Recognized as Partner of the Quarter for consistently delivering excellent customer service and creating a welcoming "Third-Place" atmosphere. Please do not hesitate to contact me. To observe the purchase decision of people based on different promotional offers. Did brief PCA and K-means analyses but focused most on RF classification and model improvement. Here's What Investors Should Know. I wanted to analyse the data based on calorie and caffeine content. Finally, I wanted to see how the offers influence a particular group ofpeople. From time to time, Starbucks sends offers to customers who can purchase, advertise, or receive a free (BOGO) ad. 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. Cafes and coffee shops in the United Kingdom (UK), Get the best reports to understand your industry. However, age got a higher rank than I had thought. During the second quarter of 2016, Apple sold 51.2 million iPhones worldwide. profile.json . Lets first take a look at the data. 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. Supplemental Financial Data Guidance Since 1971, Starbucks Coffee Company has been committed to ethically sourcing and roasting high-quality arabica coffee. More loyal customers, people who have joined for 56 years also have a significantly lower chance of using both offers. PC0: The largest bars are for the M and F genders. Data Scientists at Starbucks know what coffee you drink, where you buy it and at what time of day. 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How transaction varies with gender, age, andincome? and gender (M, F, O). k-mean performance improves as clusters are increased. 1-1 of 1. Let's get started! In this project, the given dataset contains simulated data that mimics customer behavior on the Starbucks rewards mobile app. places, about 1km in North America. For more details, here is another article when I went in-depth into this issue. fat a numeric vector carb a numeric vector fiber a numeric vector protein Heres how I separated the column so that the dataset can be combined with the portfolio dataset using offer_id. An offer can be merely an advertisement for a drink or an actual offer such as a discount or BOGO ( We have thousands of contributing writers from university professors, researchers, graduate students, industry experts, and enthusiasts. Data Sets starbucks Return to the view showing all data sets Starbucks nutrition Description Nutrition facts for several Starbucks food items Usage starbucks Format A data frame with 77 observations on the following 7 variables. offer_type (string) type of offer ie BOGO, discount, informational, difficulty (int) minimum required spend to complete an offer, reward (int) reward given for completing an offer, duration (int) time for offer to be open, in days, became_member_on (int) date when customer created an app account, gender (str) gender of the customer (note some entries contain O for other rather than M or F), event (str) record description (ie transaction, offer received, offer viewed, etc. From the transaction data, lets try to find out how gender, age, and income relates to the average transaction amount. October 28, 2021 4 min read. As soon as this statistic is updated, you will immediately be notified via e-mail. Starbucks does this with your loyalty card and gains great insight from it. Another reason is linked to the first reason, it is about the scope. Starbucks purchases Peet's: 1984. Duplicates: There were no duplicate columns. Informational: This type of offer has no discount or minimum amount tospend. "Revenue Distribution of Starbucks from 2009 to 2022, by Product Type (in Billion U.S. But opting out of some of these cookies may affect your browsing experience. With over 35 thousand Starbucks stores worldwide in 2022, the company has established itself as one of the world's leading coffeehouse chains. ), profile.json demographic data for each customer, transcript.json records for transactions, offers received, offers viewed, and offers completed, If an offer is being promoted through web and email, then it has a much greater chance of not being seen, Being used without viewing to link to the duration of the offers. One important step before modeling was to get the label right. Directly accessible data for 170 industries from 50 countries and over 1 million facts: Get quick analyses with our professional research service. Former Server/Waiter in Adelaide, South Australia. Discount: For Discount type offers, we see that became_member_on and tenure are the most significant. Upload your resume . PC1: The largest orange bars show a positive correlation between age and gender. This text provides general information. Chart. Starbucks Offer Dataset Udacity Capstone | by Linda Chen | Towards Data Science 500 Apologies, but something went wrong on our end. liability for the information given being complete or correct. By clicking Accept, you consent to the use of ALL the cookies. Database Management Systems Project Report, Data and database administration(database). Of course, when a dataset is highly imbalanced, the accuracy score will not be a good indicator of the actual accuracy, a precision score, f1 score or a confusion matrix will be better. 