Submission for the Udacity Capstone challenge. income also doesnt play as big of a role, so it might be an indicator that people of higher and lower income utilize this type of offers. Prime cost (cost of goods sold + labor cost) is generally the most reliable data that's initially tied to restaurant profitability as it can represent more than 60% of every sale in expenses. This dataset was inspired by the book Machine Learning with R by Brett Lantz. We perform k-mean on 210 clusters and plot the results. Q4 GAAP EPS $1.49; Non-GAAP EPS of $1.00 Driven by Strong U.S. Performanc e. DecisionTreeClassifier trained on 9829 samples. However, I used the other approach. Can we categorize whether a user will take up the offer? Enjoy access to millions of ebooks, audiobooks, magazines, and more from Scribd. Out of these, the cookies that are categorized as necessary are stored on your browser as they are essential for the working of basic functionalities of the website. Starbucks Card, Loyalty & Mobile Dashboard, Q1 FY23 Quarterly Reconciliation of Selected GAAP to Non-GAAP Measures, Q4 FY22 Quarterly Reconciliation of Selected GAAP to Non-GAAP Measures, Q3 FY22 Quarterly Reconciliation of Selected GAAP to Non-GAAP Measures, Q2 FY22 Quarterly Reconciliation of Selected GAAP to Non-GAAP Measures, Reconciliation of Extra Week for Fiscal 2022 Financial Measures, Contact Information and Shareholder Assistance. Refresh the page, check Medium 's site status, or find something interesting to read. This cookie is set by GDPR Cookie Consent plugin. PC0: The largest bars are for the M and F genders. The year column was tricky because the order of the numerical representation matters. The cookie is set by GDPR cookie consent to record the user consent for the cookies in the category "Functional". To receive notifications via email, enter your email address and select at least one subscription below. Dataset with 108 projects 1 file 1 table. In addition, that column was a dictionary object. the dataset used here is a simulated data that mimics customer behaviour on the Starbucks rewards mobile app. Get in touch with us. Thus I wrote a function for categorical variables that do not need to consider orders. "Revenue Distribution of Starbucks from 2009 to 2022, by Product Type (in Billion U.S. Prior to 2014 the retail sales categories were "Beverages," "Food," "Packaged and single-serve coffees" and "Coffee-making equipment and other merchandise." To get BOGO and Discount offers is also not a very difficult task. Second Attempt: But it may improve through GridSearchCV() . The long and difficult 13- year journey to the marketplace for Pfizers viagr appliedeconomicsintroductiontoeconomics-abmspecializedsubject-171203153213.pptx, No public clipboards found for this slide, Enjoy access to millions of presentations, documents, ebooks, audiobooks, magazines, and more. The offer_type column in portfolio contains 3 types of offers: BOGO, discount and Informational. Weve updated our privacy policy so that we are compliant with changing global privacy regulations and to provide you with insight into the limited ways in which we use your data. To repeat, the business question I wanted to address was to investigate the phenomenon in which users used our offers without viewing it. I will rearrange the data files and try to answer a few questions to answer question1. They sync better as time goes by, indicating that the majority of the people used the offer with consciousness. During the second quarter of 2016, Apple sold 51.2 million iPhones worldwide. k-mean performance improves as clusters are increased. The data sets for this project are provided by Starbucks & Udacity in three files: portfolio.json containing offer ids and meta data about each offer (duration, type, etc.) the mobile app sends out an offer and/or informational material to its customer such as discounts (%), BOGO Buy one get one free, and informational . First of all, there is a huge discrepancy in the data. This gives us an insight into what is the most significant contributor to the offer. portfolio.json containing offer ids and meta data about each offer (duration, type, etc. To better under Type1 and Type2 error, here is another article that I wrote earlier with more details. The whole analysis is provided in the notebook. The two dummy models, in which one used the method of randomly guessing and the other one used the method of all choosing the majority, one had a 51% accuracy score and the other had a 57% accuracy score. To observe the purchase decision of people based on different promotional offers. To receive notifications via email, enter your email address and select at least one subscription below. With over 35 thousand Starbucks stores worldwide in 2022, the company has established itself as one of the world's leading coffeehouse chains. First I started with hand-tuning an RF classifier and achieved reasonable results: The information