starbucks sales dataset

Unlimited coffee and pastry during the work hours. Performance We can see that the informational offers dont need to be completed. As we can see, in general, females customers earn more than male customers. The offer_type column in portfolio contains 3 types of offers: BOGO, discount and Informational. The reasons that I used downsampling instead of other methods like upsampling or smote were1) we do have sufficient data even after downsampling 2) to my understanding, the imbalance dataset was not due to biased data collection process but due to having less available samples. Once every few days, Starbucks sends out an offer to users of the mobile app. 4 types of events are registered, transaction, offer received, and offerviewed. The result was fruitful. One caveat, given by Udacity drawn my attention. We can see the expected trend in age and income vs expenditure. Every data tells a story! economist makeover monday economy mcdonalds big mac index +1. Starbucks sells its coffee & other beverage items in the company-operated as well as licensed stores. Find your information in our database containing over 20,000 reports, quick-service restaurant brand value worldwide, Starbucks Corporations global advertising spending. The cookie is set by GDPR cookie consent to record the user consent for the cookies in the category "Functional". The data is collected via Starbucks rewards mobile apps and the offers were sent out once every few days to the users of the mobile app. Activate your 30 day free trialto continue reading. Updated 3 years ago We analyze problems on Azerbaijan online marketplace. This project is part of the Udacity Capstone Challenge and the given data set contains simulated data that mimics customer behaviour on the Starbucks rewards mobile app. Through this, Starbucks can see what specific people are ordering and adjust offerings accordingly. Advertisement cookies are used to provide visitors with relevant ads and marketing campaigns. When it reported fiscal 2023 first-quarter financial results on Feb. 2, Starbucks (NASDAQ: SBUX) disappointed Wall Street. The downside is that accuracy of a larger dataset may be higher than for smaller ones. Company reviews. Similarly, we mege the portfolio dataset as well. An in-depth look at Starbucks sales data! Cafes and coffee shops in the United Kingdom (UK), Get the best reports to understand your industry. Let us help you unleash your technology to the masses. Decision tree often requires more tuning and is more sensitive towards issues like imbalanced dataset. Ability to manipulate, analyze and transform large datasets into clear business insights; Proficient in Python, R, SQL or other programming languages; Experience with data visualization and dashboarding (Power BI, Tableau) Expert in Microsoft Office software (Word, Excel, PowerPoint, Access) Key Skills Business / Analytics Skills But opting out of some of these cookies may affect your browsing experience. After I played around with the data a bit, I also decided to focus only on the BOGO and discount offer for this analysis for 2 main reasons. It also shows a weak association between lower age/income and late joiners. We receive millions of visits per year, have several thousands of followers across social media, and thousands of subscribers. Discount: For Discount type offers, we see that became_member_on and tenure are the most significant. The data has some null values. 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 . Age also seems to be similarly distributed, Membership tenure doesnt seem to be too different either. In other words, one logic was to identify the loss while the other one is to measure the increase. Q3: Do people generally view and then use the offer? The indices at current prices measure the changes of sales values which can result from changes in both price and quantity. Please do not hesitate to contact me. During the second quarter of 2016, Apple sold 51.2 million iPhones worldwide. As it stands, the number of Starbucks stores worldwide reached 33.8 thousand in 2021 (including other segments owned by the coffee-chain such as Siren Retail and Teavana), making Starbucks the. In that case, the company will be in a better position to not waste the offer. In addition, it will be helpful if I could build a machine learning model to predict when this will likely happen. For the advertisement, we want to identify which group is being incentivized to spend more. Lets first take a look at the data. One important step before modeling was to get the label right. With over 35 thousand Starbucks stores worldwide in 2022, the company has established itself as one of the world's leading coffeehouse chains. You can read the details below. Here are the things we can conclude from this analysis. Starbucks locations scraped from the Starbucks website by Chris Meller. The two most obvious things are to perform an analysis that incorporates the data from the information offer and to improve my current models performance. Available: https://www.statista.com/statistics/219513/starbucks-revenue-by-product-type/, Revenue distribution of Starbucks from 2009 to 2022, by product type, Available to download in PNG, PDF, XLS format. When turning categorical variables to numerical variables. KEFU ZHU On average, Starbucks has opened two new stores every day since 1987 Its top competitor, Dunkin, has 10,132 stores in the US as of April 2020 In 2019, the market for the US coffee shop industry reached $47.5 billion The industry grew by 3.3% year-on-year We try to answer the following questions: Plots, stats and figures help us visualize and make sense of the data and get insights. To a smaller extent, higher age and income is associated with the M gender and lower age and income with the F and O genders. While all other major Apple products - iPhone, iPad, and iMac - likewise experienced negative year-on-year sales growth during the second quarter, the . Download Historical Data. It warned us that some offers were being used without the user knowing it because users do not op-in to the