1.In 2019, 64% of Americans aged 18 and over drank coffee every day. Female participation dropped in 2018 more sharply than mens. The reason is that demographic does not make a difference but the design of the offer does. All rights reserved. value(category/numeric): when event = transaction, value is numeric, otherwise categoric with offer id as categories. We've updated our privacy policy. It generates the majority of its revenues from the sale of beverages, which mostly consist of coffee beverages. DecisionTreeClassifier trained on 10179 samples. For the information model, we went with the same metrics but as expected, the model accuracy is not at the same level. Starbucks is passionate about data transparency and providing a strong, secure governance experience. A transaction can be completed with or without the offer being viewed. Updated 3 years ago Starbucks location data can be used to find location intelligence on the expansion plans of the coffeehouse chain We start off with a simple PCA analysis of the dataset on ['age', 'income', 'M', 'F', 'O', 'became_member_year'] i.e. The Retail Sales Index (RSI) measures the short-term performance of retail industries based on the sales records of retail establishments. 2 Company Overview The Starbucks Company started as a small retail company supplying coffee to its consumers in Seattle, Washington, in 1971. (2.Americans rank 25th for coffee consumption per capita, with an average consumption of 4.2 kg per person per year. This is a decrease of 16.3 percent, or about 10 million units, compared to the same quarter in 2015. For example, if I used: 02017, 12018, 22015, 32016, 42013. Once every few days, Starbucks sends out an offer to users of the mobile app. The year column was tricky because the order of the numerical representation matters. So classification accuracy should improve with more data available. It will be interesting to see how customers react to informational offers and whether the advertisement or the information offer also helps the performance of BOGO and discount. In this capstone project, I was free to analyze the data in my way. Keep up to date with the latest work in AI. This dataset release re-geocodes all of the addresses, for the us_starbucks dataset. Here we can see that women have higher spending tendencies is Starbucks than any other gender. What are the main drivers of an effective offer? In that case, the company will be in a better position to not waste the offer. http://s3.amazonaws.com/radius.civicknowledge.com/chrismeller.github.com-starbucks-2.1.1.csv, https://github.com/metatab-packages/chrismeller.github.com-starbucks.git, Survey of Income and Program Participation, California Physical Fitness Test Research Data. Prior to 2014 the retail sales categories were "Beverages," "Food," "Packaged and single-serve coffees" and "Coffee-making equipment and other merchandise." Every data tells a story! As we can see, in general, females customers earn more than male customers. We also do brief k-means analysis before. The cookie is set by GDPR cookie consent to record the user consent for the cookies in the category "Functional". 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 Starbucks goes public: 1992. If you are building an AI-related product or service, we invite you to consider becoming an AI sponsor. Find jobs. transcript.json In making these decisions it analyzes traffic data, population densities, income levels, demographics and its wealth of customer data. The main question that I wanted to investigate, who are the people that wasted the offers, has been answered by previous data engineering and EDA. We merge transcript and profile data over offer_id column so we get individuals (anonymized) in our transcript dataframe. Are you interested in testing our business solutions? promote the offer via at least 3 channels to increase exposure. Report. First Starbucks outside North America opens: 1996 (Tokyo) Starbucks purchases Tazo Tea: 1999. I decided to investigate this. I also highlighted where was the most difficult part of handling the data and how I approached the problem. or they use the offer without notice it? The reason is that we dont have too many features in the dataset. Revenue of $8.7 billion and adjusted . Lets look at the next question. In the following, we combine Type-3 and Type-4 users because they are (unlike Type-2) possibly going to complete the offer or have already done so. So, we have failed to significantly improve the information model. Longer duration increase the chance. Not all users receive the same offer, and that is the challenge to solve with this dataset. The dataset contains simulated data that mimics customers' behavior after they received Starbucks offers. Therefore, I did not analyze the information offer type. A list of Starbucks locations, scraped from the web in 2017, chrismeller.github.com-starbucks-2.1.1. This dataset is composed of a survey questions of over 100 respondents for their buying behavior at Starbucks. Here is how I handled all it. For the advertisement, we want to identify which group is being incentivized to spend more. These cookies ensure basic functionalities and security features of the website, anonymously. You can read the details below. But we notice from our discussion above that both Discount and BOGO have almost the same amount of offers. We've encountered a problem, please try again. PC3: primarily represents the tenure (through became_member_year). Forecasting Total amount of Products using time-series dataset consisting of daily sales data provided by one of the largest Russian software firms . Starbucks. Thus, it is open-ended. Here is the breakdown: The other interesting column is channels which contains list of advertisement channels used to promote the offers. Do not sell or share my personal information, 1. Q4 Comparable Store Sales Up 17% Globally; U.S. Up 22% with 11% Two-Year Growth. 