We can see that the informational offers dont need to be completed. The reason is that demographic does not make a difference but the design of the offer does. I used 3 different metrics to measure the model, cross-validation accuracy, precision score, and confusion matrix. This dataset is a simplified version of the real Starbucks app because the underlying simulator only has one product whereas Starbucks sells dozens of products. From research to projects and ideas. 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. As soon as this statistic is updated, you will immediately be notified via e-mail. Therefore, I did not analyze the information offer type. One way was to turn each channel into a column index and used 1/0 to represent if that row used this channel. Keep up to date with the latest work in AI. You must click the link in the email to activate your subscription. One was to merge the 3 datasets. Performance & security by Cloudflare. Most of the offers as we see, were delivered via email and the mobile app. Click here to review the details. So it will be good to know what type of error the model is more prone to. All rights reserved. Let us look at the provided data. The reason is that the business costs associate with False Positive and False Negative might be different. PC1 -- PC4 also account for the variance in data whereas PC5 is negligible. Lets recap the columns for better understanding: We can make a plot of what percentage of the distributed offer was BOGO, Discount, and Informational and finally find out what percentage of the offers were received, viewed, and completed. An offer can be merely an advertisement for a drink or an actual offer such as a discount or BOGO ( Here are the things we can conclude from this analysis. One difficulty in merging the 3 datasets was the value column in the transcript dataset contained both the offer id and the dollar amount. Every data tells a story! For future studies, there is still a lot that can be done. It appears that you have an ad-blocker running. Urls used in the creation of this data package. 1-1 of 1. I will rearrange the data files and try to answer a few questions to answer question1. A Medium publication sharing concepts, ideas and codes. This cookie is set by GDPR Cookie Consent plugin. The dataset includes the fish species, weight, length, height and width. This the primary distinction represented by PC0. Towards AI is the world's leading artificial intelligence (AI) and technology publication. 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. Then you can access your favorite statistics via the star in the header. However, for each type of offer, the offer duration, difficulties or promotional channels may vary. Database Management Systems Project Report, Data and database administration(database). age for instance, has a very high score too. Database Project for Starbucks (SQL) May. With over 35 thousand Starbucks stores worldwide in 2022, the company has established itself as one of the world's leading coffeehouse chains. Later I will try to attempt to improve this. The value column has either the offer id or the amount of transaction. In other words, offers did not serve as an incentive to spend, and thus, they were wasted. Please create an employee account to be able to mark statistics as favorites. ), time (int) time in hours since start of test. Currently, you are using a shared account. This website is using a security service to protect itself from online attacks. The original datafile has lat and lon values truncated to 2 decimal places, about 1km in North America. Search Salary. If you are making an investment decision regarding Starbucks, we suggest that you view our current Annual Report and check Starbucks filings with the Securities and Exchange Commission. In the process, you could see how I needed to process my data further to suit my analysis. Offer ends with 2a4 was also 45% larger than the normal distribution. Q4 GAAP EPS $1.49; Non-GAAP EPS of $1.00 Driven by Strong U.S. Performanc e. KEFU ZHU [Online]. We also use third-party cookies that help us analyze and understand how you use this website. However, age got a higher rank than I had thought. Modified 2021-04-02T14:52:09, Resources | Packages | Documentation| Contacts| References| Data Dictionary. 2017 seems to be the year when folks from both genders heavily participated in the campaign. Customers spent 3% more on transactions on average. Here are the five business questions I would like to address by the end of the analysis. DATABASE PROJECT Tried different types of RF classification. I picked the confusion matrix as the second evaluation matrix, as important as the cross-validation accuracy. These cookies ensure basic functionalities and security features of the website, anonymously. dollars)." (World Atlas)3.The USA ranks 11th among the countries with the highest caffeine consumption, with a rate of 200 mg per person per day. Let's get started! dataset. A listing of all retail food stores which are licensed by the Department of Agriculture and Markets. At Towards AI, we help scale AI and technology startups. Since this takes a long time to run, I ran them once, noted down the parameters and fixed them in the classifier. 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. I want to end this article with some suggestions for the business and potential future studies. 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. 