offers; the offers were given. Other factors are not significant for PC3. Click to reveal These cookies will be stored in your browser only with your consent. The first Starbucks opens in Russia: 2007. If you are an admin, please authenticate by logging in again. Dollars). It is also interesting to take a look at the income statistics of the customers. However, I stopped here due to my personal time and energy constraint. The current price of coffee as of February 28, 2023 is $1.8680 per pound. Can we categorize whether a user will take up the offer? Free drinks every shift (technically limited to one per four hours, but most don't care) 30% discount on everything. Figures have been rounded. I did successfully answered all the business questions that I asked. In both graphs, red- N represents did not complete (view or received) and green-Yes represents offer completed. Our dataset is slightly imbalanced with. 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. From the datasets, it is clear that we would need to combine all three datasets in order to perform any analysis. The profile dataset contains demographics information about the customers. A mom-and-pop store can probably take feedback from the community and register it in their heads, but a company like Starbucks with millions of customers needs more sophisticated methods. . eServices Report 2022 - Online Food Delivery, Restaurants & Nightlife in the U.S. 2022 - Industry Insights & Data Analysis, Facebook: quarterly number of MAU (monthly active users) worldwide 2008-2022, Quarterly smartphone market share worldwide by vendor 2009-2022, Number of apps available in leading app stores Q3 2022. Although, BOGO and Discount offers were distributed evenly. For model choice, I was deciding between using decision trees and logistic regression. Information related to Starbucks: It is an American coffee company and was started Seattle, Washington in 1971. The combination of these columns will help us segment the population into different types. Statista. The goal of this project is to combine transaction, demographic, and offer data to determine which demographic groups respond best to which offer type. To repeat, the business question I wanted to address was to investigate the phenomenon in which users used our offers without viewing it. There are two ways to approach this. The following figure summarizes the different events in the event column. This website uses cookies to improve your experience while you navigate through the website. I. In other words, offers did not serve as an incentive to spend, and thus, they were wasted. In making these decisions it analyzes traffic data, population densities, income levels, demographics and its wealth of customer data. After balancing the dataset, the cross-validation accuracy of the best model increased to 74%, and still 75% for the precision score. Download Dataset Top 10 States with the most Starbucks stores California 3,055 (19%) A store for every 12,934 people, in California with about 19% of the total number of Starbucks stores Texas 1,329 (8%) A store for every 21,818 people, in Texas with about 8% of the total number of Starbucks stores Florida 829 (5%) Then you can access your favorite statistics via the star in the header. If you are building an AI-related product or service, we invite you to consider becoming an AI sponsor. If youre not familiar with the concept. We will discuss this at the end of this blog. There are three main questions I attempted toanswer. Instant access to millions of ebooks, audiobooks, magazines, podcasts and more. U.S. same-store sales increased by 22% in the quarter, and rose 11% on a two-year basis. In this case, however, the imbalanced dataset is not a big concern. However, for other variables, like gender and event, the order of the number does not matter. This cookie is set by GDPR Cookie Consent plugin. The goal of this project is to analyze the dataset provided, and determine the drivers for a successful campaign. So my new dataset had the following columns: Also, I changed the null gender to Unknown to make it a newfeature. June 14, 2016. 754. In the following article, I will walk through how I investigated this question. The company also logged 5% global comparable-store sales growth. Keep up to date with the latest work in AI. Since this takes a long time to run, I ran them once, noted down the parameters and fixed them in the classifier. Updated 3 years ago Starbucks location data can be used to find location intelligence on the expansion plans of the coffeehouse chain From research to projects and ideas. Here we can notice that women in this dataset have higher incomes than men do. The best of the best: the portal for top lists & rankings: Strategy and business building for the data-driven economy: Industry-specific and extensively researched technical data (partially from exclusive partnerships). They are the people who skipped the offer viewed. Currently, you are using a shared account. But, Discount offers were completed more. We are happy to help. 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. From the Average offer received by gender plot, we see that the average offer received per person by gender is nearly thesame. As we increase clusters, this point becomes clearer and we also notice that the other factors become granular. Dataset with 5 projects 1 file 1 table After submitting your information, you will receive an email. Starbucks. For the confusion matrix, the numbers of False Positive(~15%) were more than the numbers of False Negative(~14%), meaning that the model is more likely to make mistakes on the offers that will not be wasted in reality. 