Imagine you are working in the marketing department of a company. Your supervisor assumes that if the
company spends more on digital advertisements it would lead to an increase in sales. In fact, she hopes
that doubling the budget for digital advertising will result in daily sales that are greater than $10,000. She
wants to solve the problem at hand and asks you to investigate. To verify this assumption, the marketing
department will raise the digital advertisement budget for a six-month period, then analyze the collected
data at the end of that period.
You collect monthly data from the past six months and then randomly sample 30 days. The results of your
sample and your calculations are shown in the Excel file provided in the assignment instructions.
Write a two to three (2–3) page report using the provided template in which you:
1. Construct a box-and-whisker plot for the daily sales.
2. Copy the sample mean, median, and standard deviation for the daily sales.
3. Copy the 95% Confidence Interval for the daily sales.
4. Conduct a hypothesis test to verify if the claim that the mean daily sales is greater than $10,000
is supported. Clearly state the logic of your test, the calculations, and the conclusion of your test.
5. Provide the following discussion based on the conclusion of your test:
a. If you conclude that the mean daily sales is greater than $10,000, provide three (3)
possible causes. Share marketing strategies that will support this upward trend the
company is experiencing.
Or
b. If you conclude that the claim of mean daily sales is not greater than $10,000 is not
supported or justified, provide a detailed explanation to your supervisor of how the
company can increase daily sales. Include marketing strategies that will support an
increase in daily sales. Include your speculation on the reason(s) behind the claim.
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Title: Analysis of Daily Sales Data to Verify the Impact of Increased Digital Advertising Budget
Introduction:
In response to the supervisor's assumption that increasing the digital advertisement budget will lead to increased sales, this report aims to analyze the collected data to determine if the mean daily sales are greater than $10,000. The data was collected over a six-month period, with a randomly sampled subset of 30 days for deeper analysis. By conducting hypothesis tests and providing recommendations based on the conclusions, this report will help inform decision-making strategies for the marketing department.
1. Box-and-Whisker Plot:
A box-and-whisker plot was constructed to provide a visual representation of the daily sales data. It helps identify the distribution, outliers, and the median value. Refer to the attached Excel file for the plot.
2. Sample Statistics:
The following sample statistics were calculated for the daily sales data:
- Sample mean: [insert value]
- Sample median: [insert value]
- Sample standard deviation: [insert value]
3. 95% Confidence Interval:
The 95% confidence interval for the daily sales was calculated to provide a range estimate of the population mean. The interval can be interpreted as follows: we are 95% confident that the true mean daily sales falls within this interval. Refer to the attached Excel file for the confidence interval calculation.
4. Hypothesis Test:
Hypothesis: H0 (Null Hypothesis): The mean daily sales is not greater than $10,000.
H1 (Alternative Hypothesis): The mean daily sales is greater than $10,000.
To perform the hypothesis test, we used a one-sample t-test. The logic behind this test is to compare the mean daily sales ($10,000) to the sample mean and evaluate if there is enough evidence to support the alternative hypothesis.
Calculations:
- Sample mean: [insert value]
- Population mean (assumed): $10,000
- Standard deviation: [insert value]
- Number of observations: 30
- Degrees of freedom: 29
- t-value: [insert calculated value]
- p-value: [insert calculated value]
Conclusion of Hypothesis Test:
Based on the calculated t-value and corresponding p-value, we compare the p-value against a significance level (e.g., 0.05). If the p-value is less than the significance level, we reject the null hypothesis. If not, we fail to reject the null hypothesis.
[State the calculated p-value and compare it to the significance level.]
[State the conclusion: If the p-value is less than the significance level, reject the null hypothesis and conclude that the mean daily sales are greater than $10,000. If the p-value is greater than the significance level, fail to reject the null hypothesis and conclude that the claim is not supported.]
5. Discussion based on the Conclusion:
a. If the conclusion is that the mean daily sales are greater than $10,000:
Possible causes:
1. Increased brand visibility through digital advertisements could have led to higher sales.
- Marketing strategy: Invest in targeted online advertising campaigns to reach a wider audience and strengthen brand presence.
2. Effective utilization of customer data and analytics to optimize advertising efforts.
- Marketing strategy: Implement data-driven marketing campaigns to tailor advertisements to individual customer preferences.
3. Innovative and engaging digital advertising content that captures customer attention and drives conversions.
- Marketing strategy: Focus on creating compelling and interactive digital advertisements to maximize customer engagement.
b. If the conclusion is that the claim of mean daily sales greater than $10,000 is not supported:
Explanations:
1. Increased competition in the market might be drawing customers away from the company.
- Marketing strategy: Conduct competitive analysis to identify unique selling points and develop marketing campaigns that highlight these strengths.
2. Ineffective targeting of the digital advertisements could result in low conversion rates.
- Marketing strategy: Refine audience targeting by utilizing customer data and focusing on specific demographics or interests.
3. External factors such as economic conditions or seasonal variations may impact consumer spending.
- Marketing strategy: Implement promotional campaigns, discounts, or loyalty programs to incentivize customers during less favorable economic periods or slower seasons.
By implementing the recommended marketing strategies, the company can either capitalize on the upward trend in sales or address the underlying issues affecting daily sales, subsequently boosting overall revenue.
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