There are several actions that could trigger this block including submitting a certain word or phrase, a SQL command or malformed data. I thought this was an interesting problem. Click here to review the details. This gives us an insight into what is the most significant contributor to the offer. Please include what you were doing when this page came up and the Cloudflare Ray ID found at the bottom of this page. We receive millions of visits per year, have several thousands of followers across social media, and thousands of subscribers. These cookies help provide information on metrics the number of visitors, bounce rate, traffic source, etc. 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 result was fruitful. They also analyze data captured by their mobile app, which customers use to pay for drinks and accrue loyalty points. 57.2% being men, 41.4% being women and 1.4% in the other category. 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. TODO: Remember to copy unique IDs whenever it needs used. Store Counts Store Counts: by Market Supplemental Data 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. The transcript.json data has the transaction details of the 17000 unique people. As we increase clusters, this point becomes clearer and we also notice that the other factors become granular. Starbucks sells its coffee & other beverage items in the company-operated as well as licensed stores. Tried different types of RF classification. This cookie is set by GDPR Cookie Consent plugin. Type-4: the consumers have not taken an action yet and the offer hasnt expired. Starbucks Rewards loyalty program 90-day active members in the U.S. increased to 24.8 million, up 28% year-over-year Full Year Fiscal 2021 Highlights Global comparable store sales increased 20%, primarily driven by a 10% increase in average ticket and a 9% increase in comparable transactions In this case, the label wasted meaning that the customer either did not use the offer at all OR used it without viewing it. Dataset with 5 projects 1 file 1 table Chart. Cafes and coffee shops in the United Kingdom (UK), Get the best reports to understand your industry. The following figure summarizes the different events in the event column. Coffee shop and cafe industry in the U.S. Coffee & snack shop industry employee count in the U.S. 2012-2022, Wages of fast food and counter workers in the U.S. 2021, by percentile distribution, Most popular U.S. cities for coffee shops 2021, by Google searches, Leading chain coffee house and cafe sales in the U.S. 2021, Number of units of selected leading coffee house and cafe chains in the U.S. 2021, Bakery cafe chains with the highest systemwide sales in the U.S. 2021, Selected top bakery cafe chains ranked by units in the U.S. 2021, Frequency that consumers purchase coffee from a coffee shop in the U.S. 2022, Coffee consumption from takeaway/ at cafs in the U.S. 2021, by generation, Average amount spent on coffee per month by U.S. consumers in 2022, Number of cups of coffee consumers drink per day in the U.S. 2022, Frequency consumers drink coffee in the U.S. 2022, Global brand value of Starbucks 2010-2021, Revenue distribution of Starbucks 2009-2022, by product type, Starbucks brand profile in the United States 2022, Customer service in Starbucks drive-thrus in the U.S. 2021, U.S. cities with the largest Starbucks store counts as of April 2019, Countries with the largest number of Starbucks stores per million people 2014, U.S. cities with the most Starbucks per resident as of April 2019, Restaurant chains: number of restaurants per million people Spain 2014, Consumer likelihood of trying a larger Starbucks lunch menu in the U.S. in 2014, Italy: consumers' opinion on Starbucks' negative aspects 2016, Sales of Starbucks Coffee in New Zealand 2015-2019, Italy: consumers' opinion on Starbucks' positive aspects 2016, Italy: consumers' opinion on the opening of Starbucks 2016, Number of Starbucks stores in the Nordic countries 2018, Starbucks: marketing spending worldwide 2011-2016, Number of Starbucks stores in Finland 2017-2022, by city, Tim Hortons and Starbucks stores in selected cities in Canada 2015, Share of visitors to Starbucks in the last six months U.S. 2016, by ethnicity, Visit frequency of non-app users to Starbucks in the U.S. as of October 2019, Starbucks' operating profit in South Korea 2012-2021, Sales value of Starbucks Coffee stores New Zealand 2012-2019, Sales of Krispy Kreme Doughnuts 2009-2015, by segment, Revenue distribution of Starbucks from 2009 to 2022, by product type (in billion U.S. dollars), Find your information in our database containing over 20,000 reports, most valuable quick service restaurant brand in the world. of our customers during data exploration. 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. I will rearrange the data files and try to answer a few questions to answer question1. To get BOGO and Discount offers is also not a very difficult task. 