............................................................................................ 10 5.3 Brand sentiment – Haters and Lovers ............................................................. 12 5.4 Brand Hate ...................................................................................................... 13 5.5 Brand Love ...................................................................................................... 14 5.6 Bank comparison ............................................................................................. 16 5.7 Influence of Income and Education ................................................................ 18 5.8 Unethical Behavior ......................................................................................... 19 5.9 Possible improvements ................................................................................... 19

6 Conclusions ............................................................................................................... 21 References ............................................................................................................................. 22 Appendix ............................................................................................................................... 23

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!!!!Figure 2: I HATE Bank of America

1 Introduction and Objectives 1.1 Industry Overview Bank of America is one of the four largest financial institutions in the United States. With an asset size of $2.14 trillion1, it is a very influential bank that affects many people’s lives. This brand report on Bank of America shows that it is a strong and internationally recognized brand. However, its brand image has been impacted negatively by many scandals and the financial crisis of 2008/2009. Four major banks, listed in Figure 1, dominate the U.S banking industry. They are compared to each other with asset size, customer base, Facebook likes, Twitter followers, Google brand hate hits, and Google brand love hits. This gives a good indication about the banking industry in relation to social media sentiment and online appearance – two important factors for any brand image. The banking industry itself is so significant that influences people from all social classes. Major U.S. Banks

Asset Size (Trillion $)

Customers (Million)

Facebook Likes

Twitter Followers

Google Hits Brand Hate

Google Hits Brand Love

JP Morgan Chase

2.58 652 3,865,065 304,000 326,000 443,000

Bank of America

2.14 493 2,280,928 417,000 522,000 18,500,000

Citigroup 1.83 2004 1,053,663 662,000 380,000 556,000

Wells Fargo 1.74 705 839,884 192,000 481,000 11,400,000

Figure 1: Social Media presence 1.2 Customer Sentiment The customer sentiment shows that the company needs to improve its brand image significantly in the future. Hate websites such as www.ihatebankofamerica.com6 (see Figure 2) imply that there is a growing negative sentiment towards the image of the bank. The social media mentions on Talkwalker.com, the Trackur website tool, and Yougov.com show very negative feelings towards the brand and its image. Exhibit 2 in the Appendix illustrates

some of the main reasons why people do not like the bank. They describe it as “greedy, dishonest, misleading, despicable, and irresponsible”7, which are all serious negative attributes for a bank. There is even a Bank of America hate

!1 http://www.bankrate.com/finance/banking/americas-biggest-banks-8.aspx!2 http://www.tomsguide.com/us/jpmorgan-chase-breach-disclosure,news-19676.html 3 http://about.bankofamerica.com/en-us/our-story/our-history-and-heritage.html#fbid=XFkhmGPft5w/hashlink=today 4 http://www.citigroup.com/citi/about/citi_at_a_glance.html 5 http://www.complaintslist.com/banks/wells-fargo/ 6 http://www.ihatebankofamerica.com/ 7 https://today.yougov.com/opi/browse/Bank_of_America

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song available on YouTube composed by a former customer with 30,000 views8. However, Bank of America has 2,280,928 “Likes” on Facebook and 417,000 Followers on Twitter. Figure 1 illustrates each of the four major banks and compares its social media presence on Facebook9, Twitter10, and relates that to its total Asset Size as of 11/19/15. There is a correlation between Asset Size of the Bank and the amount of Facebook “Likes” that a bank has. Twitter followers are actually inversely related to the Asset Size except of Wells Fargo, which has the least amount in both categories. The Google hits of brand hate are fairly equal with Bank of America having the most hits. To be able to restructure and repair the image completely, more in depth analysis is needed. To analyze the source of the brand hate and sentiment of customers towards Bank of America further research needs to be done. 1.3 Objectives of the Paper The purpose of this research paper is to evaluate why people hate or love banks. The project will entail exploratory research and collecting primary data through a questionnaire as a convenient sample. It is important to produce first hand primary data that is specifically tailored for this image problem. Overall, the problem of dissatisfied customers and a shattered brand image are so significant that they need to be addressed in further primary research. The goal of the questionnaire is to determine why people hate or love Bank of America and its competitors. Furthermore, the survey intends to understand the customer profile of those haters and lovers and why they hate or love a certain brand. To be able to analyze correlations within the data, Excel and SPSS are used. The technical analysis will range from simple descriptive data to regression analysis, ANOVA matrixes, and T tests in order to test the hypotheses and prove if they are right or wrong.! 2 Literature Review 2.1 Relevance of Analysis As one of the largest banks not only in the United States but also in the entire world, Bank of America has an immense responsibility to itself and its customers. Next to corporate social responsibility, the companies’ brand image is vital for customer acquisition and retention. In the past, this has been a serious problem for the company, as illustrated in the brand sentiment section above. Many academic papers and reviews have covered the topic of satisfaction of banking services. The literature review will relate to academic studies and the hypothesis in the research methodology will be based on the conclusions from the literature review. A vital part of the analysis is its justification because it makes the research project relevant. Many articles will be summarized and in order to show the importance of a brand image analysis and illustrate its correlation to the direct revenues and profits of Bank of America. This is a key trait for the company to succeed in the future because the banking industry seems to have a big image problem since the financial crisis in 2008/2009 as it was made responsible for most of the economic downturn afterwards. It is now up to all these companies to get rid of their ‘greedy’ image and improve their customer brand relationships.

!8 https://www.youtube.com/watch?t=64&v=2VAdLxxfIVo 9 https://www.facebook.com/ 10 https://twitter.com/!

