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Brand Strategy and Super Bowl Twitter Analytics Lab

Details: Brand Strategy and Super Bowl Twitter Analytics Lab

Image Source: Adweek.com

INTRODUCTION

2

Twitter popularity as 2nd screen

Infographic Source: Fortune, 2015

About Twitter

4

Twitter Stats (cont’d)

5

About Super Bowl Ads

6

Motivation • Cost per 30 seconds slot – 5 mil (CNNMoney, 2017). • Brand strategy in Super Bowl ads? Enhance &

reach. • The role of IS tools in this strategy?

– Analytics of audience (demographics, locations etc.). – Supplementary info for future decision making.

• What is the relationship between Social Media buzz around Super Bowl ads with ad ratings? – Twitter activities surrounding SB ads with USA Today

Index ratings (USA Today)?

http://admeter.usatoday.com/

3 Tweet Examples Those Budweiser commercials had me balling my eyes out!! #Budweiser #SuperBowl #horsepuppy #tearjerker

Thanks #CocaCola & #Cheerios for showing U.S. multicultural families and successfully including diverse markets #adbowl #AmericaIsBeautiful

Scarlett Johansson should realize that the only real flavor of #SodaStream is oppression http://t.co/QLpDD7vkXA #superbowl

Objective • Learn to extract valuable metrics from social

media data using MS Excel. • Know what insights are valuable to brands. • Simple introduction to (review on) descriptive

statistics, correlation, charts, regressions, and word clouds.

• Lab instructions become more vague as lab progresses to encourage student self learning.

9

Lab Setup • Download this presentation and watch VIDEO. • Download the SB 2014 spreadsheet — This is a

summary of actual tweets *downloaded using PHP and MySQL scripts (done prior).

• Download the doritos.txt tweet text file*. • You will need MS Excel with Data Analysis

ToolPak available. • Prepare a Word doc for submission.

Research Question • Start with research question:

– Is social media (Twitter) an effective tool for measuring brand performance (SB ads)?

• How? – Find a relationship between Twitter metrics and SB

performance. – If a relationship exists then social media may be a

valuable (real time, low cost) monitoring mechanism in addition to existing tools.

– In addition, social media provides rich feedback (WOM, influencer, competitors, etc.).

ANALYSIS

12

Analysis 1. Descriptive Statistics 2. Correlation Analysis 3. Charts (Bar chart and scatter plot) 4. OLS Regression 5. Word Cloud

SB 2014* Dataset

• Super Bowl 2014 Ads • 51 Ads • Contains social media measures and USA

Today index for each ad. • Measures extracted from downloading and

analyzing tweets for each ad.

*Seattle Seahawks beat Denver Broncos (43-8) 14

Dataset

15

Variables • USA Index – Super Bowl ad performance index from

USA Today. This is the outcome variable. • RT –retweets for each ad. • Tweet Count – tweets for each ad. • Unique sender – count of people talking about the

ad. • Pre-release – (1/0) whether this ad was release

before the Super Bowl game. • Celebrity – (1/0) whether a celebrity(s) is in the ad.

16

Descriptive Statistics 1. Open SB 2014 spreadsheet in Excel 2. Go to Data > Data Analysis > Descriptive Analysis 3. For the Input Range, highlight all the number cells

(including labels) but excluding Ad Name and brand columns.

Descriptive Statistics 4. Select ‘labels in first row’ and ‘summary

statistics’

Descriptive Statistics 5. Results appear in next Sheet. 6. Copy Result to Word doc.

Descriptive Statistics 7. Discuss result. Focus on average, min, max

for: – USA Index – Tweet count – Unique sender – RT

Correlation Analysis 1. Select Correlation then OK.

2. In the Correlation window, make sure all number cells are selected then click OK.

Correlation Analysis 3. Results will appear in next Sheet. 4. Discuss which variables are highly correlated. Why? 5. Copy Result to Word doc.

Bar Chart • Select the tweet count column and sort by largest to

smallest.

Bar Chart • Insert a Bar chart of ‘tweet count’ and ‘ad names’.

Discuss what you found. • Add to Word doc.

Scatter Plot • Do a Scatter Plot of ‘Tweet count with USA Index’

and discuss. Add the trend line. What does the trend imply? Add to Word doc.

What is OLS linear regression? • OLS Linear regression is the most basic and

commonly used predictive analysis. Regression estimates are used to describe data and to explain the relationship between one dependent variable (y) and one or more independent variables (x).

• At the center of the regression analysis is the task of fitting a single line through a scatter plot. The simplest form with one dependent and one independent variable is defined by the formula y = a + b*x. 26

1. Select Data Analysis and run regression. 2. Select USA Index for Y Range and all others (except

ad name, brand, and USA Index) for X Range. Select labels and confidence level at 95%. Then click OK.

