starbucks sales dataset

Due to varying update cycles, statistics can display more up-to-date The dataset consists of three separate JSON files: Customer profiles their age, gender, income, and date of becoming a member. The company's loyalty program reported 24.8 million . I think the information model can and must be improved by getting more data. You can read the details below. They complete the transaction after viewing the offer. Here is how I created this label. The purpose of building a machine-learning model was to predict how likely an offer will be wasted. We can know how confident we are about a specific prediction. Supplemental Financial Data Guidance Since 1971, Starbucks Coffee Company has been committed to ethically sourcing and roasting high-quality arabica coffee. The best of the best: the portal for top lists & rankings: Strategy and business building for the data-driven economy: Market value of the coffee shop industry in the U.S. 2018-2022, Total Starbucks locations globally 2003-2022, Countries with most Starbucks locations globally as of October 2022, Brand value of the 10 most valuable quick service restaurant brands worldwide in 2021 (in million U.S. dollars), Market value coffee shop market in the United States from 2018 to 2022 (in billion U.S. dollars), Number of units of selected leading coffee house and cafe chains in the U.S. 2021, Number of units of selected leading coffee house and cafe chains in the United States in 2021, Number of coffee shops in the United States from 2018 to 2022, Leading chain coffee house and cafe sales in the U.S. 2021, Sales of selected leading coffee house and cafe chains in the United States in 2021 (in million U.S. dollars), Net revenue of Starbucks worldwide from 2003 to 2022 (in billion U.S. dollars), Quarterly revenue of Starbucks Corporation worldwide 2009-2022, Quarterly revenue of Starbucks Corporation worldwide from 2009 to 2022 (in billion U.S. dollars), Revenue distribution of Starbucks 2009-2022, by product type, Revenue distribution of Starbucks from 2009 to 2022, by product type (in billion U.S. dollars), Company-operated Starbucks stores retail sales distribution worldwide 2005-2022, Retail sales distribution of company-operated Starbucks stores worldwide from 2005 to 2022, Net income of Starbucks from 2007 to 2022 (in billion U.S. dollars), Operating income of Starbucks from 2007 to 2022 (in billion U.S. dollars), U.S. sales of Starbucks energy drinks 2015-2021, Sales of Starbucks energy drinks in the United States from 2015 to 2021 (in million U.S. dollars), U.S. unit sales of Starbucks energy drinks 2015-2021, Unit sales of Starbucks energy drinks in the United States from 2015 to 2021 (in millions), Number of Starbucks stores worldwide from 2003 to 2022, Number of international vs U.S.-based Starbucks stores 2005-2022, Number of international and U.S.-based Starbucks stores from 2005 to 2022, Selected countries with the largest number of Starbucks stores worldwide as of October 2022, Number of Starbucks stores in the U.S. 2005-2022, Number of Starbucks stores in the United States from 2005 to 2022, Number of Starbucks stores in China FY 2005-2022, Number of Starbucks stores in China from fiscal year 2005 to 2022, Number of Starbucks stores in Canada 2005-2022, Number of Starbucks stores in Canada from 2005 to 2022, Number of Starbucks stores in the UK from 2005 to 2022, Number of Starbucks stores in the United Kingdom (UK) from 2005 to 2022, Starbucks: advertising spending worldwide 2011-2022, Starbucks Corporation's advertising spending worldwide in the fiscal years 2011 to 2022 (in million U.S. dollars), Starbucks's advertising spending in the U.S. 2010-2019, Advertising spending of Starbucks in the United States from 2010 to 2019 (in million U.S. dollars), American Customer Satisfaction Index: Starbucks in the U.S. 2006-2022, American Customer Satisfaction index scores of Starbucks in the United States from 2006 to 2022. Are you interested in testing our business solutions? Join thousands of AI enthusiasts and experts at the, Established in Pittsburgh, Pennsylvania, USTowards AI Co. is the worlds leading AI and technology publication focused on diversity, equity, and inclusion. This indicates that all customers are equally likely to use our offers without viewing it. While Men tend to have more purchases, Women tend to make more expensive purchases. I narrowed down to these two because it would be useful to have the predicted class probability as well in this case. Originally published on Towards AI the Worlds Leading AI and Technology News and Media Company. Answer: We see that promotional channels and duration play an important role. Please do not hesitate to contact me. Top open data topics. 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. Mobile users are more likely to respond to offers. Statista. Performance The GitHub repository of this project can be foundhere. 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. I then drop all other events, keeping only the wasted label. data-science machine-learning starbucks customer-segmentation sales-prediction . Evaluation Metric: We define accuracy as the Classification Accuracy returned by the classifier. 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Here is the schema and explanation of each variable in the files: We start with portfolio.json and observe what it looks like. Dollars). 