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Figure 4: Dislike brands

2.2 Importance of Customer Brand Relationships The articles that will be mentioned show the importance of consumer brand relationships and why people love or hate brands. In the article “The power of brand love” by Barker, Peacock, and Fetscherin11, the importance of this research paper is justified to a great extent.

The main purpose of the article, is to prove that “brand love leads to greater profitability and total shareholder return” (Barker, Peacock, and Fetscherin, 2015), vindicates this research project. If there was no correlation between those two factors, it would not make sense for company executives to perform such a research study because it is of utmost importance to increase profits at all times. Furthermore, the article mentions

the importance of “brandscape”, which implies that love towards a certain brand can exist towards more than just one brand (Barker, Peacock, and Fetscherin, 2015). As Figure 3

shows, even in very different industries such as Airlines, Drug retail or Specialty retail, companies with a higher BERA score generate higher revenues. “Brand relationships – and specifically brand love – permit companies to monetize increased willingness to pay a premium, gain market share, remain price-competitive or increase profits” (Barker, Peacock, and Fetscherin, 2015). With the help of the so-called BERA (Brand Equity Relationship Assessment) analysis, it can be determined that companies with a higher BERA

score are more likely generate higher profits than companies with a lower BERA score. This score is composed of Brand Regard, Competitive Uniqueness, Brand Cognizance, and Brand Meaningfulness (Barker, Peacock, and Fetscherin, 2015). The article “Negative Double Jeopardy: The role of anti-brand sites on the Internet” by S. Umit Kucuk is important for this research study as such a website already exists for Bank of America. More valuable brands have a higher attraction towards brand hate websites than less valuable brands. This would indicate that Bank of America is a valuable brand name as well. It is also mentioned that those hate website are one of the biggest fears of major CEO’s because they can decrease profits. 2.3 Brand Love and Hate Another important article related to this research project is “Emotions that drive consumers away from brands: Measuring negative emotions toward brands and their behavioral effects” by Simona Romani, Silvia Grappi, and Daniele Dalli. It is vital to understand the

!11 https://blackboard.rollins.edu/bbcswebdav/pid-148803-dt-content-rid-479944_1/courses/90351.INB390T.1.201509/Viewpoint.pdf

Industry Company BERA score

EV to Rev. ratio

Airlines Southwest 79.3 1.5x

Delta 61.5 1.2x

Drug retail Walgreens 91.4 1.0x

CVS 87.3 0.9x

Specialty retail GNC 60.7 2.1x Vitamin Shop 32.8 1.2x

Figure 3: Relevance of BERA scores

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Figure 5: Brand Love and Hate

0% 20% 40% 60% 80% 100%

Hate/ Love?

Love Hate

reasoning behind brand love and hate. As Figure 4 illustrates, the brand hate or just dislike can be very strong and widespread12. One needs to comprehend why a customer decides to love or hate a certain brand. A certain stimulus in the human brain triggers the will to buy or not buy a product often originating form brand love or hate. Important for the brand is “the visual and verbal information that serves to identify and differentiate a brand” (Brakus, Schmitt, Zarantonello, 2009). According to the article “Consumers have Humanlike Relationships with Brands” by Jeanette Mulvey, consumer brand relationships are very similar to human relationships between people. She states that on one hand consumers relate to brands a certain way because of economic factors, such as price and quality of the

products. On the other hand, a “communal relationship” (Mulvey, 2012) is important because it promotes an emotional relationship to the brand built on partnership and trust. The article “Someone has to hate your brand” by Drew McLellan reveals another perspective to the topic of hating and loving certain brands. The

author claims that it is actually beneficial if there is hate towards a brand because “it has to stand for something” as it “cannot be neutral” (McLellan, 2014). His main point is that there is nothing worse than consumers not having an opinion or a feeling associated with a brand. Companies that “try to be everything to everyone” (McLellan, 2014) are in the “mushy middle” (McLellan, 2014) as Figure 513 graphically illustrates. This is an important consideration for this research project because it means that the amount of people that select “neutral” in any of the questions in the survey have a significance for the brand analysis as well. On top of that, it can change the interpretation of the haters of the bank because they can be considered “valuable” as the customers at least have an opinion about the bank. The brand connection matrix and the brand feeling matrix, developed by Dr. Fetscherin and Dr. Heinrich clearly show the importance of strong customer relationships with brands. They both factor in emotional connections – as in feelings and affection – and functional connections, meaning thinking and cognitive perception (Heinrich, 2014). The second one relates more to the emotional part in detail. Overall, the research extracts mentioned above justify this research paper and underline the importance of the following research.

3 Research Method 3.1 Scope of the research In order to analyze the love and hate towards the brand Bank of America, a representative survey was conducted. It helps the research to gain validity and illustrate a real-life profile of customers while measuring their satisfaction with the brand. The survey was developed

!12 https://www.linkedin.com/pulse/how-prepare-your-brand-facebook-dislike-button-sarah-segal 13 http://wordofmouth.org/blog/someone-has-to-hate-your-brand/

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Sampling error Nonresponse error

Response error Noncoverage error

Figure 6: Errors with Data

with Qualtrics, a survey development software. After determining which questions are significant for this research project (see Exhibit 1 in Appendix) the main goal was to get as much information from the respondents as possible. Therefore, most of the questions were arranged as a Likert scale, bipolar questions or rank orders to provide the respondents with a lot of options and get a detailed insight into their emotions about a brand. Four major companies dominate the banking industry with Bank of America being one of the most influential amongst all of them. The ‘big four’ manage 39% of all U.S. banking customer deposits14, so it is the main reason why those 4 banks were chosen as the main industry players to compare.

