One way was to turn each channel into a column index and used 1/0 to represent if that row used this channel. The data file contains 3 different JSON files. Growth was strong across all channels, particularly in e-commerce and pet specialty stores. . The cookies is used to store the user consent for the cookies in the category "Necessary". They complete the transaction after viewing the offer. 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. Then you can access your favorite statistics via the star in the header. The offer_type column in portfolio contains 3 types of offers: BOGO, discount and Informational. In both graphs, red- N represents did not complete (view or received) and green-Yes represents offer completed. Sales in new growth platforms Tails.com, Lily's Kitchen and Terra Canis combined increased by close to 40%. profile.json . Some users might not receive any offers during certain weeks. The dataset consists of three separate JSON files: Customer profiles their age, gender, income, and date of becoming a member. This website is using a security service to protect itself from online attacks. The combination of these columns will help us segment the population into different types. I wanted to see if I could find out who are these users and if we could avoid or minimize this from happening. Environmental, Social, Governance | Starbucks Resources Hub. While Men tend to have more purchases, Women tend to make more expensive purchases. Profit from the additional features of your individual account. This shows that there are more men than women in the customer base. With over 35 thousand Starbucks stores worldwide in 2022, the company has established itself as one of the world's leading coffeehouse chains. In the process, you could see how I needed to process my data further to suit my analysis. So my new dataset had the following columns: Also, I changed the null gender to Unknown to make it a newfeature. Customers spent 3% more on transactions on average. As a Premium user you get access to background information and details about the release of this statistic. Click here to review the details. Introduction. We've updated our privacy policy. age(numeric): numeric column with 118 being unknown oroutlier. Here is how I did it. Now customize the name of a clipboard to store your clips. The cookie is set by the GDPR Cookie Consent plugin and is used to store whether or not user has consented to the use of cookies. Other uncategorized cookies are those that are being analyzed and have not been classified into a category as yet. Income seems to be similarly distributed between the different groups. So, in conclusion, to answer What is the spending pattern based on offer type and demographics? Register in seconds and access exclusive features. data than referenced in the text. I thought this was an interesting problem. You need at least a Starter Account to use this feature. Are you interested in testing our business solutions? Functional cookies help to perform certain functionalities like sharing the content of the website on social media platforms, collect feedbacks, and other third-party features. Elasticity exercise points 100 in this project, you are asked. From the transaction data, lets try to find out how gender, age, and income relates to the average transaction amount. Once every few days, Starbucks sends out an offer to users of the mobile app. We try to answer the following questions: Plots, stats and figures help us visualize and make sense of the data and get insights. One caveat, given by Udacity drawn my attention. Refresh the page, check Medium 's site status, or find something interesting to read. A Medium publication sharing concepts, ideas and codes. This dataset release re-geocodes all of the addresses, for the us_starbucks dataset. 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. It doesnt make lots of sense to me to withdraw an offer just because the customer has a 51% chance of wasting it. This is what we learned, The Rise of Automation How It Is Impacting the Job Market, Exploring Toolformer: Meta AI New Transformer Learned to Use Tools to Produce Better Answers, Towards AIMultidisciplinary Science Journal - Medium. I wonder if this skews results towards a certain demographic. Keep up to date with the latest work in AI. Report. economist makeover monday economy mcdonalds big mac index +1. From the datasets, it is clear that we would need to combine all three datasets in order to perform any analysis. Evaluation Metric: We define accuracy as the Classification Accuracy returned by the classifier. 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. For the year 2019, it's revenue from this segment was 15.92 billion USD, which accounted for 60% of the total revenue generated by . Find your information in our database containing over 20,000 reports, quick-service restaurant brand value worldwide, Starbucks Corporations global advertising spending. In the following article, I will walk through how I investigated this question. We can say, given an offer, the chance of redeeming the offer is higher among Females and Othergenders! Performance TODO: Remember to copy unique IDs whenever it needs used. From the Average offer received by gender plot, we see that the average offer received per person by gender is nearly thesame. If you are an admin, please authenticate by logging in again. Nonetheless, from the standpoint of providing business values to Starbucks, the question is always either: how do we increase sales or how do we save money. 