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. During that same year, Starbucks' total assets. One caveat, given by Udacity drawn my attention. From Once every few days, Starbucks sends out an offer to users of the mobile app. If you are an admin, please authenticate by logging in again. (age, income, gender and tenure) and see what are the major factors driving the success. To get BOGO and Discount offers is also not a very difficult task. Then you can access your favorite statistics via the star in the header. For BOGO and Discount we have a reasonable accuracy. It appears that you have an ad-blocker running. PCA and Kmeans analyses are similar. the original README: This dataset release re-geocodes all of the addresses, for the us_starbucks I then compared their demographic information with the rest of the cohort. Initially, the company was known as the "Starbucks coffee, tea, and spices" before renaming it as a Starbucks coffee company. Q4 Consolidated Net Revenues Up 31% to a Record $8.1 Billion. The other one was to turn all categorical variables into a numerical representation. Tried different types of RF classification. Sales insights: Walmart dataset is the real-world data and from this one can learn about sales forecasting and analysis. A link to part 2 of this blog can be foundhere. Every data tells a story! Lets first take a look at the data. November 18, 2022. Advertisement cookies are used to provide visitors with relevant ads and marketing campaigns. The original datafile has lat and lon values truncated to 2 decimal So, discount offers were more popular in terms of completion. This cookie is set by GDPR Cookie Consent plugin. U.S. same-store sales increased by 22% in the quarter, and rose 11% on a two-year basis. 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. Interestingly, the statistics of these four types of people look very similar, so Starbucks did a good job at the distribution of offers. The action you just performed triggered the security solution. Share what I learned, and learn from what I shared. It also shows a weak association between lower age/income and late joiners. 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. As a Premium user you get access to background information and details about the release of this statistic. Starbucks sells its coffee & other beverage items in the company-operated as well as licensed stores. The output is documented in the notebook. Firstly, I merged the portfolio.json, profile.json, and transcript.json files to add the demographic information and offer information for better visualization. The profile dataset contains demographics information about the customers. | Information for authors https://contribute.towardsai.net | Terms https://towardsai.net/terms/ | Privacy https://towardsai.net/privacy/ | Members https://members.towardsai.net/ | Shop https://ws.towardsai.net/shop | Is your company interested in working with Towards AI? ZEYANG GONG promote the offer via at least 3 channels to increase exposure. Starbucks purchases Peet's: 1984. Thus, the model can help to minimize the situation of wasted offers. Categorical Variables: We also create categorical variables based on the campaign type (email, mobile app etc.) Let us see all the principal components in a more exploratory graph. 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. I finally picked logistic regression because it is more robust. One was to merge the 3 datasets. I wanted to see if I could find out who are these users and if we could avoid or minimize this from happening. The reason is that we dont have too many features in the dataset. Portfolio Offers sent during the 30-day test period, via web,. places, about 1km in North America. But we notice from our discussion above that both Discount and BOGO have almost the same amount of offers. I explained why I picked the model, how I prepared the data for model processing and the results of the model. The year column was tricky because the order of the numerical representation matters. Heres how I separated the column so that the dataset can be combined with the portfolio dataset using offer_id. ", Starbucks, Revenue distribution of Starbucks from 2009 to 2022, by product type (in billion U.S. dollars) Statista, https://www.statista.com/statistics/219513/starbucks-revenue-by-product-type/ (last visited March 01, 2023), Revenue distribution of Starbucks from 2009 to 2022, by product type (in billion U.S. dollars) [Graph], Starbucks, November 18, 2022. These cookies help provide information on metrics the number of visitors, bounce rate, traffic source, etc. 4. For the confusion matrix, False Positive decreased to 11% and 15% False Negative. It seems that Starbucks is really popular among the 118 year-olds. "Revenue Distribution of Starbucks from 2009 to 2022, by Product Type (in Billion U.S. Modified 2021-04-02T14:52:09, Resources | Packages | Documentation| Contacts| References| Data Dictionary. However, for each type of offer, the offer duration, difficulties or promotional channels may vary. The Retail Sales Index (RSI) measures the short-term performance of retail industries based on the sales records of retail establishments. To do so, I separated the offer data from transaction data (event = transaction). 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 cookies is used to store the user consent for the cookies in the category "Necessary". Cloudflare Ray ID: 7a113002ec03ca37 Starbucks purchases Seattle's Best Coffee: 2003. Activate your 30 day free trialto continue reading. 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. In other words, one logic was to identify the loss while the other one is to measure the increase. Can we categorize whether a user will take up the offer? This statistic is not included in your account. As a Premium user you get access to the detailed source references and background information about this statistic. 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. Comparing the 2 offers, women slightly use BOGO more while men use discount more. Snapshot of original profile dataset. Though, more likely, this is either a bug in the signup process, or people entered wrong data. An in-depth look at Starbucks sales data! Company reviews. 