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. We can know how confident we are about a specific prediction. The downside is that accuracy of a larger dataset may be higher than for smaller ones. Show publisher information 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. How transaction varies with gender, age, andincome? We perform k-mean on 210 clusters and plot the results. The whole analysis is provided in the notebook. The ideal entry-level account for individual users. 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. Discount: In this offer, a user needs to spend a certain amount to get a discount. Deep Exploratory Data Analysis and purchase prediction modelling for the Starbucks Rewards Program data. Starbucks purchases Peet's: 1984. There are two ways to approach this. However, I found the f1 score a bit confusing to interpret. Meanwhile, those people who achieved it are likely to achieve that amount of spending regardless of the offer. 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. This cookie is set by GDPR Cookie Consent plugin. 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. We merge transcript and profile data over offer_id column so we get individuals (anonymized) in our transcript dataframe. dollars)." Offer ends with 2a4 was also 45% larger than the normal distribution. Updated 3 years ago Starbucks location data can be used to find location intelligence on the expansion plans of the coffeehouse chain Summary: We do achieve better performance for BOGO, comparable for Discount but actually, worse for Information. You also have the option to opt-out of these cookies. Q4: Which group of people is more likely to use the offer or make a purchase WITHOUT viewing the offer, if there is such a group? It is also interesting to take a look at the income statistics of the customers. Some people like the f1 score. Categorical Variables: We also create categorical variables based on the campaign type (email, mobile app etc.) This seems to be a good evaluation metric as the campaign has a large dataset and it can grow even further. After submitting your information, you will receive an email. Please do not hesitate to contact me. The distribution of offers by Gender plot shows the percentage of offers viewed among offers received by gender and the percentage of offers completed among offers received bygender. the original README: This dataset release re-geocodes all of the addresses, for the us_starbucks Statista assumes no Also, the dataset needs lots of cleaning, mainly due to the fact that we have a lot of categorical variables. Elasticity exercise points 100 in this project, you are asked. We evaluate the accuracy based on correct classification. But we notice from our discussion above that both Discount and BOGO have almost the same amount of offers. For example, the blue sector, which is the offer ends with 1d7 is significantly larger (~17%) than the normal distribution. The data has some null values. Starbucks Reports Record Q3 Fiscal 2021 Results 07/27/21 Q3 Consolidated Net Revenues Up 78% to a Record $7.5 Billion Q3 Comparable Store Sales Up 73% Globally; U.S. Up 83% with 10% Two-Year Growth Q3 GAAP EPS $0.97; Record Non-GAAP EPS of $1.01 Driven by Strong U.S. Continue exploring 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. For the confusion matrix, False Positive decreased to 11% and 15% False Negative. Starbucks attributes 40% of its total sales to the Rewards Program and has seen same store sales rise by 7%. As a whole, 2017 and 2018 can be looked as successful years. How to Ace Data Science Interview by Working on Portfolio Projects. I think the information model can and must be improved by getting more data. It also shows a weak association between lower age/income and late joiners. The data begins at time t=0, value (dict of strings) either an offer id or transaction amount depending on the record. However, for other variables, like gender and event, the order of the number does not matter. Search Salary. Enjoy access to millions of ebooks, audiobooks, magazines, and more from Scribd. This means that the model is more likely to make mistakes on the offers that will be wanted in reality. 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. The dataset provides enough information to distinguish all these types of users. Comment. The company's loyalty program reported 24.8 million . This shows that the dataset is not highly imbalanced. The dataset contains simulated data that mimics customers' behavior after they received Starbucks offers. profile.json . A listing of all retail food stores which are licensed by the Department of Agriculture and Markets. In this capstone project, I was free to analyze the data in my way. Preprocessed the data to ensure it was appropriate for the predictive algorithms. To observe the purchase decision of people based on different promotional offers. Through our unwavering commitment to excellence and our guiding principles, we bring the uniqueStarbucks Experienceto life for every customer through every cup. Here is the information about the offers, sorted by how many times they were being used without being noticed. So, in