3.2 Data Collection A total number of 216 respondents were asked to answer this survey about financial institutions within the United States. It is important that the number of total valid respondents is above 13815 because that is the necessary number of respondents needed to make statistical analysis of data valid. The respondents were purchased via Amazon

Mechanical Turk (MTurk) and selected randomly. The sampling method used for this survey was convenient sample, which is “a nonprobability sample in which population elements are included in the sample because they were readily available” (Brown, Tom J., Gilbert A. Churchill, 2014). The duration of the survey was 6-7 minutes on average. It was assured that all possible answers for questions were MECE (Mutually Exclusive and Collectively Exhaustive), meaning that the answers do not overlap between categories that could cause confusion and the answer choices cover the entire bandwidth of answer

possibilities. Their analysis will determine why people hate or love Bank of America and its main competitors. The questions’ purpose can be discovering information about the respondents’ opinions about brands or simply collecting their demographic data. Exhibit 1 in the Appendix illustrates each question of the survey and its significance towards the goal of the questionnaire.

3.3 Data Cleaning Process In order to properly clean the data certain rules and regulations were applied. After exporting the data from Qualtrics, time was taken to look at the data and really understand it. First, all the headings were shortened and labeled accordingly so that each question and statement could be identified quickly. This makes it easier to import the data to SPSS and recognize it faster. All responses that took less time than 2 minutes or answered less than 50% of all questions were deleted as they provide insufficient or false data for the evaluation of the questionnaire. That included respondents that answered “N/A” or “Don’t Know” more than 3 times for a different question within the survey. Also, the responses that

!14 http://www.nasdaq.com/article/big-four-us-banks-held-35-of-all-us-deposits-at-the-end-of-2014-cm455813 15 http://www.ajronline.org/doi/abs/10.2214/ajr.138.1.180

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had clearly contradicting answers or did not finish the survey were eliminated. The “N/A’s”, “Don’t Knows”, and “Prefer not to answer’s” were deleted from each questions that included such. After cleaning, those were replaced with empty cells so that their result would not change the results of the data. For all the question with a Likert scale from 1 to 5, the “6” was deleted as well, because it represented the “Don’t Knows”. This selection process narrowed all the useful responses down from a 216 to a total of 165. After that, it was assured that all the data looks the same. Generally, all responses were edited so that they have the same format. The text and open-ended responses were rewritten so that they are consistent. Examples would be capitalization of letters and deleting spaces. Many respondents selected a value for a questions’ “Other” category but did not fill in the text box about what is meant by “Other”. These values were also deleted as they would change the totals results and averages of the dataset. The text in those “Other” questions was edited so that it matches the format of the other text open-ended answers. The answers to the question “What do you like or dislike about Bank of America?” and “What could Bank of America do to improve its brand image?” were placed into different general categories. These categories are used to determine whether the answers were positive or negative and what general message they suggest. The columns that cannot be properly analyzed in SPSS, such as the open-ended text questions, were marked in yellow so that they are not part of the export process into SPSS. 3.4 Errors with Data It can be stated that the profile of respondents is very diverse in age and gender. When analyzing the data there are a couple of errors that might be encountered. These include “sampling errors, noncoverage errors, nonresponse errors, response errors, and office errors” (Brown, Tom J., Gilbert A. Churchill, 2014). Most common are sampling errors, because it is not always clear which sample to use as the respondents. Noncoverage errors occur because of failure “to include qualified elements of the defined population in the sampling frame” (Brown, Tom J., Gilbert A. Churchill, 2014). Nonresponse errors – as the same says – are missing answers from respondents, while response errors are when a respondent answers with an inaccurate response. Lastly, an office error is when the researcher makes a mistake in coding or editing the data. In order to avoid those kinds of errors the process and steps of the graphic below need to be followed:

!!!Figure 7: Verify Data sufficiency

Most of these errors were not encountered during this research project. However, some errors occurred and had to be dealt with. The most frequent ones were response and

Right people were asked in the survey

They responded and answered each question correctly

The data was edited and coded properly

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noncoverage errors. Many respondents did not answer the complete questionnaire and if they left out more than 50% of the questions, their whole set of answers had to be deleted. Some respondents selected answers that did not correlate with other answers they gave during the questionnaire, so those had to be deleted as well.

ℎ = !!!! !(1− !)

The formula above shows how far off the sample size is from the original estimate. In this case, the sample size it the right size for the purpose of this project. The sampling frame of the survey was very accurate. With the help of the formula above, it was determined that the correct sampling frame is around 200 respondents, which is a goal that was reached. 4 Respondent Profile

A consumer profile was created of Bank of America customers portraying the age, gender, income, and level of education of the people taking part in the survey. This is important when analyzing the results of the data because it has to be determined if the demographics of the respondents have an influence on the sentiment towards a brand. Out of the total of 165 respondents, 54% are male and 46% are female. The average age of all respondents of the survey is 36.7 years old. The average age of all respondents has a standard deviation of 11.8 years. It was differentiated between women’s average age (37.9) and men’s average age (36.1). The youngest person that participated in the survey is 19 years old, while the oldest person is 74. The highest frequencies of participants are at

age 29 and 30, with 12 and 10, respectively. The average income of all respondents is $49,565 per year. The average income for men is $45,136 yearly and the average income for women is $55,814 annually. As Figure 8 illustrates, there are more men that participated in the survey. What stands out is that the average income of all female respondents is much higher than the average income of male respondents – it is a difference of $10,000. The level of education of the respondents differs, but most of them (92) hold a Bachelor’s Degree. The mean of the educational level is 2.61 with a standard deviation of 0.87, which means that it is an educated group of respondents. All respondents are over 18 years old and currently reside in the United States. Overall, the respondents of the survey come from all ages, have different levels of education, and different levels of income, which makes the study representative, as it relates the brand feelings of many different characters – not just a certain group of people.