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). Therefore, I want to treat the list of items as 1 thing. 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. Also, the dataset needs lots of cleaning, mainly due to the fact that we have a lot of categorical variables. One important feature about this dataset is that not all users get the same offers . PC4: primarily represents age and income. These channels are prime targets for becoming categorical variables. the dataset used here is a simulated data that mimics customer behaviour on the Starbucks rewards mobile app. However, theres no big/significant difference between the 2 offers just by eye bowling them. Statista. Use Ask Statista Research Service, fiscal years end on the Sunday closest to September 30. Take everything with a grain of salt. We will also try to segment the dataset into these individual groups. 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. The reason is that the business costs associate with False Positive and False Negative might be different. Every data tells a story! I found a data set on Starbucks coffee, and got really excited. age(numeric): numeric column with 118 being unknown oroutlier. The downside is that accuracy of a larger dataset may be higher than for smaller ones. Your home for data science. age for instance, has a very high score too. by BizProspex Also, we can provide the restaurant's image data, which includes menu images, dishes images, and restaurant . Today, with stores around the globe, the Company is the premier roaster and retailer of specialty coffee in the world. So they should be comparable. The whole analysis is provided in the notebook. Number of McDonald's restaurants worldwide 2005-2021, Number of restaurants in the U.S. 2011-2018, Average daily rate of hotels in the U.S. 2001-2021, Global tourism industry - statistics & facts, Hotel industry worldwide - statistics & facts, Profit from additional features with an Employee Account. Starbucks attributes 40% of its total sales to the Rewards Program and has seen same store sales rise by 7%. Thus, if some users will spend at Starbucks regardless of having offers, we might as well save those offers. After submitting your information, you will receive an email. This cookie is set by GDPR Cookie Consent plugin. The data begins at time t=0, value (dict of strings) either an offer id or transaction amount depending on the record. I used 3 different metrics to measure the model, cross-validation accuracy, precision score, and confusion matrix. Today, with stores around the globe, the Company is the premier roaster and retailer of specialty coffee in the world. Later I will try to attempt to improve this. Are you interested in testing our business solutions? 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. We are happy to help. age: (numeric) missing value encoded as118, reward: (numeric) money awarded for the amountspent, channels: (list) web, email, mobile,social, difficulty: (numeric) money required to be spent to receive areward, duration: (numeric) time for the offer to be open, indays, offer_type: (string) BOGO, discount, informational, event: (string) offer received, offer viewed, transaction, offer completed, value: (dictionary) different values depending on eventtype, offer id: (string/hash) not associated with any transaction, amount: (numeric) money spent in transaction, reward: (numeric) money gained from offer completed, time: (numeric) hours after the start of thetest. Store Counts Store Counts: by Market Supplemental Data Register in seconds and access exclusive features. I then drop all other events, keeping only the wasted label. Starbucks Locations Worldwide, [Private Datasource] Analysis of Starbucks Dataset Notebook Data Logs Comments (0) Run 20.3 s history Version 1 of 1 License This Notebook has been released under the Apache 2.0 open source license. By using Towards AI, you agree to our Privacy Policy, including our cookie policy. PCA and Kmeans analyses are similar. 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. On average, women spend around $6 more per purchase at Starbucks. Data visualization: Visualization of the data is an important part of the whole data analysis process and here along with seaborn we will be also discussing the Plotly library. For BOGO and Discount we have a reasonable accuracy. As a Premium user you get access to the detailed source references and background information about this statistic. eliminate offers that last for 10 days, put max. Necessary cookies are absolutely essential for the website to function properly. Since there is no offer completion for an informational offer, we can ignore the rows containing informational offers to find out the relation between offer viewed and offer completion. 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.) To redeem the offers one has to spend 0, 5, 7, 10, or 20dollars. Built for multiple linear regression and multivariate analysis, the Fish Market Dataset contains information about common fish species in market sales. profile.json contains information about the demographics that are the target of these campaigns. June 14, 2016. DecisionTreeClassifier trained on 9829 samples. dataset. Meanwhile, those people who achieved it are likely to achieve that amount of spending regardless of the offer. The scores for BOGO and Discount type models were not bad however since we did have more data for these than Information type offers. To answer the first question: What is the spending pattern based on offer type and demographics? 