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Exploring Connections Between Social Media and Fast Food Marketing Research By: Kira Jordan, Jenny Hua, and Lydia Drakeford

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Page 1: Marketing Research Presentation (1)

Exploring Connections Between Social Media and

Fast Food Marketing Research

By: Kira Jordan, Jenny Hua, and Lydia Drakeford 

Page 2: Marketing Research Presentation (1)

Overall Research TopicGeneral Issue:

• Explore company responses to customer comments • Complaints vs. Compliments

• The study specifically focused on responses from fast food companies. 

Page 3: Marketing Research Presentation (1)

Specific Research Questions 

1.  Does the social media platform (Facebook vs. Twitter) a comment is submitted on impact a company's response time and/or their response quality? 2. Does the nature of the comment (Positive vs. Negative) submitted affect a company's response time and/or their response quality? 3. Is there a relationship between the amount of followers a company has and the company's response time and/or their response quality? 

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Relevant Literature 

• Companies respond more often on Facebook than Twitter. 

• Companies are more likely to respond to negative reviews.  

• There is not a significant relationship between company popularity on social media sites and response quality. 

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Methodology: Sample 

Population: U.S. based chain fast food

restaurants (not cuisine specific)   Sample: 

27 Fast Food Restaurants with both Facebook and Twitter accounts 

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Methodology: Data Collection 

• 108 total comments distributed. Each company received 4 total: • Twitter positive• Twitter negative• Facebook positive • Facebook negative

• Timeline: Tuesday from 8 am to 11 am

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Message Content

• Negative: "“I had a less than positive time at one of your locations today. Unfortunately, the food was subpar to my expectations and the normal standard for your restaurant. Also, the service was slow and I felt undervalued as a customer. I typically enjoy your restaurant but this makes me question ever coming back again.”

• Positive

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Rubric for Company Responses

• 1st Factor: Speed• Ordinal Scale (0-10) for

response time• 10: 0-2 hours• 1: 48 + hours• 0: Never responded 

• 2nd Factor: Quality • Word Count: Ratio Scale• 5 categories on Interval

Scale: Personalization, Future Action, Willingness, Accuracy, and Helpfulness

• 3rd Factor: Follower count• Ordinal Scale (1-5) 

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The Results 

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Response Time Comparison  

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Question: Is there a significant difference in responses from companies when comparing

positive and negative comments? 

1. Comparison of response times for positive vs. negative 

• Test: Paired Samples T-test 

• Variables: Response Time (TP and FP) vs. Response Time (TN and FN) 

• Analysis: No significant difference

2. Comparison of quality of responses for positive vs. Negative

• Analysis: No significant difference 

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Question: Is there a significant difference in responses from companies on Facebook vs.

Twitter? 

1. Time Comparison- Not Significant 

2. Response Length Comparison- Significant (Word Count) 

3. Quality Comparison

• Test: Paired Samples T-test 

• Variables: All quality variables (Twitter vs. Facebook) 

• Analysis: Significant (below .05) differences highlighted in blue

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Question: Is there a significant relationship between the number of social media followers a company

has and their responses? 

1. Twitter Comparison 

• Test: Bivariate Correlation

• Variables: Follower Count compared to all other variables 

• Analysis: No significant correlation between follower count and any other variable on Twitter

2. Facebook Comparison 

Page 14: Marketing Research Presentation (1)

Conclusions 

Page 15: Marketing Research Presentation (1)

Summary of Conclusions  

1. The results indicate that negative Facebook posts get higher quality responses from companies than both positive Facebook posts & positive Twitter posts.2. The likelihood of receiving a Facebook response was much higher than receiving a Twitter response3. Absolutely no correlation between follower count and response quality (no matter platform or nature of comment) 

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Limitations 

• Familiarity of username • Non-response bias • Timing • Zoning differences • Business Hours