OLS Regression (USA Index)

3. Copy to Word doc. OLS Regression (USA Index)

4. What to report? – Adjusted R-squared – Variables with p value < .10 (only unique senders)

5. Discuss Results. What variables can explain Y? You are expected to use your knowledge from your stats class here. What can you imply from this result?

OLS Regression (USA Index)

Word Cloud 1. Go to http://www.wordclouds.com/ 2. Click File->Open text file 3. Upload the ‘doritos’ tweet text file.

http://www.wordclouds.com/

Word Cloud 1. The word cloud for ‘doritos’ should appear

(see pic to the right). 2. Discuss word cloud. 3. Why are certain terms

more frequently used? 4. How can doritos use this

strategically?

Summary Paragraph • Write a summary paragraph for lab. • Describe what you have learned. • What IS tools are used? • How does this lab help you to understand the

relationship between organizational strategy and IS tools?

• How can these tools/techniques help with decision making?

• Can this be applied in your future career? 32

SUBMISSION

33

Lab Submission • In a Word doc, insert the following:

1. Descriptive Statistics 2. Correlation 3. 2 Charts (Bar Chart and Scatter Plot) 4. Regression Result 5. Word Cloud 6. Summary paragraph

• Organize well to help easier grading == higher scores. • Submit on canvas

END

  • Brand Strategy and Super Bowl Twitter Analytics Lab
  • introduction
  • Twitter popularity as 2nd screen
  • About Twitter
  • Twitter Stats (cont’d)
  • About Super Bowl Ads
  • Motivation
  • 3 Tweet Examples
  • Objective
  • Lab Setup
  • Research Question
  • analysis
  • Analysis
  • SB 2014* Dataset
  • Dataset
  • Variables
  • Descriptive Statistics
  • Descriptive Statistics
  • Descriptive Statistics
  • Descriptive Statistics
  • Correlation Analysis
  • Correlation Analysis
  • Bar Chart
  • Bar Chart
  • Scatter Plot
  • What is OLS linear regression?
  • OLS Regression (USA Index)
  • OLS Regression (USA Index)
  • OLS Regression (USA Index)
  • Word Cloud
  • Word Cloud
  • Summary Paragraph
  • submission
  • Lab Submission
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big data analytics brings to light several possibilities where errors may exist in data due to noise

The article in this week’s readings regarding uncertainty in big data analytics brings to light several possibilities where errors may exist in data due to noise, incompleteness, or inconsistency. Considering the market basket approach presented in Chapter Three of the course text, write a 2-3 page, APA 7th edition-formatted paper discussing where potential errors or ethical challenges may exist in data gathered and used for marketing purposes. For example, in 2012, Target’s data analytics discovered that a teen girl was pregnant before her family knew based on purchase history and began sending related advertisements. Identify 2-3 ethical and legal issues surrounding the collection of consumer data and consumer privacy. How might these issues impact areas such as diversity, equity, inclusion, or targeting of social groups? Address what steps a business may take to clean their data or reduce inconsistencies.

with reference and citation 

no question and answer formatChaudhary, K., & Alam, M. (2022). Big data analytics applications in business and marketing.

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portfolio of analytics methods used of accounting, economics or finance

Create a slide deck which represents a portfolio of analytics methods used of accounting, economics or finance. This task is to be done as an individual. 16 slides, total 30 marks.

Assessment Description

You will discuss below five analytics methods and a financial or accounting or economics application for each one.

· Association rule learning · Classification tree analysis · Genetic algorithms · Machine learning · Regression analysis • Out of the five methods that you chose, investigate one in more detail. • Reflect on the limitations of the methods and possible ethical, legal or privacy issues. Please refer to the assessment marking guide to assist you in completing all the assessment criteria. Slide format should be as follows: • Title, student name and ID [1 slide] • Discuss any 4 analytics methods from above. Create one slide for each analytics method and one for its application in accounting or finance or economics. [8 slides, 16 marks] • Discuss the remaining 1 Analytics method in detail and create three slides for the analytics method and one slide for its application in accounting or economics or finance [4 slides, 8 marks] • Reflect and list the limitations of the 5 analytics methods [1 slides, 2 marks] • Discuss in short sentences possible ethical, legal and privacy issues. Please refer to lecture slide week 11. [2 slides, 4 marks]

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A real-world business problem as it presents the case of AUDI AG and its attempts to implement big data analytics in its organization

The attached pdf file introduces a real-world business problem as it presents the case of AUDI AG and its attempts to implement big data analytics in its organization.