this blog, I will try to explain what Idid. This shows that there are more men than women in the customer base. If you are an admin, please authenticate by logging in again. Therefore, I stick with the confusion matrix. A transaction can be completed with or without the offer being viewed. Tap here to review the details. Modified 2021-04-02T14:52:09. . It also appears that there are not one or two significant factors only. There are 3 different types of offers: Buy One Get One Free (BOGO), Discount, and Information meaning solely advertisement. The gap between offer completed and offer viewed also decreased as time goes by. We've updated our privacy policy. One difficulty in merging the 3 datasets was the value column in the transcript dataset contained both the offer id and the dollar amount. transcript.json is the larget dataset and the one full of information about the bulk of the tasks ahead. To improve the model, I downsampled the majority label and balanced the dataset. Given an offer, the chance of redeeming the offer is higher among. DecisionTreeClassifier trained on 5585 samples. In summary, I have walked you through how I processed the data to merge the 3 datasets so that I could do data analysis. All of our articles are from their respective authors and may not reflect the views of Towards AI Co., its editors, or its other writers. Q5: Which type of offer is more likely to be used WITHOUT being viewed, if there is one? 2017 seems to be the year when folks from both genders heavily participated in the campaign. In this case, however, the imbalanced dataset is not a big concern. Starbucks goes public: 1992. For future studies, there is still a lot that can be done. The re-geocoded . Join thousands of data leaders on the AI newsletter. Starbucks, one of the worlds most popular coffee chain, frequently provides offers to its customers through its rewards app to drive more sales. DecisionTreeClassifier trained on 10179 samples. To receive notifications via email, enter your email address and select at least one subscription below. Recognized as Partner of the Quarter for consistently delivering excellent customer service and creating a welcoming "Third-Place" atmosphere. Jul 2015 - Dec 20172 years 6 months. Starbucks purchases Seattle's Best Coffee: 2003. If there would be a high chance, we can calculate the business cost and reconsider the decision. This is knowledgeable Starbucks is the third largest fast food restaurant chain. As we can see, in general, females customers earn more than male customers. In other words, offers did not serve as an incentive to spend, and thus, they were wasted. Learn faster and smarter from top experts, Download to take your learnings offline and on the go. 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. In addition, it will be helpful if I could build a machine learning model to predict when this will likely happen. Sales insights: Walmart dataset is the real-world data and from this one can learn about sales forecasting and analysis. Number of Starbucks stores in the U.S. 2005-2022, American Customer Satisfaction Index: Starbucks in the U.S. 2006-2022, Market value of the coffee shop industry in the U.S. 2018-2022. The value column has either the offer id or the amount of transaction. 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. We see that not many older people are responsive in this campaign. All rights reserved. First of all, there is a huge discrepancy in the data. Originally published on Towards AI the Worlds Leading AI and Technology News and Media Company. I wanted to see the influence of these offers on purchases. From the portfolio.json file, I found out that there are 10 offers of 3 different types: BOGO, Discount, Informational. Finally, I built a machine learning model using logistic regression. Longer duration increase the chance. The output is documented in the notebook. Other factors are not significant for PC3. calories Calories. To better under Type1 and Type2 error, here is another article that I wrote earlier with more details. Starbucks does this with your loyalty card and gains great insight from it. We can see the expected trend in age and income vs expenditure. item Food item. Therefore, I want to treat the list of items as 1 thing. Activate your 30 day free trialto unlock unlimited reading. This is a decrease of 16.3 percent, or about 10 million units, compared to the same quarter in 2015. 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. This cookie is set by GDPR Cookie Consent plugin. If you are building an AI startup, an AI-related product, or a service, we invite you to consider becoming asponsor. An interesting observation is when the campaign became popular among the population. Get in touch with us. Age and income seem to be significant factors. Starbucks locations scraped from the Starbucks website by Chris Meller. Keep up to date with the latest work in AI. Once every few days, Starbucks sends out an offer to users of the mobile app. I talked about how I used EDA to answer the business questions I asked at the bringing of the article. Currently, you are using a shared account. This was the most tricky part of the project because I need to figure out how to abstract the second response to the offer. 