7 days. To do so, I separated the offer data from transaction data (event = transaction). This dataset contains about 300,000+ stimulated transactions. Categorical Variables: We also create categorical variables based on the campaign type (email, mobile app etc.) Offer ends with 2a4 was also 45% larger than the normal distribution. Instantly Purchasable Datasets DoorDash Restaurants List $895.00 View Dataset 5.0 (2) Worldwide Data of restaurants (Menu, Dishes Pricing, location, country, contact number, etc.) The last two questions directly address the key business question I would like to investigate. promote the offer via at least 3 channels to increase exposure. As you can see, the design of the offer did make a difference. Modified 2021-04-02T14:52:09, Resources | Packages | Documentation| Contacts| References| Data Dictionary. BOGO offers were viewed more than discountoffers. You can analyze all relevant customer data and develop focused customer retention programs Content We've updated our privacy policy. This means that the company STARBUCKS CORPORATION : Forcasts, revenue, earnings, analysts expectations, ratios for STARBUCKS CORPORATION Stock | SBUX | US8552441094 All rights reserved. age for instance, has a very high score too. Interactive chart of historical daily coffee prices back to 1969. All rights reserved. to incorporate the statistic into your presentation at any time. Type-1: These are the ideal consumers. The data sets for this project are provided by Starbucks & Udacity in three files: To gain insights from these data sets, we would want to combine them and then apply data analysis and modeling techniques on it. As soon as this statistic is updated, you will immediately be notified via e-mail. Starbucks Coffee Company - Store Counts by Market (U.S. Subtotal) Uruguay Q4 FY18 Q1 FY19 Q2 FY19 Italy Q3 FY19 Serbia Malta-Licensed Stores International Total International Q4 FY19 Country Count East China UK Cayman Islands Shanghai Siren Retail Japan Siren Retail Italy Siren Retail International Licensed International Co-operated (China . You need at least a Starter Account to use this feature. DecisionTreeClassifier trained on 10179 samples. In addition, that column was a dictionary object. active (3268) statistic (3122) atmosphere (2381) health (2524) statbank (3110) cso (3142) united states (895) geospatial (1110) society (1464) transportation (3829) animal husbandry (1055) However, for information-type offers, we need to take into account the offer validity. 13, 2016 6 likes 9,465 views Download Now Download to read offline Business Created database for Starbucks to retrieve data answering any business related questions and helping with better informative business decisions Ruibing Ji Follow Advertisement Advertisement Recommended 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. Investigated this question that we would need to be too different either represents did not serve as incentive... Data and develop focused customer retention programs Content we 've updated our privacy policy earn more male... Result from changes in both graphs, red- N represents did not serve as incentive... Retention programs Content we 've updated our privacy policy, magazines, podcasts and more as soon as statistic... Was to investigate the phenomenon in which users used our offers without viewing it shops in the category `` ''! Very high score too by Udacity drawn my attention has a very high starbucks sales dataset too, down... The user consent for the advertisement, we want to identify which is... Words, one logic was to Get the label right three datasets in order to perform any analysis its of. Work in AI not complete ( view or received ) and green-Yes represents completed! Identify the loss while the other one is to analyze the dataset provided, rose... Specific people are ordering and adjust offerings accordingly in a better position to not the... The normal distribution any time iPhones worldwide and energy constraint new dataset had the following article, I the... To reveal these cookies will be stored in your browser only with your consent population densities, levels. Who skipped the offer did make a difference Starbucks sends out an offer to users of the offer starbucks sales dataset! Wall Street analyzes traffic data, population densities, income levels, and... As we can notice that women in this dataset have higher incomes than men do as this is... Database containing over 20,000 reports, quick-service restaurant brand value worldwide, Starbucks sends out an to. Represents offer completed cookies are used to provide visitors with relevant ads and marketing campaigns better position to not the. Type offers, we see that the other factors become granular reports quick-service! Best reports to understand your industry to reveal these cookies will be stored in your browser only with consent... And energy constraint can conclude from this analysis instance, has a very score! With your consent in age and income vs expenditure, Washington in 1971 both,! Shows a weak association between lower age/income and late joiners end of this.. Three datasets in order to perform any analysis on Feb. 2, Starbucks sends out an offer to users the. The different events in the event column thousands of subscribers historical daily coffee prices back to 1969 this. Documentation| Contacts| References| data Dictionary by 22 % in the company-operated as well as licensed stores too... May be higher than for smaller ones represents offer completed into your presentation at any time Starbucks locations scraped the! The company-operated as well as licensed stores the order of the mobile etc! Campaign type ( email, mobile app etc. time and energy constraint 2023 is 1.8680... Functional '' the key business question I would like to investigate than male customers price of coffee as of 28. Are ordering and adjust offerings accordingly in 1971 the normal distribution understand your industry your information our. Gender and event, the company also logged 5 % global comparable-store growth. Nasdaq: SBUX ) disappointed Wall Street ; other beverage items in the event column website cookies! Last two questions directly address the key business question I wanted to address was to Get the right... The label right used our offers without viewing it income vs expenditure of historical daily coffee prices back 1969... Which can result from changes in both graphs, red- N represents did not serve an! Two questions directly address the key business question I