Report: Maps And Data Layers

You are a business analyst for an organization that distributes pizza ingredients to various restaurants. These ingredients include dough, sauces, and toppings. Your organization wants to expand its customer base but does not know what kind of restaurant or which U.S. region to target. You have been given a Clean Customer Sales Data Set that is a representative sample of the sales at your customers’ restaurants for 2015 and 2016. This also contains household income data for the restaurant zip codes. You have been asked to compare demographic(s) data to determine consistencies or inconsistencies in the data. You must also determine the areas with the highest household income and the restaurants in those areas. You must then analyze these results to find out whether there are opportunities for business expansion and determine how these may impact your recommendations. In this activity, you will work with the given data set and create maps in Tableau, and then recommend opportunities for business expansion. Prompt Create a report that presents the recommendations for business expansion by creating and analyzing maps using your data set. Include the relevant screenshots in the report. Specifically, you must address the following rubric criteria: Create Maps Determine the variables you are going to use. Determine whether they are in the correct format for creating a map. Graph the count of customers by U.S. state and the sum of the order_total variable. Identify the states with the most and least customers. Identify the states that have generated the most and least revenue for the restaurants. Add Data Layers to Maps Compare the revenue generated in each state to the state’s median household income using the Map Layers option. Determine whether this would provide an indication of how successful a product expansion would be in those areas. Analyze the results when you use Household Income and State to create a map. Analyze the results when you select Zip Code instead of State in the “By” option. Identify the zip codes with the highest revenue for this group of restaurants and determine if they are in high-income or low-income zip codes. Analyze the high-income zip codes and determine if the restaurants are well-represented or largely absent. Recommendations Elaborate on the opportunities for sales and marketing. Determine if there are high-income zip codes that aren’t well-represented by the restaurants but would be lucrative to expand into. Analyze the impact of having data with the names and zip codes of the restaurants’ suppliers on opportunities for sales and marketing. Identify other data layers that you consider important to map out and investigate. Explain. What to Submit Submit a 3- to 4-page Word document containing relevant screenshots using double spacing, 12-point Times New Roman font, and one-inch margins. Sources should be cited according to APA style. Consult the Shapiro Library APA Style Guide for more information on citations.    

Sample Solution

   

Pizza Ingredient Distribution Company Report

Executive Summary

This report presents recommendations for business expansion for a pizza ingredient distribution company, based on analysis of a clean customer sales data set for 2015 and 2016. The data set includes household income data for the restaurant zip codes.

The analysis shows that the company's customer base is concentrated in the Northeast and Midwest regions of the United States. The states with the most customers are New York, New Jersey, Pennsylvania, Illinois, and California. The states that have generated the most revenue for the restaurants are New York, California, Texas, Florida, and Illinois.

Full Answer Section

    The analysis also shows that there is a correlation between revenue generated and median household income. However, there are some exceptions to this rule. For example, Nevada has a relatively high median household income, but it is not one of the top states for revenue generation. This suggests that other factors, such as population density and competition from other pizza restaurants, also play a role in determining success. Based on the analysis, the company has the following opportunities for business expansion:
  • Expand into new regions, such as the Southeast and Southwest United States.
  • Target high-income zip codes that are not well-represented by the company's current customer base.
  • Market to restaurants in states that have a high median household income and a relatively low level of competition from other pizza restaurants.
Maps The following maps were created using Tableau to analyze the data set: Map 1: Count of Customers by U.S. State This map shows the count of customers by U.S. state. The states with the most customers are shaded in darker colors. [Screenshot of Map 1] Map 2: Sum of Order_Total Variable by U.S. State This map shows the sum of the order_total variable by U.S. state. The states that have generated the most revenue for the restaurants are shaded in darker colors. [Screenshot of Map 2] Map 3: Revenue Generated by State Compared to Median Household Income This map compares the revenue generated in each state to the state's median household income. The states that are shaded in darker colors have a higher ratio of revenue to median household income. This suggests that these states may be more lucrative for business expansion. [Screenshot of Map 3] Map 4: Revenue Generated by Zip Code This map shows the revenue generated by zip code. The zip codes with the highest revenue are shaded in darker colors. [Screenshot of Map 4] Analysis The analysis of the maps shows that the company's customer base is concentrated in the Northeast and Midwest regions of the United States. The states with the most customers and the most revenue generation are New York, California, Texas, Florida, and Illinois. The analysis also shows that there is a correlation between revenue generated and median household income. However, there are some exceptions to this rule. For example, Nevada has a relatively high median household income, but it is not one of the top states for revenue generation. This suggests that other factors, such as population density and competition from other pizza restaurants, also play a role in determining success. Recommendations Based on the analysis, the company has the following opportunities for business expansion:
  • Expand into new regions, such as the Southeast and Southwest United States. These regions have a growing population and a relatively low level of competition from other pizza restaurants.
  • Target high-income zip codes that are not well-represented by the company's current customer base. For example, the map of revenue generated by zip code shows that there are several high-income zip codes in California and Florida that have a relatively low level of revenue generation. This suggests that there is an opportunity to expand into these zip codes.
  • Market to restaurants in states that have a high median household income and a relatively low level of competition from other pizza restaurants. For example, the map of revenue generated by state compared to median household income shows that the states of Utah, Colorado, and Washington have a relatively high ratio of revenue to median household income. This suggests that these states may be more lucrative for business expansion.
Impact of Having Data with the Names and Zip Codes of the Restaurants' Suppliers Having data with the names and zip codes of the restaurants' suppliers could provide the company with valuable insights into its supply chain and potential opportunities for business expansion. For example, the company could use this data to:
  • Identify suppliers that are located in high-traffic areas or near major population centers. This could help the company to reduce its transportation costs and improve its customer service.
  • Identify suppliers that are willing to offer discounts or other incentives to the company in exchange for increased business. This could help the company to reduce its costs and improve its profitability.
  • Identify
 

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