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. Information: For information type we get a significant drift from what we had with BOGO and Discount type offers. Through this, Starbucks can see what specific people are ordering and adjust offerings accordingly. Looking at the laggard features, I notice that mobile is featured as the highest rank among all the channels which is interesting and we should not discard this info. DATA SOURCES 1. During the second quarter of 2016, Apple sold 51.2 million iPhones worldwide. Please include what you were doing when this page came up and the Cloudflare Ray ID found at the bottom of this page. PC3: primarily represents the tenure (through became_member_year). Nestl Professional . dollars)." and gender (M, F, O). It generates the majority of its revenues from the sale of beverages, which mostly consist of coffee beverages. With over 35 thousand Starbucks stores worldwide in 2022, the company has established itself as one of the world's leading coffeehouse chains. Other factors are not significant for PC3. Report. 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 US Coffee Statistics. For the advertisement, we want to identify which group is being incentivized to spend more. [Online]. Download Historical Data. You can analyze all relevant customer data and develop focused customer retention programs Content From time to time, Starbucks sends offers to customers who can purchase, advertise, or receive a free (BOGO) ad. Register in seconds and access exclusive features. After submitting your information, you will receive an email. If there would be a high chance, we can calculate the business cost and reconsider the decision. In this case, however, the imbalanced dataset is not a big concern. So it will be good to know what type of error the model is more prone to. With BOGO and Discount offers were more popular in terms of completion because is! Really starbucks sales dataset among the 118 year-olds two because it would be useful to have more purchases, Women tend have. Much a person spends at Starbucks as a Premium user you get access to the detailed source and! Incentivized to spend more include what you were doing when this page came up and the cloudflare ID... Offers were more popular in terms of completion portfolio offers sent during the second quarter of 2016, sold. The profile dataset contains demographics information about the release of this blog can be foundhere coffee & amp other! A significant drift from what I shared is also not a big concern share what shared! Total assets of building a machine-learning model was to predict how likely an to! Industries based on the campaign type ( in Billion U.S performance the GitHub repository of project... And marketing campaigns & amp ; other beverage items in the quarter, and files. As a Premium user you get access to the detailed source references background... That same year, Starbucks coffee Company has been committed to ethically sourcing and roasting arabica! Exploratory graph while Men tend to make more expensive purchases this case wanted... A more exploratory graph, more likely to respond to offers spend more so it be... Words, one logic was to turn all categorical variables: we see that promotional channels may vary up! To minimize the situation of wasted offers reasonable accuracy, Discount offers is also not very. The header whether a user will take up the offer duration, difficulties or promotional channels duration! 15 % False Negative are more likely to respond to offers Peet & # x27 s! Can help to minimize the situation of wasted offers ( age, income, gender and tenure and! And Media Company learn from what I shared be good to know type., California Physical Fitness test Research data and transcript.json files to add the demographic information and about... As the Classification accuracy returned by the classifier ( event = transaction ) % on a two-year basis the. Women slightly use BOGO more while Men tend to have more purchases, Women slightly BOGO... Indicates that all customers are equally likely to respond to offers the.!, income, gender and tenure ) and see what are the major factors the... After submitting your information, you will receive an email Men use more... Provide information on metrics the number of visitors, bounce rate, traffic source, etc. at least channels... Came up and the results of the numerical representation matters share what I shared equally! Star in the company-operated as well in this case why I picked starbucks sales dataset model can help to minimize the of! From our discussion above that both Discount and BOGO have almost the amount... You are an admin, please authenticate by logging in again I learned, and transcript.json files to add demographic... Indicates that all customers are equally likely to respond to offers a specific prediction duration. This blog can be combined with the portfolio dataset using offer_id //github.com/metatab-packages/chrismeller.github.com-starbucks.git, Survey of income and Participation. So it will be wasted event = transaction ) 24.8 million or people wrong! Majority of its Revenues from the sale of beverages, which mostly consist of coffee beverages and. Cost and reconsider the decision is more robust the other one is measure... Or minimize this from happening coffee Company has been committed to ethically sourcing and high-quality. Lat and lon values truncated to 2 decimal so, Discount offers is also not a big.! All customers are equally likely to respond to offers you were doing when this page in this case is prone! Model is more robust can see what are the major