Demographics Survey Results Number of respondents 216 Gender Male (%) 54 Female (%) 46 Age Min years 19 Max years 74 Mean years 37 Education High School (%) 16 Some College (%) 18 Bachelor’s Degree (%) 56 Master’s Degree (%) 10 Household Income Min Income (USD yearly) 5,000 Max Income (USD yearly 250,000 Mean Income (USD yearly) 49,500

Figure 8: Demographics of the respondents

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5 Love and Hate of Brands 5.1 Hypothesis Testing In order to analyze the brand image and test the validity of the questionnaire, 8 hypotheses are presumed based on assumptions made throughout the creation of this questionnaire. A hypothesis is a statement that is previously assumed but has no evidence to be proven. It is the purpose of further analysis to test those hypotheses. With the help of primary data gained, they describe what is expected, and what the possible outcomes of the survey are. These 8 hypotheses shall be tested with the analysis of the questionnaire and its results. It can then be analyzed whether the hypotheses are true or not. The hypothesis serve a great importance throughout the whole analysis as they give a purpose of each of the analytical points made. The following are the hypothesis and their justification, which will be tested with the results of the final survey: H1: Gender does not influence brand hate.

H2: Age does not influence brand love. H3: Bank of America is the most hated brand out of all U.S. banks. H4: Wells Fargo is the most loved brand among the four major U.S. banks. H5: Household income affects what a customer values about a bank. H6: Customers hate Bank of America’s customer service the most.

H7: People do not like a bank if it performs unethically. H8: Education affects why people hate a brand. 5.2 Brand Awareness Measuring brand awareness of a company is extremely important and relates back to the literature review. It is vital to know if customers recognize a brand and acknowledge it as a differentiation from others because of its products16. A brand name is the key to a successful company with high revenues and profits. This is not only essential for current customers but also for potential clients17. The most vital part of a business like this is customer retention. Therefore, customer service and satisfaction needs to be at the highest level in order to successfully retain customers on a long-term basis. On top of that, customers need to be familiar with a brand and its logo to ensure brand awareness.

!16 http://www.investopedia.com/terms/b/brandawareness.asp 17 http://www.businessdictionary.com/definition/brand-awareness.html

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0% 20% 40% 60% 80% 100%

JP Morgan Chase

Bank of America

Citigroup

Wells Fargo

Familiar or Strongly familiar with brand

Figure 9: Logo familiarity

It was analyzed in Figure 9 by comparing Bank of America to each of the other major three banks in the United States. The question was how familiar the respondents are with each

brand – JP Morgan Chase, Bank of America, Citigroup, and Wells Fargo. Figure 9 illustrates how many respondents are more familiar and less familiar with which brands. For all four brands, there are at least 148 out of the 165 respondents who indicate to be familiar or strongly familiar with the four brands. On the other hand, there were at most 9 respondents who indicated that they are not familiar with any of the brand or not familiar with those brands at all. This shows that

most respondents show a great familiarity with the brands because those are the four major banks and they control 44% of all U.S. banks assets held18. Figure 10 and 11 below show a comparison of Bank of America with all the other banks individually. It also indicates the mean difference, which helps determining if the difference between disliking the banks is significant. The dependent variable is “Like most”. This data was gathered through the use of SPSS by selecting “Compare Means” in the data analysis and using the One-way ANOVA.

Dislike most (I) Dislike most (J) Mean Difference (I-J) Bank of America JP Morgan Chase

Citigroup Wells Fargo

-.122 .103 .775

JP Morgan Chase Citigroup Wells Fargo

.225

.897 Citigroup Wells Fargo .672

Figure 10: Brand comparison: Dislike most !

Like most (I) Like most (J) Mean Difference (I-J) Bank of America JP Morgan Chase

Citigroup Wells Fargo

-.212 .411 .380

JP Morgan Chase Citigroup Wells Fargo

.623

.592 Citigroup Wells Fargo -.031

Figure 11: Brand comparison: Like most

!18 http://www.forbes.com/sites/steveschaefer/2014/12/03/five-biggest-banks-trillion-jpmorgan-citi-bankamerica/

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It is obvious from Figure 10 that there is a statistical significance between respondents who dislike Bank of America and JP Morgan Chase as -.122 is below 0.05. All other comparisons are statistically insignificant as they are above 0.05. This means that there are significantly more people who dislike JP Morgan Chase rather than Bank of America. Exhibit 6 and 7 in the Appendix show the exact numbers as calculated in SPSS. Figure 11 illustrates the same comparison with “Like most” as the variable and “Dislike most” as the dependent variable. The results show that there is a significant difference between people who like Bank of America and JP Morgan Chase, and between Citigroup and Wells Fargo. 5.3 Brand sentiment – Haters and Lovers To get a general feeling of how much the four major U.S. banks are loved or hated, questions three, four, and five of the survey will be analyzed because they refer to brand feeling, possible recommendations, and a ranking of the brands. Figure 12 shows how many of each respondent likes each bank the most. The four major US banks – JP Morgan Chase, Bank of America, Citigroup, and Wells Fargo – were considered. The frequencies amongst the banks are spread out almost evenly for likes, Wells Fargo leading the ranking with 61% likes, followed by JP Morgan Chase (54%), Citigroup (47%), and Bank of America (41%) with the least amount of likes (36). This is a first confirmation of hypothesis 4, which states that Wells Fargo is the most liked bank of all four. Wells Fargo is also the least disliked bank (39%), which is a positive indication for their brand image, closely followed by JP Morgan Chase (46%) and Citigroup (53%). However, Bank of America is the most disliked bank among the major U.S. banks with 59%. This is an indicator that hypothesis 3 is correct as well. Bank of America seems to be the most hated bank among all major U.S. banks. The x-axis indicates each bank and the y-axis the number of people who like or dislike each of the banks.

