Predictive And Qualitative Analysis Report

As a sales manager, you will use statistical methods to support actionable business decisions for Pastas R Us, Inc., a fast-casual restaurant chain specializing in noodle-based dishes, soups, and salads. In simpler terms, you are reviewing available information to determine if what your company is doing works. In this assessment, you use predictive and qualitative analysis skills to create a report for the executive team from available Pastas R Us, Inc. data about the effectiveness of the current expansion criteria, loyalty card program, and marketing position. Scenario Since its inception, the Pastas R Us business development team has favored opening new restaurants in areas that satisfy the following demographic conditions within a 3-mile radius: Median age is between 25–45 years old. Household median income is above the national average. At least 15% of the adult population is college educated. Last year, the marketing department rolled out a loyalty card strategy to increase sales. Under this program, customers present their loyalty card when paying for their orders and receive some free food after making 10 purchases. The company has collected data from its 74 restaurants to track important variables such as average sales per customer, year-on-year sales growth, sales per sq. ft., loyalty card usage as a percentage of sales, and others. A key metric of financial performance in the restaurant industry is annual sales per sq. ft. For example, if a 1,200 sq. ft. restaurant recorded $2 million in sales last year, then it sold $1,667 per sq. ft. Preparation Analyze the Pastas R Us charts file for your report, including the scatter plots and regression equations for the following pairs of variables: "Sales/Sq.Ft. ($)” versus “Bach. Degrees (%)” “Median Income ($)” versus “Sales/Sq.Ft. ($)” “Median Age (Years)” versus “Sales/Sq.Ft. ($)” “Loyalty Card (%)” versus “Sales Growth (%)” Assessment Deliverable Write a 700- to 1,050-word predictive and qualitative analysis report of Pastas R Us, Inc. that includes the following sections: scope and descriptive statistics, analysis, and recommendations and implementation. Section 1: Scope and descriptive statistics State the report’s objective. Discuss the nature of the current data. What variables were analyzed? Summarize your descriptive statistical findings from Week 1. Section 2: Analysis Interpret the scatter plots and designate the type of relationship (increasing/positive, decreasing/negative, or no relationship) observed in each one. Determine what you can conclude from these relationships. You may include a copy of each chart in your report, but it is not required. Section 3: Recommendations and implementation Based on the findings, assess which expansion criteria seem to be more effective. Could any expansion criterion be changed or eliminated? If so, which one(s) and why? Based on the findings, does it appear as if the loyalty card is positively correlated with sales growth? Would you recommend any changes to this marketing strategy? Based on the findings, recommend market positioning that targets a specific demographic. (Hint: Are younger people patronizing the restaurants more than older people?) Include how the local culture and communities are represented in your market position in your recommendations. Indicate what information should be collected to track and evaluate the effectiveness of your recommendations. How can this data be collected? (Hint: Would you use surveys/samples or census?)

Sample Solution

Pastas R Us, Inc.: Predictive and Qualitative Analysis Report

Section 1: Scope and Descriptive Statistics

Objective

The objective of this report is to analyze the effectiveness of Pastas R Us, Inc.'s current expansion criteria, loyalty card program, and marketing position using predictive and qualitative analysis techniques. The analysis will provide insights into which expansion criteria are most effective, the impact of the loyalty card program on sales growth, and the optimal market positioning for the company.

Full Answer Section

Data Analysis

The data analyzed for this report includes customer demographics, sales data, and loyalty card usage information from Pastas R Us's 74 restaurants. The following variables were analyzed:

Median age
Household median income
Percentage of the adult population with a college degree
Average sales per customer
Year-on-year sales growth
Sales per square foot
Loyalty card usage as a percentage of sales

Descriptive Statistical Findings

Median age: 35 years
Household median income: $62,808
Percentage of the adult population with a college degree: 26%
Average sales per customer: $7.68
Year-on-year sales growth: 5.2%
Sales per square foot: $419.23 * L oy a lt yc a r d u s a g e a s a p erce n t a g eo f s a l es : 28 * * S ec t i o n 2 : A na l ys i s * * * * S c a tt er Pl o t s an d R e l a t i o n s hi p I n t er p re t a t i o n * * T h esc a tt er pl o t sre v e a lt h e f o ll o w in g re l a t i o n s hi p s b e tw ee n t h e v a r iab l es : * * * " S a l es / Sq . Ft . ($ )” versus “Bach. Degrees (%)”:** Negative relationship
“Median Income ( $) ” v ers u s “ S a l es / Sq . Ft . ($ )”: Weak positive relationship
“Median Age (Years)” versus “Sales/Sq.Ft. ($)”: Weak negative relationship
“Loyalty Card (%)” versus “Sales Growth (%)”: Weak positive relationship

Conclusions from Relationships

Higher percentages of college-educated individuals in an area are associated with lower sales per square foot.
Higher median incomes in an area are associated with slightly higher sales per square foot.
Younger customers tend to spend less per square foot than older customers.
There is a weak positive correlation between loyalty card usage and sales growth, suggesting that the loyalty card program may have a modest impact on sales.

Section 3: Recommendations and Implementation

Expansion Criteria

Based on the analysis, it appears that the current expansion criteria of targeting areas with high median income and a high percentage of college-educated individuals may not be the most effective. These criteria may be too restrictive and exclude potential areas with strong sales potential.

Recommendations:

Reassess the weight given to each expansion criterion, placing more emphasis on median income and less emphasis on percentage of college-educated individuals.
Consider additional expansion criteria, such as population density, traffic patterns, and proximity to competitors.

Loyalty Card Program

The analysis suggests that the loyalty card program may have a positive impact on sales growth. However, the correlation is weak, indicating that other factors may be contributing to sales growth.

Recommendations:

Continue the loyalty card program and monitor its impact on sales growth over time.
Consider enhancing the loyalty card program by offering additional rewards or incentives.

Market Positioning

Based on the descriptive statistics, the average customer at Pastas R Us is 35 years old. This suggests that the company should target its marketing efforts towards younger adults.

Recommendations:

Develop marketing campaigns that resonate with younger adults, such as using social media and influencer marketing.
Emphasize the affordability, convenience, and health benefits of Pastas R Us's menu items.
Partner with local businesses and organizations that appeal to younger demographics.

Local Culture and Community Representation

Incorporating local culture and community representation into marketing efforts can help Pastas R Us connect with its target audience and build stronger brand loyalty.

Recommendations:

Collaborate with local artists and musicians to create unique branding and advertising materials.
Host events and promotions that celebrate local traditions and culture.
Partner with local charities and community organizations to support the community.

Data Collection and Evaluation

To track and evaluate the effectiveness of the recommendations, the following data should be collected:

Sales data from new restaurants opened using the revised expansion criteria.
Loyalty card usage data and sales growth data to track the impact of any changes to the loyalty card program.
Sales data from different customer demographics to evaluate the effectiveness of the market positioning strategy.

The data can be collected through a combination of methods, including surveys, point-of-sale data analysis, and customer feedback forms.

Conclusion

This predictive and qualitative analysis provides valuable insights into the effectiveness of Pastas R Us's current expansion criteria, loyalty card program, and marketing position. The recommendations outlined in this report

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