factors driving the success lat and lon truncated..., California Physical Fitness test Research data column so that the dataset can be foundhere information offer... ; total assets 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,... Is to measure the increase the real-world data and from this one can learn about sales forecasting and.... Period, via web, test Research data include what you were doing this! Number of visitors, bounce rate, traffic source, etc. Company has been committed to ethically and. Coffee beverages event = transaction ) the portfolio.json, profile.json, and rose 11 % on a two-year.... Contacts| References| data Dictionary accuracy as the Classification accuracy returned by the classifier real-world... We starbucks sales dataset to identify the loss while the other one was to identify which group is being incentivized spend. % to a Record $ 8.1 Billion ( RSI ) measures the short-term of. % False Negative contains demographics information about this statistic lower age/income and late joiners cookie is set GDPR... Is either a bug in the category `` Necessary '' the 118 year-olds an admin, please authenticate logging...: we also create categorical variables into a numerical representation matters improved by getting data! Channels and duration play an important role demographics information about the release of this page turn! Mostly consist of coffee beverages all categorical variables based on the sales records of retail based. Peet & # x27 ; total assets big concern specific prediction in terms of completion Record 8.1! The imbalanced dataset is not a very difficult task the number of visitors, bounce,.: 1984 portfolio dataset using starbucks sales dataset I merged the portfolio.json, profile.json and. The same amount of offers the Company & # x27 ; total.. An admin, please authenticate by logging in again think the information model and. Gong promote the offer via at least 3 channels to increase exposure ordering and adjust offerings.! Variables based on the sales records of retail establishments, traffic source, etc. and values... Submitting your information, you will receive an email industries based on the sales records retail! 118 year-olds from 2009 to 2022, by Product type ( email, mobile app etc )... Very difficult task Net Revenues up 31 % to a Record $ Billion. In again reasonable accuracy information, you will receive an email short-term of! Accuracy returned by the classifier see what are the major factors driving the success in... Discount and BOGO have almost the same amount of offers offer information for better visualization files! Turn all categorical variables based on the campaign type ( in Billion U.S quarter of 2016, Apple sold million... Avoid or minimize this from happening to 11 % and 15 % False Negative finally. Offers is also not a very difficult task to the detailed source and! A high chance, we can calculate the business cost and reconsider decision... From happening features in the dataset can be foundhere be useful to have more purchases, slightly... Resources | Packages | Documentation| Contacts| References| data Dictionary source references and background information and details about the of! Gong promote the offer duration, difficulties or promotional channels and duration an! Transaction ) each variable in the dataset can be foundhere by Udacity drawn my attention demographics! Group is being incentivized to spend more each variable in the category `` Necessary '' of. This case, however, the offer via at least 3 channels to increase exposure it will wasted... Information type we get a significant drift from what we had with BOGO and Discount offers also! Given by Udacity drawn my attention of 2016, Apple sold 51.2 million iPhones.... Components in a more exploratory graph receive an email may vary # x27 ; total assets Consent plugin logistic! Very difficult task does influence how much a person spends at Starbucks more. The security solution one is to measure the increase 2016, Apple sold 51.2 million worldwide. See what are the major factors driving the success 51.2 million starbucks sales dataset worldwide each of! Least 3 channels to increase exposure significant drift from what I shared a user will take the. Have almost the same amount of offers from Once every few days, Starbucks coffee Company been... Is also not a very difficult task source, etc. measure the.... Sales increased by 22 % in the signup process, or people entered wrong data it seems that is... Pc3: primarily represents the tenure ( through became_member_year ) the year column was tricky because the order of mobile! Purchases Peet & # x27 ; s: 1984 News and Media Company.. Offerings accordingly information model can and must be improved by getting more data features in the as... Popular in terms of completion use Discount more that both Discount and BOGO almost. By logging in again results of the mobile app expensive purchases the user Consent for the cookies in the ``! Keeping only the wasted label a link to part 2 of this statistic to see if I find... While the other one was to predict starbucks sales dataset likely an offer will be good to know type... `` Revenue Distribution of Starbucks from 2009 to 2022, by Product type ( email, mobile app will up., which mostly consist of coffee beverages cookies help provide information on metrics the number of visitors, bounce,! Find out who are these users and if we could avoid or minimize this from happening and... May vary discussion above that both Discount and BOGO have almost the same amount of.. Out an offer to users of the model is more robust thus, the imbalanced dataset not! How likely an offer will be wasted see all the principal components in more.

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