!Figure 12: Like and Dislike most

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0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

JP Morgan Chase

Bank of America

Citigroup

Wells Fargo

Like most Dislike most

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!5.4 Brand Hate There are a total of 36% of respondents who like Bank of America for different reasons and 56% who dislike Bank of America for the reasons illustrated in Figure 13. Therefore, it is concluded that 8% respondents do not have a positive nor negative opinion about the brand. A ratio of 92:60 – or approximately 1.5:1 – indicated that there are 50% more respondents who dislike bank of America than like it. The five most mentioned things customers like about Bank of America.

Reasons for Like Frequency (%) Reasons for Dislike Frequency (%) Customer Service 65 High fees 33 Location 18 Customer Service 27 Reliability 8 Abiding the law 21 Fees 6 Brand image 14 Brand Image 3 Location 5

Figure 13: Reasons for Like/ Dislike Bank of America

The following word cloud illustrates the main reasons why people hate or dislike Bank of America based on the comments they made in the questionnaire.19 The bigger the word, the more often it was mentioned during the course of answering the questionnaire. It stands out that customer service, high fees charged, convenience, and online banking was important in determining whether a customer dislikes a certain bank.

!Figure 14: Word Cloud reasons for hate

!19 https://www.jasondavies.com/wordcloud/#

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!To illustrate in even more detail what customers dislike or hate about a certain bank, some of their quotes were taken out directly from the questionnaire. Many of those were negative, and the two most negative ones – high fees and customer service – confirm that hypothesis 4 is true. Hypothesis 6 is also confirmed, as customer service is by far the biggest of all the negative words, which implicates that it is the traits about Bank of America that customers like least. The following are some of the comments from respondents to show what exactly they said. “I guess I don't like it because it's so big and impersonal.” This is an issue that many corporate organizations face, but it is hard to resolve. Many respondents stated also that they “dislike that it has so many banking fees both for domestic and foreign transaction. They are infamous hoarders.” Many harsh words were used when describing Bank of America’s fees, because they seem to be too high. Somebody else stated “Fees are higher than other banks I've held accounts in.” Many customers also blame Bank of America and the other major four U.S banks to be a “Large part of the system that is destroying the banking system of the US.” The financial crisis of 2008/2009 has impacted many people’s lives and employment negatively and big banks are often blamed for that. Relating this to hypothesis 1, it was tested in SPSS if brand hate is gender related and in reverse. For hypothesis 2, it was tested if age has any influence on brand love and the same test in reverse. Both hypotheses were confirmed based on the following data. ANOVA (Dependent) Variable Statistical Significance Brand hate towards all four banks Gender .863 Brand love towards all four banks Gender .844 Brand hate towards all four banks Age .944 Brand love towards all four banks Age .754

Figure 15: Brand hate compared to

None of the values are below 0.05 in terms of statistical significance so none of the differences between brand hate towards all four major U.S. banks and age or gender are significant. This confirms and satisfies both, hypothesis 1 and hypothesis 2, stating that gender and age have no influence on either hate or love towards a brand. This was assumed because the sentiment towards a brand should generally be based on unbiased factors, such as customer service, price, quality, and overall satisfaction. However, the brand image also plays an important role and the purpose of this study was to assess if age and gender – two very useful points of demographic data – have an influence on that. The fact that both of them do not have any influence at all is significant for all further results in this study. 5.5 Brand Love Many of the 36% of respondents who indicated that they like Bank of America commented about their experiences and why they like the bank. Their comments give a detailed insight into the positive traits of the bank. In order to give an overview about those comments, a word cloud20 was created with their main positive attributes. The words that stand out from this word cloud are mortgages, online banking, availability, fees, reliability, value, and interest rates. The overall sentiment towards the brand image is rather negative than positive. There are many factors that appear on both, the hate and the love site, such as


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customer service and fees. This could be due to the region in which the bank operates or the specific branch. Many other factors come into play when doing an analysis like this. Issues like the customers’ personality, current mood, financial situation, stress level, and many more need to be considered in such an evaluation.

!Figure 16: Word Cloud reasons for love

To take a deeper look into what customers like about the bank, some main comments were chosen. One customer stated: “I liked it when I was a customer because they treated me right and helped with my first car loan.” Therefore, it can be concluded that there were also some positive experiences with customer service at Bank of America. This often depends on the region as well. Customers also seemed to like the “User interface” because it “is very accessible on website and mobile phone”. This respondent perceived an overall positive brand image: “Seems like a solid company and I have never heard anything bad about them around my hometown.” Customers also like low fees, and the banks’ honesty: “They seem honest and I've heard they have great programs and low fees”. Some customers have positive aspects to mention, but see negatives as well:!“They offer a wide variety of services, but at the same time I have heard some negative things about them.” Overall, it can be stated that the sentiment from those comments is rather negative than positive, although some factors like customer service, fees, and safety were mentioned on both sides.