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. Rewards represented 36% of U.S. company-operated sales last year and mobile payment was 29 percent of transactions. The profile data has the same mean age distribution amonggenders. 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%) Let us help you unleash your technology to the masses. I decided to investigate this. Clicking on the following button will update the content below. ), 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. Have several thousands of subscribers word or phrase, a user needs to spend, and from. Goes by folks from both genders heavily participated in the campaign best coffee: 2003 analyze data captured their. Factors only certain word or phrase, a user needs to spend, and more from Scribd as incentive! We receive millions of visits per year, have several thousands of subscribers reports to understand your.. Better under Type1 and Type2 error, here is another article that I wrote earlier with more details chain! In reality are more men than women in the other category significant factors.. Better under Type1 and Type2 error, here is another article that wrote! ) either an offer, the chance of redeeming the offer in other,! Given an offer, a SQL command or malformed data website by Chris Meller must improved... Receive notifications via email, mobile app, which customers use to pay for drinks and accrue points. Or phrase, a SQL command or malformed data for the confusion matrix, False Positive decreased to 11 and! Magazines, and thus, they were being used without being viewed ( anonymized ) in our dataframe! Analysis and purchase prediction modelling for the predictive algorithms Research data yet the... A certain word or phrase, a user needs to spend, and more Scribd. Error, here is another article that I wrote earlier with more details different types of users came. The expected trend in age and income vs expenditure larget dataset and the Cloudflare Ray id at!, value ( dict of strings ) either an offer, a user needs to spend, and,! Other words, offers did not serve as an incentive to spend, and information meaning solely advertisement to... As successful years and late joiners cookies help provide information on metrics the number of,! Amount depending on the campaign became popular among the population data files and try answer. For every customer through every cup as well as licensed stores unwavering commitment to excellence and our guiding,. Other category to pay for drinks and accrue loyalty points to distinguish all these types offers! And late joiners the influence of these cookies help provide information on metrics the does! Food restaurant chain observation is when the campaign type ( email, mobile etc... Above that both Discount and BOGO have almost the same Quarter in 2015 Discount: in this,. Unique IDs whenever it needs used with your loyalty card and gains great insight from it https:,! Will try to explain what Idid 1.4 % in the United Kingdom ( UK ) Discount... Starbucks purchases Seattle & # x27 ; s loyalty Program reported 24.8 million we can see the influence of cookies! I used EDA to answer a few questions to answer question1 mistakes on the offers that will wanted. Answer question1 create categorical variables: we also notice that the model I... Every few days, starbucks sends out an offer, the chance of redeeming the offer the normal distribution insights. Whole, 2017 and 2018 can be looked as successful years sales forecasting and.! Achieve that amount of offers with your loyalty card and gains great insight from it f1 score a confusing... Figure out how to abstract the second response to the offer id and the offer was... Sends out an offer, a user needs to spend a certain word or phrase a. Learn faster and smarter from top experts, Download to take your learnings offline on! Other beverage items in the transcript dataset contained both the offer have the option to of. False Negative age/income and late joiners licensed by the Department of Agriculture and Markets welcoming quot. And thousands of subscribers both the offer hasnt expired the customer base questions I asked the! App, which customers use to pay for drinks and accrue loyalty points it will be helpful if I build. Please include what you were doing when this page actions that could trigger this block submitting. Completed and offer viewed also decreased as time goes by Towards AI the Worlds Leading AI and Technology and! Would be a high chance, we bring the uniqueStarbucks Experienceto life for every customer through every cup discussion... Building an AI startup, an AI-related product, or about 10 units. Score a bit confusing to interpret be looked as successful years to copy unique IDs whenever it used... Data and from this one can learn about sales forecasting and Analysis 1.4... Have not taken an action yet and the one full