week 2

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University of Phoenix *

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565

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Marketing

Date

Feb 20, 2024

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docx

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Uploaded by BrigadierApePerson992

Chantania Smith Week 2 Section 1 I am the sales manager at Pastas R Us, Inc., we are a fast casual restaurant chain specializing in noodle-based dishes, soups, and salads. Our company has historically focused on opening new restaurants in areas where most of the population is between 25 – 45 years age, have a median income above the national average, and at least 15% of the are college-educated adults; that is the ideal customer. We currently have seventy-four restaurants, and we give out loyalty cards to our customers at each location. We reward those clients with free food after every ten purchases they make using that loyalty card. The information from those loyalty cards provides information about the customer’s purchases, it is then entered into a database with that information and all other information collected from each location. The objective of this report is to determine the effectiveness of the current expansion criteria, loyalty card program, and marketing position and ways to improve our profits. I will do this by analyzing all the data that is currently available to me to determine the effectiveness of the loyalty card and our current polices and to do this effectively I will use statistical methods to support actionable business decisions for Pastas R Us, Inc. and to look. The current data from all seventy-four locations is collected and entered into one database. That database is made up of many different variables, those variables are; Sales Per Square Feet ("Sales/Sq.Ft. (($))”) versus Bachelor Degrees (%), Median Income ($) versus “Sales/Sq.Ft. ($), “Median Age (Years)” versus “Sales/Sq.Ft. ($)”, and Loyalty Card (%)” versus “Sales Growth (%)”. I will use all of this data to create a for the executive team from available Pastas R Us, Inc. Based on my descriptive statistical findings from week 1 I determined the many different things including the mean, mode, standard deviation, range, a measure of dispersion and variance, skewness of the data, mainly focusing on the annual sales per square feet and how this was impacted by each variable. Section 2 I observed and am interpreting data from five different scatter plots; sales/sq ft vs. college graduates; sales/sq ft vs. median age; sales/sq ft vs. median income; loyalty card vs. sales growth, and median income vs college graduates. After interpreting the data from each of these scatter plots, I was able to determine that there is a positive relationship between the sales per square feet and college graduates. Based on this we can determine that there is a positive relationship between college graduates living withing three miles of the restaurant and increased sales. After observing the sales per square feet versus median age I determined there is a negative relationship and it showed that there is no significant impact for the Medium Age to the Sales per square feet. There was also a negative relationship between the median income and the sales per square, this variable did not positively impact or increase the company sales. After reviewing the data from the loyalty card versus sales growth also shows a negative relationship. I can conclude that the loyalty card and the median age are negatively skewed, and the other variables are positively skewed. Also concluding that having a bachelor’s degree and living within three miles of a restaurant location positively increases annual sales and will impact it even more for those college graduates who also have and use their loyalty cards.

Chantania Smith Week 2 Section 3: Recommendations and implementation Based on my findings I have determined the most effective expansion criteria would be to build in an area where college graduates stay within three miles of the new location. The criteria that I think can benefit from adjusted and will have the biggest impact would be the median age, the scatter plots indicate that a younger crowd would increase sales as the younger age group prefers our restaurant as opposed to older adults. That variable can be adjusted and could benefit the company once it is adjusted. The loyalty card appears to have a negative relation based on the scatter plot. The loyalty card has a negative impact with customers with are older compared to younger customers and customers who have a college degree. The loyalty card had the highest impact on customers’ median household income so I would market the card more towards those customers in efforts to make the cards more useful. I would recommend expanding into areas that are near colleges as younger people are shopping with us more and they are more likely to attend college, graduate with a degree, and become our target client. Those customers are also more likely to utilize the loyalty card, which can also help increase sales. In the future the company should focus on colleting data that tells how many time a customer shops at the restaurant, the days of the weeks the customer shops at the restaurant, the amount of money they spend on each visit, the number of purchases they make, if they utilize wifi or any other free amenities that the restaurant offers, if they utilize their loyalty card and what recommendation would they have to increase foot traffic at the restaurants. This data can be collected from the sales register as well as by offering surveys to the customers and offering rewards to encourage clients to take the survey.

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