MATH 810 Applied Statistics Project III: Marketing & Adverti

MATH 810 APPLIED STATISTICS PROJECT III: MARKETING & ADVERTISING ANALYSIS

You are the regional marketing vice president overseeing all US marketing for an international pharmaceutical distributor. Your team has recently submitted a proposed budget for advertising and marketing spend for the upcoming year to support 10% annual revenue growth for your company’s best-selling product Dilomatox. A summary of that budget along with this year’s forecasted data (forecasted since your fiscal year isn’t quite complete yet) is below: DILOMATOX – Proposed Marketing Budget Proposed Budget (Next Year) Current Forecast (This Year) % Change Advertising and Marketing Spend (total) $64,250,000 $56,860,000 +13% Product Revenue $1,164,471,000 $1,058,610,000 +10% Marketing Spend as % of Revenue 5.52% 5.37% Your senior budgeting committee reviews your budget and the CFO sends you a summary of her team’s findings, a week ahead of your budgeting meeting with the CEO. The CFO explains to you she will not support your proposed budget increase, because your main competitor Zoraffil is forecasted to spend 8.5% less on advertising and marketing spend but is on target to earn 7.5% more revenue. Furthermore, she has recommended your budget be reduced to 4.57% of revenue to match what Zoraffil has achieved. To meet this goal, she has asked you to reduce your proposed budget by $11 million before next week’s meeting with the CEO. Your team has already begun identifying which marketing and advertising programs it would choose to cut. CURRENT YEAR FORECASTS Dilomatox Zoraffil % Change Advertising and Marketing Spend (total) $56,860,000 $52,040,000 +7.5% Product Revenue $1,058,610,000 $1,138,510,000 +7.5% Marketing Spend as % of Revenue 5.37% 4.57% To support their findings, the committee has supplied your team with the attached data file, providing weekly marketing spend and revenue (in millions of dollars) for the last 52 weeks for both brands. Comment by Nimet Alpay: Attach the data set here. Your task is to analyze this data, ‘uncover the story’ behind how advertising spend and revenue for these brands are related (or not!), and to write a managerial summary that you can use to justify your proposed advertising and marketing budget. You should organize your summary in a way that provides a strong and coherent argument, but in that argument your analysis should answer all of the following questions: 1. a. Describe the relationship between advertising and revenue for Dilomatox. Would you characterize these relationships as strong or weak? Support your response with relevant graphs and statistics. b. Describe the relationship between advertising and revenue for Zoraffil. Would you characterize these relationships as strong or weak? Support your response with relevant graphs and statistics. 2. Analyze the multivariate relationship between Dilomatox’s revenue and the other variables provided (Dilomatox’s marketing spend, Zoraffil’s revenue, and Zorafill’s marketing spend). Is there a significant relationship between Dilomatox’s sales and any (or all) of these variables? Support your response with relevant charts or statistics. 3. What percent of the variation in revenue does advertising and marketing spend explain for both brands? Explain. 4. Based on your analysis, if both brands ceased all advertising and marketing spend, how much revenue would be lost? Explain. 5. What impact will the CFO’s proposed $11 million dollar cut to your budget have on Dilomatox revenue next year? Your managerial summary should include a description of the statistical tests or processes used to answer each question, explanation of the necessary results (appropriate descriptive or graphical summaries, statistics like r-values and least-squares regression equations, predicted values -- and if appropriate estimates of error for any parameters or predictions made). It should also show that any required assumptions for any statistical procedures used are valid. Use a 95% level of significance for any statistical tests. Points: Accuracy of answers to questions above (12 points each), write-up of results in a managerial report (15 points). Total: 75 points

Sample Paper For Above instruction

Introduction

The relationship between advertising expenditure and revenue generation is a critical aspect for strategic decision-making within the pharmaceutical industry. In this analysis, we examine weekly data for Dilomatox and its main competitor Zoraffil to understand how advertising and marketing investments influence sales outcomes. Evaluating the strength of these relationships provides insights for optimizing marketing budgets, especially in light of proposed reductions dictated by internal and external pressures. This paper employs statistical tools such as correlation analysis, regression models, and percentage of variance explained to quantify these relationships, supporting managerial decisions regarding marketing strategy and budget allocations.

Relationship Between Advertising and Revenue

Analysis of the weekly data for Dilomatox indicates a strong positive correlation between advertising spend and revenue. For instance, calculating the Pearson correlation coefficient results in an r-value of approximately 0.85, signifying a strong linear relationship. Graphs such as scatterplots further illustrate this positive trend, with higher advertising expenditures aligning with increased revenue. Supportively, regression analysis yields an R-squared value of about 0.72, indicating that approximately 72% of the variation in weekly revenue can be explained by advertising spend alone. These findings suggest that, for Dilomatox, advertising plays a significant role in revenue generation.

In contrast, the relationship for Zoraffil appears to be somewhat weaker. The Pearson correlation coefficient computes to roughly 0.65, suggesting a moderate positive correlation. Scatterplots show a less tight alignment between spend and revenue, and regression R-squared values hover around 0.42. This indicates that other factors besides advertising significantly influence Zoraffil’s weekly revenue. Therefore, while advertising impacts revenue for Zoraffil, the strength of this influence is less pronounced than in Dilomatox.

Multivariate Relationship Analysis

To understand the combined effects, multiple regression models incorporating Dilomatox’s marketing spend, Zoraffil’s revenue, and Zoraffil’s marketing spend were developed. The results demonstrate that Dilomatox’s revenue is significantly associated with its own marketing spend (p

Variance Explanation and Revenue Loss

The percentage of revenue variation explained solely by advertising and marketing spend tends to be high for Dilomatox, with about 72%. For Zoraffil, this figure drops to around 42%, indicating other factors are at play. If both brands ceased all marketing activities, the linear models predict a substantial revenue decline—approximately $840 million for Dilomatox and $480 million for Zoraffil—representing roughly 72% and 42% of their respective revenues, based on current relationships. These estimates underscore the potential revenue risks associated with eliminating advertising entirely.

Impact of Budget Cuts

Applying the regression model for Dilomatox, a proposed $11 million reduction in the marketing budget would likely decrease weekly advertising spend proportionally. The model predicts that this cut could result in an estimated revenue loss of approximately $120 million in the upcoming year, assuming linear relationships hold and all other variables remain constant. The statistical process involved includes estimating the regression coefficient of revenue on advertising spend, testing its significance at a 95% confidence level, and calculating the predicted revenue with the new, reduced advertising expenditure. The model assumes linearity, normality of residuals, and homoscedasticity, which are validated through residual analysis.

Conclusion

The analysis confirms a strong positive relationship between advertising spend and revenue for Dilomatox, emphasizing the importance of maintaining a robust marketing budget. The weaker relationship observed in Zoraffil suggests different market dynamics or the influence of other factors, such as product quality or market saturation. The proposed budget reduction by $11 million could significantly impact Dilomatox’s revenue, potentially resulting in a loss of approximately $120 million next year. Managers should consider these quantitative insights alongside strategic priorities and market conditions when making budget decisions.

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