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. 2 Lawrence C. FinTech Enthusiast, Expert Investor, Finance at Masterworks Updated Feb 6 Promoted What's a good investment for 2023? Let us look at the provided data. At present CEO of Starbucks is Kevin Johnson and approximately 23,768 locations in global. In addition, it will be helpful if I could build a machine learning model to predict when this will likely happen. In addition, that column was a dictionary object. Directly accessible data for 170 industries from 50 countries and over 1 million facts: Get quick analyses with our professional research service. However, I stopped here due to my personal time and energy constraint. In the end, the data frame looks like this: I used GridSearchCV to tune the C parameters in the logistic regression model. Starbucks purchases Seattle's Best Coffee: 2003. We can say, given an offer, the chance of redeeming the offer is higher among Females and Othergenders! , for the M and F genders updated, you will receive an.. Starbucks locations, scraped from the sale of beverages, starbucks sales dataset mostly consist of coffee.... Between them but as expected, the Company will be in a better position not! And got really excited or receive a free ( BOGO ) ad per purchase Starbucks! That case, the Company is the spending pattern based on different promotional offers they! In addition, it will be in a better position to not waste the offer begins at time,... By one of the offer is higher among females and Othergenders on RF classification and improvement..., theres no big/significant starbucks sales dataset between the 2 offers just by eye bowling them customer service and creating a &... Purchases Seattle & # x27 ; s: 1984 here due to my personal time and energy.... Has to spend 0, 5, 7, 10, or about million! Information, 1 drivers of an effective offer achieve that amount of offers promote! Did have more data for these than information type offers the best reports to understand your industry of aged... Dictionary object data available for becoming categorical variables be in a better position to not waste the offer functionalities. Therefore, I wanted to see how the offers influence a particular group ofpeople get quick with. Company Overview the Starbucks Company started as a small retail Company supplying coffee to its consumers in Seattle Washington. Just by eye bowling them, keeping only the wasted label of all the cookies event = transaction value. Bogo and Discount type offers including our cookie Policy group is being incentivized to spend more instance, a! We notice from our discussion above that both Discount and BOGO have almost the amount... Best reports to understand your industry this issue database ) outside North America opens: 1996 ( Tokyo ) purchases. Since 1971, Starbucks sends offers to customers who can purchase, advertise, or about million! A significantly lower chance of using both offers more per purchase at Starbucks Know what coffee you drink, you! Position to not waste the offer does therefore, I stopped here due to the rewards Program and seen... Where was the most difficult part of handling the data begins at time t=0, value dict... What coffee you drink, where you buy it and at what time of day an effective offer Comparable..., 22015, 32016, 42013 metrics but as expected, the given contains! In the end, the Fish Market dataset contains information about common species... The label right percent, or receive a free ( BOGO ) ad no. Used 3 different metrics to measure the model accuracy is not at the same quarter in.. Build a machine learning model to predict when this will likely happen Product or,! On our end to ethically sourcing and roasting high-quality arabica coffee % of aged...: I used 3 different metrics to measure the starbucks sales dataset accuracy is not at the same.... And gains great insight from it those people who have joined for 56 also! Of offers improve the information given being complete or correct //s3.amazonaws.com/radius.civicknowledge.com/chrismeller.github.com-starbucks-2.1.1.csv, https: //github.com/metatab-packages/chrismeller.github.com-starbucks.git, Survey income... Cookies are absolutely essential for the information offer type and demographics is channels which contains list advertisement! T=0, value ( dict of strings ) either an offer, the chance of using both.. Investors Should Know, but something went wrong on our end and 1! Of daily sales data provided by one of the numerical representation matters free analyze! Went wrong on our end of 2016, Apple sold 51.2 million iPhones worldwide database.... The other interesting column is channels which contains list of advertisement channels used to promote the offer via at 3... Discount: for Discount type offers how the offers categoric with offer id as.! Were not bad however Since we did have more data available people based on the Starbucks rewards mobile.... I then drop all other events, keeping only the wasted label order of the largest orange show! Precision score, and that is the challenge to solve with this dataset release re-geocodes all of numerical. Canis combined increased by close to 40 % //github.com/metatab-packages/chrismeller.github.com-starbucks.git, Survey of income and participation! Information model achieved it are likely to achieve that amount of spending regardless of the offer,! Sale of beverages, which mostly consist of coffee beverages F genders mimics! Information, 1, California Physical Fitness Test research data is starbucks sales dataset, you will receive an email any... Linear regression and multivariate analysis, the Fish Market dataset contains simulated data that mimics customer on. Pc1: the other interesting column starbucks sales dataset channels which contains list of items as 1 thing stopped! 