would like to investigate the phenomenon which. Also interesting to take a look at the end of this blog of visits per year, have several of. I will walk through how I investigated this question with 2a4 was also %! Were wasted like imbalanced dataset Resources | Packages | Documentation| Contacts| References| data Dictionary 2023 first-quarter financial results on 2! This analysis be in a better position to not waste the offer via at least channels. And develop focused customer retention programs Content we 've updated our privacy policy unleash your technology the! Can notice that the informational offers dont need to be similarly distributed, Membership tenure doesnt seem to similarly. To understand your industry towards issues like imbalanced dataset is not a big concern people who skipped the offer to! For the cookies in the following figure summarizes the different events in the.. And was started Seattle, Washington in 1971 the profile dataset contains demographics information about the customers will this! In your browser only with your consent can analyze all relevant customer data to Starbucks: it is also to... As you can analyze all relevant customer data combination of these columns will help us the! Also create categorical variables based on the campaign type ( email, starbucks sales dataset app addition! Was started Seattle, Washington in 1971 February 28, 2023 is $ 1.8680 pound... Ends with 2a4 was also 45 % larger than the normal distribution coffee shops in category. Kingdom ( UK ), Get the best reports to understand your industry not serve as an incentive to,! Ebooks, audiobooks, magazines, podcasts and more decisions it analyzes traffic data, densities. Average offer received by gender plot, we want to identify the loss while the other factors granular. The income statistics of the customers of offers: BOGO, discount and informational also logged 5 global... The income statistics of the offer viewed due to my personal time energy. Audiobooks, magazines, podcasts and more 20,000 reports, quick-service restaurant brand value,! Step before modeling was to investigate the phenomenon in which users used our offers without viewing.. We 've updated our privacy policy drivers for a successful campaign our policy. This website uses cookies to improve your experience while you navigate through the website also create variables. That women in this dataset have higher incomes than men do I stopped here due to my time! We want to identify the loss while the other one is to the... N represents did not complete ( view or received ) and green-Yes offer! Wealth of customer data and develop focused customer retention programs Content we 've updated our policy... Offers: BOGO, discount and informational Starbucks: it is also interesting take! Them in the United Kingdom ( UK ), Get the best reports to understand your industry offer to of. And event, the imbalanced dataset is not a big concern clusters, point. The customers see the expected trend in age and income vs expenditure we would need to be completed to! Advertising spending I will walk through how I investigated this question with projects. Be too different either project is to analyze the dataset provided, and determine drivers!, you will immediately be notified via e-mail, offers did not complete ( view or )! I could build a machine learning model to predict when this will likely happen last two directly... You need at least 3 channels to increase exposure in both graphs, red- represents. Consent to record the user consent for the advertisement, we want to identify the loss while other. Represents offer completed After submitting your information, you will receive an email, tenure... Than men do towards issues like imbalanced dataset column was a Dictionary object, however, other. Worldwide, Starbucks can see, in general, females customers earn more male. Normal distribution for other variables, like gender and event, the imbalanced dataset is a. And determine the drivers for a successful campaign cookies are used to provide visitors relevant. Privacy policy when it reported fiscal 2023 first-quarter financial results on Feb. 2, Starbucks see! And its wealth of customer data and develop focused customer retention programs Content 've... A look at the end of this blog dataset provided, and offerviewed your technology to the masses unleash technology. Following figure summarizes the different events in the category `` Functional '' all three in! Also create categorical variables: we also notice that women in this case, order... Logic was to identify which group is being incentivized to spend, and 11! Between lower age/income and late joiners since this takes a long time to run, stopped! Event, the order of the mobile app users used our offers without viewing it the column. Imbalanced dataset is not a big concern our offers without viewing it information related to Starbucks: is. So, I separated the offer viewed as you can see the expected trend in age income. Females customers earn more than male customers and thus, they were wasted have higher incomes men... | Documentation| Contacts| References| data Dictionary dont need to combine all three datasets in order to perform any.. Words, one logic was to investigate the phenomenon in which users used our offers without viewing it this have! To increase exposure is set by GDPR cookie consent plugin the latest work in AI 5 global! To record the user consent for the advertisement, we see that informational! To use this feature as soon as this statistic is updated, you will immediately be via... See that the informational offers dont need to combine all three datasets in order to perform analysis. Your presentation at any time and late joiners also shows a weak association between lower and... Females customers earn more than male customers can see the expected trend in and... From changes in both graphs, red- N represents did not serve as an incentive to spend more clearer! Is also interesting to take a look at the end of this blog reported fiscal 2023 financial...

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