![]() Step 1: To forecast produce sales for existing stores you should aggregate produce sales across all stores by month and create a forecast. Note: Use a 6 month holdout sample for the TS Compare tool (this is because we do not have that much data so using a 12 month holdout would remove too much of the data) You’ve been asked to prepare a monthly forecast for produce sales for the full year of 2016 for both existing and new stores. What format do each of the 10 new stores fall into? Please provide a data table.įresh produce has a short life span, and due to increasing costs, the company wants to have an accurate monthly sales forecast.What are the three most important variables that help explain the relationship between demographic indicators and store formats? Please include a visualization.What methodology did you use to predict the best store format for the new stores? Why did you choose that methodology?.You can leave all predictor variables in the model. However, there is no need to do so in this project. Note: In a real world scenario, you could use PCA to reduce the number of predictor variables.Use the StoreDemographicData.csv file, which contains the information for the area around each store.Use the model to predict the best store format for each of the 10 new stores.Make sure to compare a decision tree, forest, and boosted model. Use a 20% validation sample with Random Seed = 3 when creating samples with which to compare the accuracy of the models.Develop a model that predicts which segment a store falls into based on the demographic and socioeconomic characteristics of the population that resides in the area around each new store.Task 2: Determine the Store Format for New Stores However, we don’t have sales data for these new stores yet, so we’ll have to determine the format using each of the new store’s demographic data. The company wants to determine which store format each of the new stores should have. The grocery store chain has 10 new stores opening up at the beginning of the year. Make sure to include a legend! Feel free to simply copy and paste the map into the submission template. Please provide a map created in Tableau that shows the location of the existing stores, uses color to show cluster, and size to show total sales.Based on the results of the clustering model, what is one way that the clusters differ from one another?.How many stores fall into each store format?.What is the optimal number of store formats? How did you arrive at that number?.Use the StoreSalesData.csv and StoreInformation.csv files.Segment the 85 current stores into the different store formats.Use percentage sales per category per store for clustering (category sales as a percentage of total store sales). ![]()
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