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5.6 Bank comparison As an extension to previous analysis, a possible recommendation was compared to age and gender in order to further analyze the brand sentiment towards Bank of America. Possible Recommendation vs. Age

Statistical significance

Possible Recommendation vs. Gender

Statistical significance

JP Morgan Chase .822 JP Morgan Chase .339 Bank of America .072 Bank of America .398 Citigroup .709 Citigroup .761 Wells Fargo .951 Wells Fargo .613 Figure 17: ANOVA – Possible recommendation vs. Age/Gender

As the significance values in Figure 17 show, neither of the two variables have significance below 0.05 when compared to gender in the ANOVA matrix. This means that gender does not have an influence on a possible recommendation of any of the four major U.S. banks. To determine what is most important for customers as clients of a bank, respondents were asked to indicate what is most important for them. Figure 18 shows from a rank of 1 through 5 how important each of the traits is to the respondents. They are illustrated in just three groups, as 1 and two were grouped together and 4 and 5 were grouped together as well. Therefore, 1 stands for “Very important” and “Important”, 2 stand for “Neutral”, and 3 stands for “Not important” and “Not important at all”. The x-axis simply shows the number of people who indicated each of the answers.

!Figure 18: Important traits of bank

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Customer Service

Financial services

Loans/ Mortgage

Convenience

Manageable Fees

Security/ Accessibility

Not important Neutral Important

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The results of this analysis clearly show that four of those six factors are more important than the other two. Security and accessibility of savings, manageable fees, convenience, and customer service appear to be more important than the quality of loans and mortgages and financial services. There are significantly more people (150, 156, 154, and 160, respectively) who rated the values mentioned above as “4” and “5”. The higher those ratings are, the lower the “3’s”, which represent neutral and the lower also the “1’s” and “2’s”. Further analysis focuses on brand hate and its origin. The questions in the survey relate to brand hate in general at first and try to find reasons for that. As mentioned in the literature review, brand hate is a serious problem for major companies, especially for banks. Bank of America has experienced major forms of brand hate such has a Bank of America hate website21 with many negative customer reviews as well as a Bank of America hate song on YouTube. Company executives are extremely concerned about such negative developments for their brand image. Therefore, it is vital to find out more about the reasons and origins of this hate in order to prevent further problems and resolve potential issues. Figure 19 illustrates the different reasons for brand hate that were selected by customers for brand hate. For this graph, “Strongly Agree” and “Agree” were grouped together as “1” in the dark blue color. Neutral is represented by number “2” in green; “Strongly Disagree” and “Agree” were grouped together as “3” in red.

!Figure 19: Reasons for Brand Hate

What stands out right away from Figure 19 is that almost all respondents agree or strongly agree that negative past experiences are a legitimate reason for brand hate. This could be an indication that many of those people have had negative past experiences with their banks before. Identification issues seem to be less of a problem for the respondents, as well as

!21 http://www.ihatebankofamerica.com/

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Negative past experiences

Identification issues

Poor values

Unethical market behavior

Violation of rules

Disagree Neutral Agree

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violations of rules. Unethical market behavior and poor values of a bank are right in between. The more people agree or strongly agree, the less disagree or strongly disagree. To find out what consequences brand-hate causes, respondents were asked for their opinion in Figure 20.

!Figure 20: Consequences of brand hate

As Figure 20 shows, only 52% of all respondents agree or strongly agree that brand hate causes retaliation, but the majority agrees or strongly agrees that brand hate causes avoidance of a certain brand and negative word of mouth about that brand. The more the respondents agree or strongly agree with both of these consequences, the less they disagree with the other factors. Retaliation is spread out to 43% of respondents who agree or strongly agree, 27% who are neutral, and 30% who disagree. 84% agree that it causes negative word of mouth and 82% agree for brand avoidance.

5.7 Influence of Income and Education As part of the reasons for brand hate analysis, it was analyzed if income had a significant impact on why people hate brands with the help of an ANOVA matrix. This relates back to hypothesis 5. Hypothesis 5 ended up being rejected because as Figure 21 shows, household income has no statistical effect on why people hate brands. This was previously assumed to be the case because different levels of income could potentially influence the financial issues and problems one experiences with a bank and therefore trigger many different reasons why people hate certain brands.

!ANOVA (Dependent) Variable Statistical Significance Brand hate because of negative experiences Household Income .730 Brand hate because of identification issues Household Income .955 Brand hate because of poor values Household Income .781 Brand hate because of unethical behavior Household Income .620 Brand hate because of violation of rules Household Income .702

Figure 21: Brand hate reasons vs. Household Income

In most households, mostly males do banking for the whole family. Females who take on the financials are rare in families but have to perform that role when they are single. A new

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Avoidance of brands

Negative word of mouth

Retaliation

Disagree Neutral Agree

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trend even states that women start to take over finances from men22. However, income spread between men and women has shown no differences either. Another analysis was done with the educational level of the respondents. ANOVA (Dependent) Variable Statistical Significance Brand hate because of negative experiences Level of Education .668 Brand hate because of identification issues Level of Education .499 Brand hate because of poor values Level of Education .309 Brand hate because of unethical behavior Level of Education .240 Brand hate because of violation of rules Level of Education .864