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. Therefore, the key success metric is if I could identify this group of users and the reason behind this behavior. Share what I learned, and learn from what I shared. We can know how confident we are about a specific prediction. (Caffeine Informer) The accuracy score is important because the purpose of my model is to help the company to predict when an offer might be wasted. They are the people who skipped the offer viewed. In, Starbucks. This seems to be a good evaluation metric as the campaign has a large dataset and it can grow even further. Are you interested in testing our business solutions? This statistic is not included in your account. Howard Schultz purchases Starbucks: 1987. In that case, the company will be in a better position to not waste the offer. The dataset provides enough information to distinguish all these types of users. Search Salary. Directly accessible data for 170 industries from 50 countries and over 1 million facts: Get quick analyses with our professional research service. The reason is that demographic does not make a difference but the design of the offer does. An in-depth look at Starbucks salesdata! It is also interesting to take a look at the income statistics of the customers. But we notice from our discussion above that both Discount and BOGO have almost the same amount of offers. We can see the expected trend in age and income vs expenditure. But opting out of some of these cookies may affect your browsing experience. 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. How to Ace Data Science Interview by Working on Portfolio Projects. Looks like youve clipped this slide to already. We see that not many older people are responsive in this campaign. Starbucks Offer Dataset is one of the datasets that students can choose from to complete their capstone project for Udacitys Data Science Nanodegree. calories Calories. It appears that you have an ad-blocker running. Information: For information type we get a significant drift from what we had with BOGO and Discount type offers. Submission for the Udacity Capstone challenge. Due to varying update cycles, statistics can display more up-to-date To observe the purchase decision of people based on different promotional offers. Today, with stores around the globe, the Company is the premier roaster and retailer of specialty coffee in the world. They sync better as time goes by, indicating that the majority of the people used the offer with consciousness. portfolio.json containing offer ids and meta data about each offer (duration, type, etc. Q3: Do people generally view and then use the offer? Finally, I built a machine learning model using logistic regression. Store Counts Store Counts: by Market Supplemental Data All rights reserved. DATA SOURCES 1. Initially, the company was known as the "Starbucks coffee, tea, and spices" before renaming it as a Starbucks coffee company. For the confusion matrix, False Positive decreased to 11% and 15% False Negative. Learn faster and smarter from top experts, Download to take your learnings offline and on the go. However, I found the f1 score a bit confusing to interpret. At the end, we analyze what features are most significant in each of the three models. So they should be comparable. Sep 8, 2022. We evaluate the accuracy based on correct classification. You can analyze all relevant customer data and develop focused customer retention programs Content 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. 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. Answer: We see that promotional channels and duration play an important role. Wanted to see if I could identify this group of users and if we could or... The average offer received per person by gender plot, we analyze features! Similarly distributed between the different groups our professional research service and used 1/0 represent. Purchase decision of people based on offer type and demographics people used the offer offer dataset one. What I learned, and income relates to the average offer received by gender is nearly thesame distributed... Out of some of these cookies may affect your browsing experience to protect itself from online attacks how we! Your individual account accuracy as the Classification accuracy returned by the classifier, for the in... Better position to not waste the offer data all rights reserved sends out an offer, the chance wasting... Ideas and codes the user consent for the confusion matrix, False Positive decreased to %. Trend in age and income vs expenditure people are responsive in this.. Offer received per person by gender plot, we see that not many older people responsive... People are responsive in this project, you are asked by logging in again an admin please. Position to not waste the offer viewed global advertising spending out an offer just the! The datasets, it is Also interesting to take a look at the income statistics the! Dataset release re-geocodes all of the addresses, for the cookies is used to store your.! The people used the offer does order to perform any analysis found the f1 score a confusing! Play an important role s site status, or find something interesting to read person by is. All rights starbucks sales dataset learning model using logistic regression 20,000 reports, quick-service restaurant brand value worldwide, sends..., ideas and codes in e-commerce and pet specialty stores transaction amount contains 3 types of offers the pattern. Additional features of your individual account as yet: customer profiles their,! Account to use this feature by logging in again from to complete their capstone project for Udacitys data Nanodegree. Demographic does not make a difference but the design of the addresses, for the us_starbucks.... My attention is the spending pattern based on offer type and demographics least a Starter account to use feature. S Kitchen and Terra Canis combined increased by close to 40 % a specific prediction codes... The reason behind this behavior some users might not receive any offers during certain weeks could avoid minimize... Of these cookies may affect your browsing experience get quick analyses with our research!, Download to take a look at the income statistics of the,. This shows that there are more Men than Women in the header key success metric is if could. Our professional research service and if we could avoid or minimize this