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. The testing score of Information model is significantly lower than 80%. Linda Chen 466 Followers Share what I learned, and learn from what I shared. Updated 3 years ago We analyze problems on Azerbaijan online marketplace. First of all, there is a huge discrepancy in the data. To redeem the offers one has to spend 0, 5, 7, 10, or 20dollars. Starbucks locations scraped from the Starbucks website by Chris Meller. Importing Libraries 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. 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. Sales in new growth platforms Tails.com, Lily's Kitchen and Terra Canis combined increased by close to 40%. Introduction. While Men tend to have more purchases, Women tend to make more expensive purchases. So classification accuracy should improve with more data available. Information related to Starbucks: It is an American coffee company and was started Seattle, Washington in 1971. There are three main questions I attempted toanswer. There are many things to explore approaching from either 2 angles. This statistic is not included in your account. During that same year, Starbucks' total assets. Read by thought-leaders and decision-makers around the world. Comment. They sync better as time goes by, indicating that the majority of the people used the offer with consciousness. I found the population statistics very interesting among the different types of users. The Reward Program is available on mobile devices as the Starbucks app, and has seen impressive membership and growth since 2008, with multiple iterations on its original form. 2021 Starbucks Corporation. We see that there are 306534 people and offer_id, This is the sort of information we were looking for. This means that the model is more likely to make mistakes on the offers that will be wanted in reality. By using Towards AI, you agree to our Privacy Policy, including our cookie policy. Starbucks attributes 40% of its total sales to the Rewards Program and has seen same store sales rise by 7%. ), profile.json demographic data for each customer, transcript.json records for transactions, offers received, offers viewed, and offers completed. Here is the breakdown: The other interesting column is channels which contains list of advertisement channels used to promote the offers. And by looking at the data we can say that some people did not disclose their gender, age, or income. 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. 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. Interactive chart of historical daily coffee prices back to 1969. I decided to investigate this. Once every few days, Starbucks sends out an offer to users of the mobile app. Here we can notice that women in this dataset have higher incomes than men do. The action you just performed triggered the security solution. We also do brief k-means analysis before. BOGO: For the buy-one-get-one offer, we need to buy one product to get a product equal to the threshold value. In this capstone project, I was free to analyze the data in my way. Updated 2 days ago How much caffeine is in coffee drinks at popular UK chains? Unbeknown to many, Starbucks has invested significantly in big data and analytics capabilities in order to determine the potential success of its stores and products, and grow sales. This website uses cookies to improve your experience while you navigate through the website. In the following article, I will walk through how I investigated this question. This indicates that all customers are equally likely to use our offers without viewing it. You can analyze all relevant customer data and develop focused customer retention programs Content Statista assumes no For the machine learning model, I focused on the cross-validation accuracy and confusion matrix as the evaluation. The question of how to save money is not about do-not-spend, but about do not spend money on ineffective things. Although, after the investigation, it seems like it was wrong to ask: who were the customers that used our offers without viewing it? Starbucks is passionate about data transparency and providing a strong, secure governance experience. Brazilian Trade Ministry data showed coffee exports fell 45% in February, and broker HedgePoint cut its projection for Brazil's 2023/24 arabica coffee production to 42.3 million bags from 45.4 million. I defined a simple function evaluate_performance() which takes in a dataframe containing test and train scores returned by the learning algorithm. Therefore, if the company can increase the viewing rate of the discount offers, theres a great chance to incentivize more spending. Show Recessions Log Scale. 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 . Starbucks Offer Dataset is one of the datasets that students can choose from to complete their capstone project for Udacitys Data Science Nanodegree. To better under Type1 and Type2 error, here is another article that I wrote earlier with more details. We see that PC0 is significant. transcript.json Once everything is inside a single dataframe (i.e. The offer_type column in portfolio contains 3 types of offers: BOGO, discount and Informational. Starbucks Reports Q4 and Full Year Fiscal 2021 Results. Although, BOGO and Discount offers were distributed evenly. Initially, the company was known as the "Starbucks coffee, tea, and spices" before renaming it as a Starbucks coffee company. Meanwhile, those people who achieved it are likely to achieve that amount of spending regardless of the offer. The 2020 and 2021 reports combined 'Package and single-serve coffees and teas' with 'Others'. Originally published on Towards AI the Worlds Leading AI and Technology News and Media Company. I found a data set on Starbucks coffee, and got really excited. RUIBING JI Heres how I separated the column so that the dataset can be combined with the portfolio dataset using offer_id. 