Figure 22: Brand hate reasons vs. Level of education As Figure 22 shows, there is no significant statistical difference between those results. Therefore, the level of education does not influence why people hate a band. Based on this analysis, hypothesis 8, stating that education has a significant influence on why people hate a brand, is rejected. Education from all different levels is not relevant in terms of brand hate. If people are less educated, they can still understand the main issues that a brands and its service have. More educated people might be able to grasp the mechanisms behind this failure but the general understanding of identification issues, negative past experiences, poor values, unethical behavior, and the violation of rules are not a part of that. People that are less educated – with for example a high school degree or just some college classes taken – can understand all these problems. 5.8 Unethical Behavior Furthermore, it was determined whether there is a correlation between unethical behaviors of a bank and if people hate that brand. This is important to know and understand because if a customer thinks that a bank behaves unethically, he or she should not like the brand. This is a logical conclusion, which is important to test in this analysis. Figure 23 illustrates the comparison of people who indicated that they agree or strongly agree about hating banks because of unethical behavior and liking or disliking them. ANOVA (Dependent) Variable Statistical Significance Brand hate because of unethical behavior Dislike most .059 Brand hate because of unethical behavior Like most .320

Figure 23: Unethical behavior and brand hate/ love

As the values show, none of the correlations form the Anova is below 0.05, and therefore there is no significant difference between those variables. This means that hypothesis 7 is confirmed. People do not like a bank if it performs unethically. This is a logical conclusion that was assumed before as well. 5.9 Possible Improvements Lastly, respondents were asked for suggestions for Bank of America to improve their brand image in an open-ended question. This is an important part of the survey as it gives the respondent the opportunity to display their open opinion about a brand and is open to

!22 http://www.gobankingrates.com/personal-finance/women-taking-over-family-finances-men/

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possible improvement suggestions. The word cloud below shows suggestions of respondents to improve the brand image of Bank of America followed by actual quotes of the respondents.23 The main suggestions are based on better customer service, lower fees, and working on its overall brand image by being more transparent, honest, and less greedy.

!Figure 24: Word Cloud improve suggestions

Some of the comments as quoted from respondents present what exactly they suggested as improvements for Bank of America’s brand image. “More transparency and accountability” was often asked for, which is an important suggestion for Bank of America’s brand image. This was often criticized in the past, especially during the financial crisis of 2008/2009. The following was a very interesting approach for the bank as well: “It could offer products that are targeted to the younger demographic.” By changing the variety of the financial products targeted towards a younger part of the population, the brand image can be improved and a new customer base can be gained. One of the most important suggestions, which relates to the problem that was mentioned the most by respondents is to “Lower fees and improve customer service.” Many of the complaints on hate websites, the YouTube song, as well as responses from this survey are based on bad customer service and high fees. This is probably one of the hardest issues to improve because of budget restraints, but customer service could definitely be improved by professional training. To improve the overall brand image within the society, a reasonable suggestion was made: “Associate itself with sports and charitable organizations.” By doing that, people will be able to associate Bank of America with something positive instead of negative. This idea ties into another important suggestion, which is to “Be respectful and honest to customers.” By assuring this, Bank of America would create an ultimate image booster for itself. However, this is a timely process, which can take decades of hard work and honest determination.


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6 Conclusions From the results for the survey – presented in section 5 of this research paper – many conclusions can be drawn. At first, it stands out that age and gender do not have an impact on any of the significant statistics analyzed. Overall, demographic data – such as level of education and household income – does not have a very big influence on the statistics that were analyzed in this project. During the research, it came up that there is an overall negative sentiment against Bank of America and the banking industry in general. This is mainly due to the financial crisis of 2008/2009 and movements such as “Occupy Wall Street”. Customers have a sentiment that banks are greedy organizations trying to take money away from their clients. The sentiment – taken from the results of the survey – was that Bank of America is the most hated bank out of the four major U.S. banks (JP Morgan Chase, Bank of America, Citigroup, and Wells Fargo). It appears from their comments that customers hate or do not like the bad customer service, high fees, unethical behavior of the bank, and exorbitant charges relating to fraud. As opposed to this brand hate, respondents like Wells Fargo the most out of all four banks. It was determined from further analysis that customers have had negative past experiences with the brand and think that Bank of America has poor values because of their unethical market behavior. For Bank of America, this is a very serious problem, which needs to be solved as soon as possible. Most of them believe that this can cause negative word of mouth and brand avoidance as opposed to active retaliation. Those serious consequences need to be avoided at all costs. Customers were asked for possible suggestions to improve their brand image. The main suggestions were to lower their fees, improve customer service, and be more honest. Those are very fundamental principles that should be followed by any company and are deeply rooted in the groundwork of an organization. Therefore, it is a complex and lengthy process to change and work on those principles. It has to happen over time and be implemented carefully. The brand report gives detailed insight into what respondents and customers recommended and bases actual recommendation off of that. Bank of America needs to implement strict employee training and further actions in order to improve its customer service. On top of that, it was mentioned to associate itself with popular sports teams and charity events. This could help Bank of America to create a better brand image and a more approachable brand name. Also, it was stated to create a younger perception of the brand in order to attract a younger generation of clients. This could help changing the overall brand image as well. Generally, it can be said that Bank of America needs to take serious and fast actions in order to avoid further brand hate and contain current negative sentiments towards its brand. It is evident that brand hate affects their profit and revenue streams. Therefore, it should be the companies’ executives’ top priority to address this issue as fast as possible.

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References Barker, Ryan, Jeffrey Peacock, and Marc Fetscherin. "The Power of Brand Love." International Journal of Market Research Int. J. Market Res. 57 (2015): 669. Print. Brown, Tom J., and Gilbert A. Churchill. Basic Marketing Research: Customer Insights and Managerial Action. 8th ed. Stamford: CENGAGE Learning, 2014. Print. Heinrich, Daniel. "Consumer-Brand Relationships."!Macmillan Publishers Ltd 21.5 (2014): 366-71. Print. Kucuk, S Umit. "Negative Double Jeopardy: The Role of Anti-brand Sites on the Internet." J Brand Management Journal of Brand Management 15 (2007): 209-22.