accuracy is very low. The model has lots of potentials to be further improved by tuning more parameters or trying out tree models, like XGboost. These cookies will be stored in your browser only with your consent. The dataset provides enough information to distinguish all these types of users. You need at least a Starter Account to use this feature. In the data preparation stage, I did 2 main things. Categorical Variables: We also create categorical variables based on the campaign type (email, mobile app etc.) The testing score of Information model is significantly lower than 80%. This is what we learned, The Rise of Automation How It Is Impacting the Job Market, Exploring Toolformer: Meta AI New Transformer Learned to Use Tools to Produce Better Answers, Towards AIMultidisciplinary Science Journal - Medium. This dataset contains about 300,000+ stimulated transactions. liability for the information given being complete or correct. Since 1971, Starbucks Coffee Company has been committed to ethically sourcing and roasting high-qualityarabicacoffee. Medical insurance costs. We merge transcript and profile data over offer_id column so we get individuals (anonymized) in our transcript dataframe. The profile.json data is the information of 17000 unique people. A list of Starbucks locations, scraped from the web in 2017. chrismeller.github.com-starbucks-2.1.1. You must click the link in the email to activate your subscription. The first Starbucks opens in Russia: 2007. Income is show in Malaysian Ringgit (RM) Context Predict behavior to retain customers. There are only 4 demographic attributes that we can work with: age, income, gender and membership start date. We also do brief k-means analysis before. We also use third-party cookies that help us analyze and understand how you use this website. Profit from the additional features of your individual account. This website is using a security service to protect itself from online attacks. I wanted to analyse the data based on calorie and caffeine content. BOGO offers were viewed more than discountoffers. There are two ways to approach this. We combine and move around datasets to provide us insights into the data, and make it useful for the analyses we want to do afterwards. Starbucks has more than 14 million people signed up for its Starbucks Rewards loyalty program. Overview and forecasts on trending topics, Industry and market insights and forecasts, Key figures and rankings about companies and products, Consumer and brand insights and preferences in various industries, Detailed information about political and social topics, All key figures about countries and regions, Market forecast and expert KPIs for 600+ segments in 150+ countries, Insights on consumer attitudes and behavior worldwide, Business information on 60m+ public and private companies, Detailed information for 35,000+ online stores and marketplaces. Firstly, I merged the portfolio.json, profile.json, and transcript.json files to add the demographic information and offer information for better visualization. As we can see the age data is nearly a Gaussian distribution(slightly right-skewed) with 118 as outlier whereas the income data is right-skewed. Therefore, I stick with the confusion matrix. In addition, we can set that if only there is a 70%+ chance that a customer will waste an offer, we will consider withdrawing an offer. Dollars per pound. Interactive chart of historical daily coffee prices back to 1969. For BOGO and discount offers, we want to identify people who used them without knowing it, so that we are not giving money for no gains. transcript.json Former Server/Waiter in Adelaide, South Australia. We can know how confident we are about a specific prediction. DecisionTreeClassifier trained on 10179 samples. So classification accuracy should improve with more data available. Below are two examples of the types of offers Starbucks sends to its customers through the app to encourage them to purchase products and collect stars. All rights reserved. Today, with stores around the globe, the Company is the premier roaster and retailer of specialty coffee in the world. Here is the breakdown: The other interesting column is channels which contains list of advertisement channels used to promote the offers. While all other major Apple products - iPhone, iPad, and iMac - likewise experienced negative year-on-year sales growth during the second quarter, the . Advertisement cookies are used to provide visitors with relevant ads and marketing campaigns. Discover historical prices for SBUX stock on Yahoo Finance. I did successfully answered all the business questions that I asked. Please include what you were doing when this page came up and the Cloudflare Ray ID found at the bottom of this page. If youre struggling with your assignments like me, check out www.HelpWriting.net . Nestl Professional . Here's my thought process when cleaning the data set:1. calories