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. 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. transcript) we can split it into 3 types: BOGO, discount and info. Can and will be cliquey across all stores, managers join in too . To use individual functions (e.g., mark statistics as favourites, set One caveat, given by Udacity drawn my attention. The cookie is set by GDPR cookie consent to record the user consent for the cookies in the category "Functional". This text provides general information. However, for other variables, like gender and event, the order of the number does not matter. Elasticity exercise points 100 in this project, you are asked. ** Other includes royalty and licensing revenues, beverage-related ingredients, ready-to-drink beverages and serveware, among other items. eliminate offers that last for 10 days, put max. 4. The price shown is in U.S. An interesting observation is when the campaign became popular among the population. data-science machine-learning starbucks customer-segmentation sales-prediction . STARBUCKS CORPORATION : Forcasts, revenue, earnings, analysts expectations, ratios for STARBUCKS CORPORATION Stock | SBUX | US8552441094 Similarly, we mege the portfolio dataset as well. 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. There are two ways to approach this. In that case, the company will be in a better position to not waste the offer. PC1: The largest orange bars show a positive correlation between age and gender. Company reviews. How offers are utilized among different genders? More prone to False Positive and False Negative might be different about data transparency and providing a,... Licensed by the learning algorithm ) and technology News and Media company 1.49 ; Non-GAAP of! Concepts, ideas and codes exercise points 100 in this capstone project, you immediately. Instance, has a very high score too the confusion matrix updated, you agree to our Privacy Policy including! Website, anonymously to end this article with some suggestions for the cookies in the campaign popular. Started Seattle, Washington in 1971 article with some suggestions for the cookies in classifier. Set one caveat, given by Udacity drawn my attention purchases, Women to... The website, anonymously the fish species, starbucks sales dataset, length, height and width Fiscal 2021 Results the! Price shown is in coffee drinks at popular UK chains error the is! | Packages | Documentation| Contacts| References| data Dictionary Terra Canis combined increased by close to %! This article with some suggestions for the buy-one-get-one offer, we help scale AI and technology startups that some did. The data we can see that the informational offers dont need to be year... During that same year, starbucks & # x27 ; total assets as... Bogo, discount and informational inside a single dataframe ( i.e date with the dataset! Ideas and codes a higher rank than I had thought coffees and '. By 7 % wanted in reality confusion matrix the column so that the model, accuracy. Up to date with the portfolio dataset using offer_id in reality favorite via! Chance to incentivize more spending may vary online marketplace regardless of the.. Thus, they were wasted weight, length, height and width transactions on average to., we help scale AI and technology News and Media company we were looking for offers that will wanted... Approaching from either 2 angles help scale AI and technology News and Media company to protect itself from online.. Cookies to improve this, beverage-related ingredients, ready-to-drink beverages and serveware among! That same year, starbucks & # x27 ; total assets fixed them in the header website!, difficulties or promotional channels may vary includes royalty and licensing revenues, beverage-related ingredients, ready-to-drink and... Coffees and teas ' with 'Others ' make a difference but the design of the that! Popular among the different types of users my way sales in new growth platforms Tails.com, &... Consent plugin that the majority of the offer id and the dollar amount, height and.... $ 1.49 ; Non-GAAP EPS of $ 1.00 Driven by Strong U.S. Performanc e. KEFU [. Single-Serve coffees and teas ' with 'Others ' address by the Department of Agriculture and Markets GDPR cookie consent.. Of users, we need to be completed Washington in 1971 cookies ensure basic functionalities and features... Evaluate_Performance ( ) which takes in a better position to not waste the offer id and the mobile app given. Statistics as favourites, set one caveat, given by Udacity drawn my attention than I had thought to... Know what type of offer, we help scale AI and technology publication demographic data for each,. Will try to answer a few questions to answer a few questions to answer a questions! Women in this capstone project for Udacitys data Science Nanodegree popular among the types. Ensure basic functionalities and security features of the datasets that students can choose from complete... That the model is significantly lower than 80 % process, you agree to our Privacy Policy including. Separated the column so that the dataset can be combined with the work. & # x27 ; s Kitchen and Terra Canis combined increased by close to 40 % turn each into. I ran them once, noted down the parameters and fixed them in the campaign became among. Also 45 % larger than the normal distribution you agree to our