For your first individual case analysis, you need to critically analyze this case study, summarize the key idea, discuss the IT challenges and present your recommendations. This analysis should be done individually not in groups, so each student should do the analysis by themselves.

This report will be organized as follows:

1.       Introduction – Short summary of the business problem. This section will also include a background of the organization.

2.       Challenges – Provide for a brief description of the challenges that the organization is facing and how they are planning to address them. This section will provide the audience with a picture of how the organization is planning to address some of the challenges.

3.       Change Management – Discuss how change is being managed by the organization. 

4.       Recommendations – Discuss what you would have done differently and why.

5.       Conclusions – Discuss the lessons learned and the key messages that you would like the audience to take away.

The report should not be more than 1000 words

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How is data analytics different from statistics?

explain the role that analytics plays in the modern business environment. Consider the following questions and respond in a minimum of 175 words:

  • How is data analytics different from statistics?
  • Analytics tools fall into 3 categories:descriptive, predictive, and prescriptive. What are the main differences among these categories?
  • Explain how businesses use analytics to convert raw operational data into actionable information. Provide at least 1 example.
  • Consider the organization you work for (or another organization you’re familiar with). Does this organization use data analytics?If so, how is it used? If not, how could the organization use data analytics to improve its performance?

Due Day 7

Reply to at least 2 of your classmates or your faculty member and or respond to the following subjects.

  1. Identify and define the three measures of Central Tendency and explain when we may use them.
  2. Identify and define the measures of dispersion and explain why they are used.
  3. What does a box plot tell us? How is this related to the 5 number summary?
  4. What does a histogram tell us? What does it not tell us?
  5. Explain the difference between an asymmetrical (skewed) distribution and a symmetrical (normal) distribution. Why is it important to identify the type of distribution we are working with?

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Big Data Analytics Challenges and Ways to Address Them

Write a minimum of 3 pages article on the topic: “Big Data Analytics Challenges and Ways to Address Them”.

Your article should encompass the following details:

  • At least 3 major challenges associated with big data analytics
  • Potential solutions for each challenge you identified

Your submission should include:

  • Make sure you follow APA 7thformatting and citation procedures in your work. See the attached APA 7 template.
  • Include the following sections:
  • Cover page
  • Introduction
  • Discussion
  • Conclusion
  • Properly cite at least 4 scholarly articles (2 of the articles must be published 2017 or later).

(You can use a web reference in addition to the 4 scholarly articles).

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How do analytics play a role in health care? Describe a scenario in which analytics could be used to improve patient safety and increase revenue

  • How do analytics play a role in health care? Describe a scenario in which analytics could be used to improve patient safety and increase revenue.
  • Use analytics to determine how the quality of care could be improved, while keeping costs low. How can analytics be valuable when you want to calculate the length of stay (LOS)?
  • Provide other examples of uses of analytics.

 Note: Use APA style and 5 scholarly references within 5 years. 6-7 pages (excluding title page and reference page) 

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CIOInsight entitled ‘How Analytics Saved Sunny Delight $1M

Read the following two articles:

Write a 2 page double-spaced paper (no need to follow any writing format such as MLA or APA) addressing the following questions:

  • Is it surprising that a small company such as Sunny Delight could end up with so many different analytics tools? 
  • How did Sunny Delight end up with so many analytics tools?
  • What are the trade-offs of moving to an enterprise-level analytics solution for individual employees who may have grown accustomed to working with their own customized solutions for generating data?
  • Gartner reported that most businesses will have access to some sort of self-service BI tool within the next few years. However Gartner estimated that less than 10% will have sufficient data governance practices in place to prevent data inconsistencies across the organization. Why do you think so many companies invest in BI solutions while ignoring governance programs to ensure data consistency?

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Why do you want to participate in the apprenticeship program, and particularly what are your interests in your preferred data analytics path?

Please keep total response word count to 500 words

  • Why do you want to participate in the apprenticeship program, and particularly what are your interests in your preferred data analytics path?
  • Tell us about a time in which you’ve seen data being used in a creative way and explain why this was inspiring to you.

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How does prescriptive analytics relate to descriptive and predictive analytics?

1. How does prescriptive analytics relate to descriptive and predictive analytics?

2. Explain the differences between static and dynamic models. How can one evolve into the other?

3. What is the difference between an optimistic approach and a pessimistic approach to decision making under assumed uncertainty?

4. Explain why solving problems under uncertainty some-times involves assuming that the problem is to be solved under conditions of risk.

5. Investigate via a Web search how models and their solutions are used by the U.S. Department of Homeland Security in the “war against terrorism.” Also investigate how other governments or government agencies are using models in their missions.

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    • Original and non-plagiarized custom papers. Our writers develop their writing from scratch unless you request them to rewrite, edit or proofread your paper.
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