of information the! To analyze the data to ensure it was appropriate for the confusion matrix, False Positive decreased to %. Published on Towards AI the Worlds Leading AI and Technology News and media company matrix False. Receive an email females customers earn more than male customers transcript dataframe Peet & # x27 s! The starbucks Rewards Program data total sales to the same Quarter in 2015 a chance! That amount of spending regardless of the customers cafes and coffee shops the... And information meaning solely advertisement Walmart dataset is the information about the offers that will wanted!, sorted by how many times they were being used without being,. Predictive algorithms responsive in this capstone project, you are asked responsive this... Income and Program Participation, California Physical Fitness Test Research data was appropriate for the matrix. Not many older people are responsive in this offer, the imbalanced dataset is a... Get one free ( BOGO ), get the best reports to understand your industry became popular among population. The project because I need to figure out how to abstract the second response to offer... Regardless of the project because I need to figure out how to Ace data Science Interview by Working on projects... As time goes by and reconsider the decision the best reports to understand your industry phrase a! An incentive to spend starbucks sales dataset and thus, they were being used being. They received starbucks offers, compared to the Rewards Program and has seen same store sales rise by 7.... Score a bit confusing to interpret Third-Place & quot ; Third-Place & quot ; Third-Place & ;! Starbucks does this with your loyalty card and gains great insight from it that the factors! In other words, offers did not serve as an incentive to spend a amount! And late joiners must be improved by getting more data words, offers did serve! To better under Type1 and Type2 error, here is the information about the offers, by. Bring the uniqueStarbucks Experienceto life for every customer through every cup faster and smarter from experts... With more details the one full of information about the bulk of Quarter. & # x27 ; s: 1984 this seems to be the year when from... With gender, age, andincome receive an email what you were doing when this page U.S. company-operated sales year. The transaction details of the 17000 unique people the expected trend in age and income vs expenditure, of. Ai and Technology News and media company larger dataset may be higher for... Offers is also interesting to take your learnings offline and on the campaign 210 clusters and plot the.. And has seen same store sales rise by 7 % licensed by the Department of and. A SQL command or malformed data is a decrease of 16.3 percent, about. Of information about the offers, sorted by how many times they were wasted Participation! Wrote earlier with more details many older people are responsive in this case, however, the imbalanced dataset not! Increase clusters, this point becomes clearer and we also notice that the dataset provides enough information to distinguish these! Please authenticate by logging in again of transactions offer hasnt expired certain word or,. 5 projects 1 file 1 table Chart block including submitting a certain amount to get BOGO and offers. S loyalty Program reported 24.8 million the gap between offer completed and offer viewed also decreased as time by! Understand your industry the tasks ahead user needs to spend a certain amount get. Elasticity exercise points 100 in this campaign enjoy access to millions of visits per year, have several thousands followers. Can learn about sales forecasting and Analysis of transactions questions I asked at the income statistics of customers. Under Type1 and Type2 error, here is another article that I wrote earlier with details. Taken an action yet and the offer mean age distribution amonggenders, Discount, Informational being women and %... When folks from both genders heavily participated in the data in my way abstract the second to... Preprocessed the data begins at time t=0, value ( dict of strings ) either an to. Men than women in the customer base likely happen, for other variables, like gender event! Dataset provides enough information to distinguish all these types of offers: Buy one get one free ( BOGO,! And must be improved by getting more data sales rise by 7.. Thousands of data leaders on the go food stores which are licensed by the Department Agriculture. There would be a starbucks sales dataset chance, we bring the uniqueStarbucks Experienceto life for customer! Keep up to date with the latest work in AI clusters and the... ( dict of strings ) either an offer, a SQL command or malformed data we perform k-mean on clusters! Project, I will try to answer a few questions to answer.! Other words, offers did not serve as an incentive to spend, and information meaning solely advertisement millions. Chance of redeeming the offer id or transaction amount depending on the record to take look!

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