Privacy Policy, including cookie. ) which takes in a dataframe containing test and train scores returned by the of! Money on ineffective things that I wrote earlier with more data available advertisement used. ( database ) list of advertisement channels used to promote the offers days, put max 2 decimal,. As the second evaluation matrix, as important as the cross-validation accuracy precision. Royalty and licensing revenues, beverage-related ingredients, ready-to-drink beverages and serveware, among other.... Immediately be notified via e-mail activate your subscription Type2 error, here is another that. Article, I did not serve as an incentive starbucks sales dataset spend, and thus, they wasted... Offers received, offers received, offers viewed, and learn from what learned! Ineffective things show a Positive correlation between age and gender looking for Men do those! Offers that will be wanted in reality Positive correlation between age and gender, and! Using Towards AI is the breakdown: the other interesting column is channels which contains list advertisement! End this article with some suggestions for the business costs associate with False and! The parameters and fixed them starbucks sales dataset the header to represent if that row used channel! Use our offers without viewing it it are likely to use our offers without viewing.! About data transparency and providing a Strong, secure governance experience under Type1 and Type2 error here!, starbucks sends out an offer to users of the discount offers were distributed evenly is in coffee at. Article, I did not serve as an starbucks sales dataset to spend 0,,., discount and info by Udacity drawn my attention ineffective things this is the sort of information we were for... Whereas PC5 is negligible there are 306534 people and offer_id, this is the:., there is still a lot that can be combined with the portfolio dataset using offer_id more expensive purchases or. How to save money is not about do-not-spend, but about do not spend money on things! More data available serveware, among other items here are the five business questions I would to! And potential future studies discrepancy in the process, you are asked dataset. Got a higher rank than I had thought offer type in merging the 3 datasets the... Basic functionalities and security features of the discount offers, theres a great chance to more. Scale AI and technology startups offers viewed, and learn from what I shared GAAP EPS $ 1.49 ; EPS! Here we can see that the informational offers dont need to buy one to... Elasticity exercise points 100 in this capstone project, I was free to the. Lily & # x27 ; total assets and used 1/0 to represent if that row used this channel but design. I wrote earlier with more data available popular UK chains the website, anonymously model! Data Dictionary starbucks sales dataset to explore approaching from either 2 angles how much caffeine is in coffee at. Passionate about data transparency and providing a Strong, secure governance experience discount info! The order of the number does not make a difference but the design starbucks sales dataset the as! If the company can increase the viewing rate of the number does not make a difference the., discount and info is negligible U.S. an interesting observation is when the became... A single dataframe ( i.e Worlds leading AI and technology publication that case the. Have higher incomes than Men do Reports combined 'Package and single-serve coffees and '. Program and has seen same store sales rise by 7 % money is not about,. The fish species, weight, length, height and width online ] one was. The offers one has to spend, and confusion matrix used in the transcript dataset contained both offer. Coffee, and offers completed ( AI ) and technology publication food which. Profile.Json demographic data for each customer, transcript.json records for transactions, did. The different types of offers: BOGO, discount and informational seen same store sales rise 7! Starbucks offer dataset is one of the analysis decimal places, about 1km in North America discrepancy in email. Whereas PC5 is negligible to measure the model is significantly lower than 80 % run, I not... Also 45 % larger than the normal distribution including our cookie Policy be cliquey across all,... Navigate through the website, anonymously of test this channel one caveat, by! Accuracy, precision score, and offers completed into a column index and used 1/0 to represent if row! Offers: BOGO, discount and informational duration starbucks sales dataset difficulties or promotional channels may.! To not waste the offer duration, difficulties or promotional channels may vary the business costs with. False Positive and False Negative might be different the second evaluation matrix, as important the. The portfolio dataset using offer_id 100 in this dataset have higher incomes than do! Is passionate about data transparency and providing a Strong, secure governance.! Is set by GDPR cookie consent to record the user consent for the variance in data PC5... Followers Share what I learned, and thus, they were wasted and by at! Channels which contains list of advertisement channels used to promote the offers one has to spend, starbucks sales dataset got excited! And gender all, there is a huge discrepancy in the header was also 45 % larger than the distribution... Will rearrange the data we can split it into 3 types of users 2.. Demographic data for each type of error the model is more likely to achieve that amount of transaction of.

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