Print. McLellan, Drew. "Someone Has to Hate Your Brand." WordofMouth.org. 10 Sept. 2014. Web. 20 Nov. 2015. Mulvey, Jeanette. "Consumers Have Humanlike Relationships with Brands." Business News Daily. 10 July 2012. Web. 20 Nov. 2015. Romani, Simona, Silvia Grappi, and Daniele Dalli. "Emotions That Drive Consumers Away from Brands: Measuring Negative Emotions toward Brands and Their Behavioral Effects." International Journal of Research in Marketing (2011): 55-67. Print.

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Appendix Exhibit 1: Codebook

# of Q Question Label Purpose

V1 Finished 1 = “Yes” 2 = “No”

- Survey was terminated by respondent

Q1 You are invited to participate in a brief anonymous survey on your experience with financial brands. To participate, you must be over 18 years old and live in the U.S. Please provide answers that best reflect your opinion and feelings. It should take about 5 minutes to complete. You can terminate the survey anytime. Your participation is greatly appreciated. By clicking 'Agree' you affirm to participate in this study.

1 = “Yes” 2 = “No”

- Make sure the respondents agree on participating in the survey to the conditions mentioned - Inform about length, conditions, and can terminate the survey at all times!

Q23_2 – Q23_5

To what extent do you agree or disagree with the following statement? I am familiar with the following logos.

1 = “Strongly Disagree” 2 = “Disagree” 3 = “Neither Agree nor Disagree” 4 = “Agree” 5 = “Strongly Agree”

- Illustrate what brands are in the survey and what they are all about - Find out how familiar respondents are with the brand/ brand awareness and logo recognition!

Q29_1 – Q29_4

How do you feel about the following brands?

1 = “Hate” 2 = “Dislike” 3 = “Neither” 4 = “Like” 5 = “Love”

- First impression how people think about the brands - Determine lovers and haters - Determine hate and love in the industry!

Q11_1 – Q11_4

How likely are you to recommend the following brands to colleagues or friends?

1 = “Very unlikely” 2 = “Unlikely” 3 = “Neutral” 4 = “Likely” 5 = “Very Likely”

- Find out if there is a correlation between brand hate/ love and recommendations to colleagues/ friends!

Q16_1 – Q16_2

Which of the following brands do you like or dislike the most?

1 = “JP Morgan Chase” 2 = “Bank of America” 3 = “Citigroup” 4 = “Wells Fargo”

- Force respondents to determine which brand they like and dislike the most!

Q9_1 – Q9_6

How important are the following services of a bank to you?

1 = “Not important at all” 2 = “Not important” 3 = “Neutral” 4 = “Important” 5 = “Very Important”

- Determine what services are most important for customers to have in a bank - Later on compare to Bank of America!

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Q7_1 – Q7_5

To what extent do you agree or disagree with the following statement? People hate banks because of...


- Find out why people hate or love financial institutions in general - Relate the reasons for bank hate to Bank of America and its competitors!

Q12_1 – Q12_3

To what extent do you agree or disagree with the following statement? Brand hate can cause...


- Explore what respondents could imagine as a possible result of brand hate - Consequences for Bank of America!

Q13 Are you a customer of Bank of America?

1 = “Existing customer” 2 = “Past customer (not using Bank of America anymore)” 3 = “Never a customer”

- Find out if the respondent is a customer of Bank of America, which would make him/her more representative

Q28 What do you like or dislike about Bank of America?

Open-ended - Open-ended question to determine why people love or hate Bank of America

Q10_1 – Q10_6

To what extent do you agree or disagree with the following statement? Bank of America possesses...


- Relate the characteristics and strengths of a bank to Bank of America and see if the bank possesses them!

Q33_1 – Q33_6

How strongly do you think Bank of America maintains the following values?

1 = “Strongly Disagree” 2 = “Disagree” 3 = “Somewhat Disagree” 4 = “Neither Agree nor Disagree” 5 = “Somewhat Agree” 6 = “Agree” 7 = “Strongly Agree”

- On a scale, this question determines how much respondents think if Bank of America possesses certain values or not!

Q12 What could Bank of America do to improve its brand image?

Open-ended - Open-ended question for suggestions by respondents

Q17_1_1_TEXT

Please indicate your age. Number - Basic demographic data about respondents!

Q17_2_1_TEXT

Please indicate your gender. 1 = “Male” 2 = “Female”

- Basic demographic data about respondents!

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Q18_1_1_TEXT

Please indicate your household income.

Number - Basic demographic data about respondents!

Q18_2_1_TEXT

Please indicate your level of education.

1 = “High School” 2 = “Some College” 3 = “Bachelor’s Degree” 4 = “Master Degree”

- Basic demographic data about respondents!

Source: Author Exhibit 2: Opinions about the Bank of America

Source: Yougov

!Exhibit 3: JP Morgan Chase vs. Bank of America

Source: Author, SPSS

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Exhibit 4: Citigroup vs. Bank of America

Source: Author, SPSS Exhibit 5: Wells Fargo vs. Bank of America


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Exhibit 6: Mean difference Bank of America vs. all other banks

Source: Author, SPSS Exhibit 7: Mean difference Bank of America vs. all other banks


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Exhibit 8: Hate/ Love vs. Age/ Gender

Source: Author, SPSS Exhibit 9: Hate/ Love vs. Age/ Gender


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Exhibit 10: Brand hate/love vs. Like/Dislike

Source: Author, SPSS Exhibit 11: Anova Brand Hate and Household Income


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Exhibit 12: Anova Brand Hate and Level of Education


bank of america - final

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