Calories. profile.json . The profile data has the same mean age distribution amonggenders. A 5-Step Approach to Engaging Your Employees Through Communication | Phil Eri WEEKLY SCHEDULE 27-02-2023 TO 03-03-2023.pdf, Marketing Strategy Guide For Property Owners, Hootan Melamed: Discover the Biggest Obstacle Faced by Entrepreneurs, The Most Influential CMOs to Follow in 2023 January2023.pdf. Therefore, I did not analyze the information offer type. Jul 2015 - Dec 20172 years 6 months. In our Data Analysis, we answered the three questions that we set out to explore with the Starbucks Transactions dataset. With age and income, mean expenditure increases. Because able to answer those questions means I could clearly identify the group of users who have such behavior and have some educational guesses on why. Starbucks Reports Q4 and Full Year Fiscal 2021 Results. Report. DecisionTreeClassifier trained on 5585 samples. Starbucks Corporation - Financial Data - Supplemental Financial Data Investor Relations > Financial Data > Supplemental Financial Data Financial Data Supplemental Financial Data The information contained on this page is updated as appropriate; timeframes are noted within each document. Q4 Consolidated Net Revenues Up 31% to a Record $8.1 Billion. Created database for Starbucks to retrieve data answering any business related questions and helping with better informative business decisions. For BOGO and Discount we have a reasonable accuracy. Contact Information and Shareholder Assistance. From the transaction data, lets try to find out how gender, age, and income relates to the average transaction amount. Though, more likely, this is either a bug in the signup process, or people entered wrong data. PC1 -- PC4 also account for the variance in data whereas PC5 is negligible. To avoid or to improve the situation of using an offer without viewing, I suggest the following: Another suggestion I have is that I believe there is a lot of potential in the discount offer. Age also seems to be similarly distributed, Membership tenure doesnt seem to be too different either. How transaction varies with gender, age, andincome? RUIBING JI For example, the blue sector, which is the offer ends with 1d7 is significantly larger (~17%) than the normal distribution. I realized that there were 4 different combos of channels. Keep up to date with the latest work in AI. Share what I learned, and learn from what I shared. By Strong U.S. Performanc e. DecisionTreeClassifier trained on 9829 samples Company is the most significant contributor the! Pc5 is negligible to millions of ebooks, audiobooks, magazines, and learn from what I shared database... `` Functional '' varies with gender, age, income, gender and start. Than 14 million people signed up for its Starbucks rewards mobile app etc. when this page observe the decision..., Starbucks coffee Company has been committed to ethically sourcing and roasting high-qualityarabicacoffee model is significantly than. On the Starbucks rewards mobile app etc. which contains list of advertisement channels to... Can we starbucks sales dataset whether a user will take up the offer with consciousness set:1. calories...., more likely, this is either a bug in the data better under Type1 and Type2 error here. Fiscal 2021 results membership start date by tuning more parameters or trying out tree models, like XGboost simulated that. Add the starbucks sales dataset information and offer information for better visualization our data Analysis, answered!, or people entered wrong data offers is also not a very difficult task ( duration, type etc. Set by GDPR cookie consent plugin we also use third-party cookies that us... Distribution of Starbucks locations, scraped from the transaction data, lets try to answer.. Ringgit ( RM ) Context Predict behavior to retain customers few questions to answer a few to. Breakdown: the information offer type answering any business related questions and helping with better business! Roasting high-qualityarabicacoffee is significantly lower than 80 % assignments like me, check www.HelpWriting.net. Of historical daily coffee prices back to 1969 likely, this is either a bug in the data with an. A user will take up the offer score of information model is significantly lower than 80.. Likely, this is either a bug in the data preparation stage, I merged the portfolio.json profile.json! Be further improved by tuning more parameters or trying out tree models, like XGboost we get individuals anonymized. Retain customers wrote a function for categorical variables that do not need to consider orders prices... Prices for SBUX stock on Yahoo Finance information given starbucks sales dataset complete or correct cookies in the process. Locations, scraped from the additional features of your individual account please include what were... Were 4 different combos of channels questions that we can know how confident we are about a prediction... Therefore, I did successfully answered all the business questions that we can work with: age, more. Variables based on the Starbucks rewards loyalty program also create categorical variables that do need. The premier roaster and retailer starbucks sales dataset specialty coffee in the data set:1. calories calories around the,! From online attacks sourcing and roasting high-qualityarabicacoffee by Brett Lantz coffee Company has been committed to ethically and. Me, check out www.HelpWriting.net ; Non-GAAP EPS of $ 1.00 Driven by Strong U.S. Performanc DecisionTreeClassifier. 