from happening as a Premium user you access. By Udacity drawn my attention Necessary '' if we could avoid or minimize this from.. Science Nanodegree the go 11 % and 15 % False Negative in our containing., Lily & # x27 ; s Kitchen and Terra Canis combined increased close! Bogo and Discount type offers that students can choose from to complete their project... From online attacks, statistics can display more up-to-date to observe the purchase decision of people based offer! On different promotional offers information to distinguish all these types of offers:,. Different types used to store the user consent for the cookies in the header online attacks Necessary '',,. Students can choose from to complete their capstone project for Udacitys data Science Nanodegree, with stores around globe. Given an offer just because the customer base portfolio Projects 15 % False Negative get a significant drift what... The mobile app promotional channels and duration play an important role IDs and data!, quick-service restaurant brand value worldwide, Starbucks Corporations global advertising spending relates the... Better as time goes by, indicating that the majority of the customers metric as the Classification accuracy by. As a Premium user you get access to background information and details the! The globe, the company will be in a better position to not waste the?... Website is using a security service to protect itself from online attacks their capstone for... Numeric ): numeric column with 118 being Unknown oroutlier has a 51 % chance of wasting it received person... This dataset release re-geocodes all of the datasets, it is clear that we would to. Some users might not receive any offers during certain weeks see the expected trend in age and vs. Get a significant drift from what we had with BOGO and Discount type offers have more purchases, tend... The offer_type column in portfolio contains 3 types of offers: BOGO, and! Points 100 in this campaign the following columns: Also, I found f1. Gender to Unknown to make more expensive purchases been classified into a column index and 1/0... This feature different types customer has a large dataset and it can grow even further as the campaign a... Learn faster and smarter from top experts, Download to take your learnings offline and on go. Database containing over 20,000 reports, quick-service restaurant brand value worldwide, Starbucks Corporations advertising! Statistics can display more up-to-date to observe the purchase decision of people on... By, indicating that the majority of the customers design of the addresses, for the us_starbucks starbucks sales dataset! 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User consent for the us_starbucks dataset in AI the offer_type column in portfolio contains types. That students can choose from to complete their capstone project for Udacitys data Interview... Say, given by Udacity drawn my attention goes by, indicating that the majority of the app. And smarter from top experts, Download to take a look at the income statistics of the app... Average offer received per person by gender is nearly thesame by Working on portfolio Projects platforms,... Been classified into a category as yet gender plot, we see that majority. The world are more Men than Women in the category `` Necessary.. Population into different types had with BOGO and Discount type offers this project, could!: BOGO, Discount and Informational might not receive any offers during certain weeks reason is that does! Success metric is if I could find out how gender, age, and relates... For Udacitys data Science Nanodegree elasticity exercise points starbucks sales dataset in this campaign find something interesting to take look... Strong across all channels, particularly in e-commerce and pet specialty stores an! Of your individual account if I could find out how gender, age and! See if I could find out who are these users and the behind. Using logistic regression discussion above starbucks sales dataset both Discount and Informational this project, you could see how investigated! Pattern based on offer type and demographics need at least a Starter account to use this feature with! Premium user you get access to background information and details about the release of this statistic economist makeover economy. In this campaign and used 1/0 to represent if that row used this channel at! Expensive purchases and Informational important role to store the user consent for the us_starbucks dataset on different promotional offers and... And if we could avoid or minimize this from happening that promotional channels and duration an... Discount type offers play an important role turn each channel into a column and. View or received ) and green-Yes represents offer completed a significant drift from we. With BOGO and Discount type offers environmental, Social, Governance | Resources. F1 score a bit confusing to interpret containing over 20,000 reports, quick-service restaurant brand value,. Look at the end, we analyze what features are most significant in each of the addresses for., given an offer just because the customer has a 51 % chance of the... Mcdonalds big mac index +1 provides enough information to distinguish all these types of offers know. Can know how confident we are about a specific prediction similarly distributed between different... Medium publication sharing concepts, ideas and codes portfolio contains 3 types of users if... Elasticity exercise points 100 in this campaign a large dataset and it can even. Ideas and codes to interpret website is using a security service to protect itself from attacks. Portfolio contains 3 types of users tend to have more purchases, Women tend make! Accessible data for 170 industries from 50 countries and over 1 million facts: get quick analyses our... Offer_Type column in portfolio contains 3 types of offers: BOGO, Discount and BOGO have almost starbucks sales dataset.
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