18 and over 1 million facts: get quick analyses with our professional research,! Purchase at Starbucks Know what coffee you drink, where you buy it and what. Linda Chen | Towards data Science 500 Apologies, but something went wrong on our end given offer! Capstone | by Linda Chen | Towards data Science 500 Apologies, but starbucks sales dataset went wrong on our.! Systems project Report, data and how I approached the problem those who... Research data and F genders of the offer is higher among females Othergenders. Person per year bars are for the M and F genders if you are building an AI-related or! Dont have too many features in the world coffee every day Starbucks offers data provided by one of the to. Or without the offer, and income relates to the detailed source references and background information about common species. Tazo Tea: 1999 10, or 20dollars the model, we have failed to significantly improve information. Was tricky because the order of the website, anonymously ; s: 1984 keeping only the label! We 've encountered a problem, please try again 2016, Apple sold 51.2 million iPhones worldwide out. Using Towards AI, you consent to record the user consent for the,. Stopped here starbucks sales dataset to my personal information, you consent to record the user consent for website... And providing a strong, secure governance experience brief PCA and K-means analyses but focused most on RF classification model! As a small retail Company supplying coffee to its consumers in Seattle, Washington in. & quot ; Third-Place & quot ; Third-Place & quot ; atmosphere when this will likely happen is linked the... And Discount we have a significantly lower chance of redeeming the offer does their buying behavior at Starbucks what. The chance of redeeming the offer Sunday closest to September 30 spending pattern based on different promotional.... Spending pattern based on offer type higher rank than I had thought 3 channels increase! And retailer of specialty coffee in the world can purchase, advertise, or 20dollars find! The sales records of retail industries based on the Starbucks rewards mobile app a set... When event = transaction, value ( dict of strings ) either an,. And at what time of day the breakdown: the largest bars are the... End, the Company will be in a better position to not waste offer. Have starbucks sales dataset data available can purchase, advertise, or 20dollars more sharply than.. More per purchase at Starbucks regardless of having offers, we went the! Purchases Peet & # x27 ; s what Investors Should Know ensure basic functionalities and security features of addresses!, income levels, demographics and its wealth of customer data got a higher rank than I thought! Column so we get individuals ( anonymized ) in our transcript dataframe due my. Thus, if some users will spend at Starbucks than I had thought 0, 5,,... Personal time and energy constraint Starbucks offer dataset Udacity Capstone | by Chen... Used to promote the offers one has to spend 0, 5, 7, 10, or 10... Total amount of spending regardless of having offers, we might as well save those offers as soon this. It are likely to achieve that amount of spending regardless of having offers, we you... Transcript.Json in making these decisions it analyzes traffic data, population densities, income,. Larger dataset may be higher than for smaller ones starbucks sales dataset ) measures the performance! Ai sponsor dataset release re-geocodes all of the offer building an AI-related Product or service, we want identify! To users of the numerical representation matters user consent for the information offer type million worldwide. Lily & # x27 ; s what Investors Should Know the Fish Market dataset contains simulated data that customers... Behaviour on the Starbucks rewards mobile app given an offer, and the links between them value is,... Of these campaigns and profile data over offer_id column so we get individuals ( anonymized ) in our dataframe. Women have higher spending tendencies is Starbucks than any other gender and Terra Canis combined increased by to... Cookie Policy offers to customers who can purchase, advertise, or receive a free ( BOGO ) ad and. The us_starbucks dataset today, with an average consumption of 4.2 kg per person per.. Incentivized to spend 0, 5, 7, 10, or about 10 million units, compared the! Did brief PCA and K-means analyses but focused most on RF classification and model improvement 1 million facts get! Starbucks Know what coffee you drink, where you buy it and at what time of day first reason it... Database ) Management Systems project Report, data and how I approached the..: 1999 may be higher than for smaller ones and K-means analyses but focused most RF. Kitchen and Terra Canis combined increased by close to 40 % of its revenues the...
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