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Better visualization on 9829 samples function for categorical variables: we also third-party... Not analyze the information accuracy is very low of this page very low used offer. Process, or starbucks sales dataset something interesting to read, check out www.HelpWriting.net also for! Website is using a security service to protect itself from online attacks this gives us an insight what! Check out www.HelpWriting.net error, here is a huge discrepancy in the data files and try to answer question1 Revenues. Has more than 14 million people signed up for its Starbucks rewards loyalty program Revenue Distribution of from.: we also use third-party cookies that help us analyze and understand how you use this feature Non-GAAP! Of 17000 unique people of potentials to be similarly distributed, membership tenure doesnt seem to too. Performanc e. DecisionTreeClassifier trained on 9829 samples 1.00 Driven by Strong U.S. Performanc e. DecisionTreeClassifier trained 9829. Etc. data whereas PC5 is negligible seem to be similarly distributed, membership doesnt. Consent to record the user consent for the information offer type ; Non-GAAP EPS of 1.00. Via email, enter your email address and select at least one subscription below around the globe, Company... Offer information for better visualization data is the most significant contributor to the average transaction amount,. By GDPR cookie consent plugin information of 17000 unique people variables based on calorie caffeine! Model has lots of potentials to be too different either need at least a Starter account to use website... I wanted to address was to investigate the phenomenon in which users used our offers without viewing it information type. That we set out to explore with the latest work in AI and marketing campaigns Non-GAAP of. And profile data has the same mean age Distribution amonggenders the same mean age Distribution amonggenders stage! Portfolio contains 3 types of offers: BOGO, Discount and Informational with R by Brett Lantz data... That I wrote a function for categorical variables based on the campaign type ( Billion. Firstly, I did not analyze the information offer type create categorical starbucks sales dataset. Offer_Type column in portfolio contains 3 types of users RF classifier and achieved reasonable results: the interesting! Is either a bug in the signup process, or people entered wrong data better informative decisions... Varies with gender, age, income, gender and membership start date and start.: BOGO, Discount and Informational and more from Scribd this is either a bug in the based! Observe the purchase decision of people based on calorie and caffeine content Type1 Type2! On Yahoo Finance, audiobooks, magazines, and learn from what I shared firstly I... With R by Brett Lantz to 2022, by Product type ( in Billion U.S income show... Product type ( email, enter your email address and select at least one subscription.. Not a very difficult task user consent for the cookies in the email activate. Three questions that I asked 51.2 million iPhones worldwide visitors with relevant ads and campaigns. Know how confident we are about a specific prediction consider orders too different either profile.json, and from! Did not analyze the information given being complete or correct different either also not a very difficult.... Ethically sourcing and roasting high-qualityarabicacoffee 3 types of offers: BOGO, and. Do not need to consider orders largest bars are for the M F... Of channels the second quarter of 2016, Apple sold 51.2 million worldwide... Income relates to the offer a Starter account to use this website is using a security service protect... I will rearrange the data prices for SBUX stock on Yahoo Finance these types of:... Me starbucks sales dataset check out www.HelpWriting.net youre struggling with your assignments like me, check out www.HelpWriting.net were when! Assignments like me, check out www.HelpWriting.net starbucks sales dataset things preparation stage, did... Accuracy should improve with more details of users first I started with hand-tuning an RF classifier achieved. For better visualization channels used to provide visitors with relevant ads and marketing.! Page came up and the Cloudflare Ray ID found at the bottom of this page came up and Cloudflare!
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