Data analysis aims to describe the distribution of the collected data and determine the accuracy of data in representing a phenomenon. The descriptive statistics indicate that the data is approximately normally distributed and without outliers meaning that the data does not portray any significant bias that may render the analysis results and interpretations erroneous ( Mishra et al., 2019). The report seeks to analyze the effectiveness of the expansion strategy contemplated by Pastas R Us, Inc. Since its inception, the company’s management favors opening of new restaurants within a 3-mile radius while targeting populations within a median age of between 25 to 45 years, at least 15% college level graduates, and household median income above the national average. Also, the marketing department has focused attention on increasing loyalty cards sales to stimulate annual sales growth. In evaluating the strategy, the report seeks to establish the relationship between the company’s sales per square foot and the target variables, as well as the relationship between loyalty card percentage and percentage growth in sales.
Analysis
The relationship between two variables in a scatter graph may be interpreted by observing the trend and slope of the regression line while the strength of the correlation is measured using the r-squared. Like a positive slope, an increasing trend implies that the dependent variable increases with an increase in the independent variable (Sarikaya & Gleicher, 2017). Contrary, a negative slope or a declining trend suggests that the dependent variable decline with an increase in the independent variable. The r-squared value estimates the percentage of variation in the dependent variable, which is explained by the variation in the independent variable (Sarikaya & Gleicher, 2017).
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There exists a positive relationship between the annual sales per square foot and the percentage of the population with a Bachelor’s degree, as shown by the positive slope and increasing trend. An increase in the population proportion with a bachelor’s degree increases the sales per square foot. Variation in the percentage population with Bachelor’s degree explains an 11.69% variation of the annual sales per square foot.
A negative relationship exists between the annual sales per square foot and median household income, as shown by the negative slope and slightly declining trend. Therefore, an increase in the median household income decreases the sales per square foot. Variation in median household income explains a 0.05% variation of the annual sales per square foot.
A negative relationship exists between the annual sales per square foot and the median age, as shown by the negative slope and slightly declining trend. Therefore, an increase in the median age decreases the sales per square foot. Variation in median age explains a 0.36% variation of the annual sales per square foot.
A negative relationship exists between the sales growth and loyalty card net sales, shown by the negative slope and slightly declining trend. Therefore, an increase in the loyalty card net sales triggers a decline in sales growth. Variation in loyalty card percentage sales explains only a 0.36% variation of the sales growth percentage.
Recommendations and implementation
A fairly strong positive correlation exists between the population proportion with a Bachelor’s degree and the annual sales per square foot. Therefore, Pastas R Us, Inc. should accelerate establishing new restaurants in areas with more than 15% population proportion with a Bachelor’s degree. On the contrary, there exists a negative correlation between the annual sales per foot and the target variables of median household income and median age. Therefore, Pastas R Us, Inc. should consider establishing new restaurants in areas with lower median age and household income. Also, the correlation between the percentage annual sales growth and the percentage of loyalty card payments is negative. As a result, the company’s strategy of rolling out a loyalty card program would trigger a decline in annual sales growth. Although the loyalty card strategy seeks to offer discounts to the loyal consumer base, the program is unpopular, suggesting that the consumers are not obsessed with the prices. Pastas R Us, Inc. should therefore discontinue the loyalty card payment strategy at the earliest possible opportunity.
Other than focusing on prices, the brand positioning should focus more on product attributes, benefits, and quality. Continuous assessment of the changing consumer preferences should remain a priority to increase the effectiveness of the company’s strategies. Other than concentrating on factors that influence demand, the company should take an interest in consumer satisfaction. Examples of data that may be collected include demographic information such as age, income, education level, gender and customer satisfaction report such as quality and level of satisfaction measured on the Likert scale, and suggestions on possible improvements. Data analytics is a critical tool in constant evaluation and may involve collecting data through surveys. Surveys may be through social media platforms, company websites, emails, and phone calls.
References
Mishra, P., Pandey, C. M., Singh, U., Gupta, A., Sahu, C., & Keshri, A. (2019). Descriptive statistics and normality tests for statistical data. Annals of cardiac anesthesia , 22(1), 67.
Sarikaya, A., & Gleicher, M. (2017). Scatterplots: Tasks, data, and designs. IEEE transactions on visualization and computer graphics, 24(1), 402-412.
