Bubba Gump Shrimp Company is a successful retailer of regional food, both in its restaurants and through other retail channels. Bubba Gump began as a small, privately owned restaurant. Thanks to unexpected exposure from a blockbuster movie, Bubba Gump grew rapidly from its humble beginnings and now operates several restaurants, sells branded merchandise through an online retail site, and wholesales its branded merchandise to other retail outlets. 

Bubba Gump’s growth was initially very rapid in response to a strong demand and high name recognition that followed from its movie exposure. After its first few years of rapid growth, sales increased at slower rates and finally leveled off. Sales have declined in each of the last two years. Bubba Gump Shrimp Company has collected a large amount of data about its business, including restaurant point-of-sale (POS) data, web channel sales performance, customer information through restaurant loyalty programs, and customer and sales transaction data through its website and retail partners. 

Bubba Gump’s leadership has decided to commission an analysis of the company’s vast data assets to better understand its customers and look for ways to create new revenue growth. You have been assigned to plan, conduct, and report on this data mining initiative for Bubba Gump Shrimp Company. The company data that is available to you includes Bubba Gump’s restaurant point-of-sale (cash register, credit card) data, its customer database (collected from its restaurant loyalty program and online sales channel), its web store sales transaction data, and customer and sales data from third-party retailers. All of Bubba Gump’s data has recently been integrated in a data warehouse. 

That enterprise data warehouse was built specifically to support data mining initiatives like the one you have been assigned to conduct, by consolidating data from multiple operations and channels in one place and integrating the data across sources for a complete view of the customer experience. For the first time, Bubba Gump analysts can link sales transactions to specific customers at specific restaurants, for example. It also means that you can link customer transactions across channels; that is, for any given customer, you can link to both their restaurant purchases, their online purchases, and (in some cases) their purchases from third-party retail partners. You have been selected to develop and execute the data mining analysis plan for Bubba Gump’s customer analysis project. Your project will be the first major data mining project conducted against the new Bubba Gump data warehouse. Because Bubba Gump’s data was not previously integrated in a single data warehouse, company leadership has never been able to analyze its customers across their complete experience. 

In other words, customer restaurant purchases, online purchases, and third-party retailer purchases could not be analyzed together previously; each channel had to be analyzed separately. As a first step, a sample of 500 customers has been selected from the analytics data warehouse and given a survey in exchange for purchase credits at one of Bubba Gump’s sales channels. The survey sample was selected from the universe of customers who have made purchases from at least one Bubba Gump outlet (restaurant, web store, etc.). Responses to various customer satisfaction questions were recorded, and historical purchase information has been extracted from the data warehouse for each customer in the sample.Your task is to analyze the survey responses to understand whether there are natural “clusters” within Bubba Gump’s customer population. You are then to create a visualization of this survey data that describes Bubba Gump’s customers across any dimensions that define those subgroups.

Your Assignment 

In your response, address the following critical elements below:(Please just answer the questions bellow based on the scenerio below you do not need the data but f you must I have attched a picture of the data)

Critical elements:

Analysis Tools

What data mining tools will you use to perform the analysis? Why these particular ones?

Data Visualizations

What data visualizations will you use in your report, and why?

Research Question

What is the specific research question that needs to be addressed? What research question will you work from in order to analyze the given data for meaningful patterns?

Research Measurement

How will you determine if your research question was answered or if your hypothesis generation was successful? How will you measure progress? Follow-Up Questions What are cogent follow-up questions or explorations that should follow from your initial research?

Research and Support

Are there any published sources or other resources that address your line of inquiry? Where do they fall short? How will they help guide your analysis?

E DAT220 Final Project Data (1) - JMP Pro File Edit Tables Rows Cols DOE Analyze Graph Tools View Window Help DAT220 Final Projec. D4 OSource WEB PUR Webstore CH YN first_name last name city county zip ZIP 2 Restaurant RES_VISITS Spend WEB VISITS THIRD SPEND THIRD VISITS state 70 Gayla Schnitzler yward Alameda CA 94545 94 100 71 Mitsue Scipione Oroville Butte CA 95965 95 51 2 78 1 131 72 Lizbeth Kohl Gardena 1 Los Angeles San Diego CA 90248 90 17 1 73 Brett Mccullan La Mesa CA 91942 91 22 1 1 20 1. Columns (18/0) L first_name last_name 74 Staci Schmaltz Pasadena Los Angeles CA 91106 91 81 1 Los Angeles San Francisco San Diego San Bernardino 75 Merissa Tomblin Belflower CA 90706 90 29 1 1 76 Trinidad Mcrae San Francisco CA 94105 94 197 81 1 L city L county L state Azip A ZIP_2 A Restaurant 4 RES_VISITS WEB_PURCH_YN A Webstore_Spend A WEB_VISITS 4 THIRD SPEND THIRD VISITS 1 Age L Married YN A MARR_BIN 77 Mari Lueckenbach San Diego Onofrio CA 92110 92 38 1 78 Antione San Bemardino CA 92410 92 77 1 2 1 79 Clorinda Heimann Escondido San Diego CA 92025 92 31 1 80 Dick Wenzinger Gardena Los Angeles CA 90248 90 147 1 1 231 2 1 81 Daniel Peruzza Santa Ana Orange CA A 92705 92 20 11 82 Cristal Samara Los Angeles Los Angeles CA 90021 90 16 1 Sayaphon Jacobos 83 Rasheeda Saratoga Santa Clara CA 95070 95 20 84 Refugia Hayward Alameda CA 94545 94 60 1 1 32 1. 26 1 85 Dorothy Chesterfield San Diego San Diego CA 92126 92 111 86 Gail Similton Thousand Palms Riverside CA 92276 92 17 25 23 1 87 Thaddeus Ankeny Roseville Placer CA 95678 95 31 1 88 Lai Harabedian Novato Marin CA 94945 94 40 1 1. 89 Carmelina Lindall Littleton Douglas CO 80126 80 70 1 51 1 ORows 90 Alease Buemi Boulder Boulder CO 80303 80 14 1 All rows 502 91 Howard Paulas Denver Denver CO 80231 80 51 1 Selected 92 Pamella Fortino Denver Denver CO 80212 80 175 Excluded Colorado Springs Colorado Springs Englewood 93 Sherita Saras El Paso CO 80937 80 57 2 1 Hidden Labelled 94 Jaclyn Bachman El Paso CO 80919 80 90 95 Mitzie Hudnall Arapahoe CO 80110 80 100 2 96 Virgie Kiel Denver Denver CO 80216 80 210 1 1 1