Data Analysis Of Starbucks' Global Presence

Posted on Aug 2, 2020
The skills I demoed here can be learned through taking Data Science with Machine Learning bootcamp with NYC Data Science Academy.

The first Starbucks was opened in Seattle in 1971 by three partners, Jerry Baldwin, Zev Siegl andΒ Gordon Bowke. In the mid 1980's, they expanded domestically and opened their first store outside of North America in 1996 in Japan. A year later, they opened a store in the Philippines. ​Today, Starbucks has more than 31,000 stores across 79 countries in 6 continents.

Data on the Top Starbucks Locations

​Where can Starbucks expand today? ​To analyze which countries have the strongest expansion potential, we will look at the following indicators for various countries:

  • Starbucks 2017 store data
  • GDP by Purchasing Power Parity
  • Population
  • Ease of doing business index - higher rating indicates simpler business regulation and stronger protections of property rights

Click here for the full project code in Python.

Starbucks could use the following data to chose which countries to put stores in

For this analysis, we are going to combine the Starbucks store by country data shown above with GDP by purchasing power parity, population, ease of doing business index, and coffee consumption. We will use these factors to compare countries with Starbucks locations and countries without Starbucks locations.

Countries with Starbucks stores have a GDP by purchasing power parity of at least $500,000, population of at least 17 million, and a business performance rating of at least 74.​​​​

Data on Main Locations Starbucks Are ExpandingΒ 

We are going to look at the Starbucks 10k report from 2012 to 2016. We are interested in the number of stores open per year across regions.

In 2012, Starbucks was still opening more domestic stores than international stores (around 500 domestic and 400 international).Β  By 2016, the number of stores opened in Asia alone had doubled, outpacing the number opened in North America.​ As of 2019, Starbucks had opened 4000 stores in Asia , serving 11 million customers per week .

Starbucks' international strategy

​Starbucks uses three approaches on their international stores: licensed stores, company owned subsidiaries, and joint venture. They use licensed stores when they want quick expansion in a particular country. Company owned stores are opened when Starbucks has knowledge of the local market, for example, the U.S and Canada. Finally, the joint venture strategy helps to initiate introduce its business practices to the local market. Starbucks does not franchise stores because they want to maintain consistency in culture, standards, and operations.

Top countries for Starbucks to expand their operation.

Although there's worldwide growth potential, Asia is where Starbucks has expanded most, so we will analyze three countries in Asia.

  1. China

China is the most populated country in the world with 1.39 billion people, and it's middle class is projected to double in coming years . They have a GDP of $23.5T, the second highest in the world and they score high on the business performance index. For every store there, there are 526 thousand people, making China a good country for Starbucks to expand.

Β  Β  Β 2.Β  India

India is the second most populated country in the world with 1.35 billion people and a GDP of $9.6T.Β  They have a younger population and largest middle class in the world.Β  They also scored high on business performance index.Β  For every Starbucks store there are 1.6 million people thus making this a country a good potential to expand.

Β  Β  Β 3. Indonesia

Indonesia has a population of 270 million people and a GDP of $3.3T.Β  Starbucks brand recognition is strong in Indonesia and consumers don't mind paying high price for it.Β  Indonesia producesΒ  high quality beans that Starbucks buys at a premium price.Β  For every Starbucks store, there are 1.02 million people.Β  These factors indicate great expansion potential in Indonesia.

In conclusion:

Starbucks opened their first store in 1971, started expanding domestically in the 1980s, and to other continents in the 1990s.Β  Of their 31,000+ stores operating today, only half are outside of North America, which presents an opportunity to increase their presence around the world.Β  Asia is where Starbucks has been increasing their presence, so we analyzed data from three Asian countries that score high on these data points: current number of stores, GDP, population, and ease of doing business.Β  Countries that aren't saturated, and score well on these data points are favorable candidates for expansion.

About Author

Randy Pantinople

Randy was a high school math and physics teacher for 16 years. He got his masters degree in Physics Education at the University of Southeastern Philippines. His passion about trends, predictions, and data driven decisions led him to...
View all posts by Randy Pantinople >

Related Articles

Leave a Comment

No comments found.

View Posts by Categories


Our Recent Popular Posts


View Posts by Tags

#python #trainwithnycdsa 2019 2020 Revenue 3-points agriculture air quality airbnb airline alcohol Alex Baransky algorithm alumni Alumni Interview Alumni Reviews Alumni Spotlight alumni story Alumnus ames dataset ames housing dataset apartment rent API Application artist aws bank loans beautiful soup Best Bootcamp Best Data Science 2019 Best Data Science Bootcamp Best Data Science Bootcamp 2020 Best Ranked Big Data Book Launch Book-Signing bootcamp Bootcamp Alumni Bootcamp Prep boston safety Bundles cake recipe California Cancer Research capstone car price Career Career Day citibike classic cars classpass clustering Coding Course Demo Course Report covid 19 credit credit card crime frequency crops D3.js data data analysis Data Analyst data analytics data for tripadvisor reviews data science Data Science Academy Data Science Bootcamp Data science jobs Data Science Reviews Data Scientist Data Scientist Jobs data visualization database Deep Learning Demo Day Discount disney dplyr drug data e-commerce economy employee employee burnout employer networking environment feature engineering Finance Financial Data Science fitness studio Flask flight delay gbm Get Hired ggplot2 googleVis H20 Hadoop hallmark holiday movie happiness healthcare frauds higgs boson Hiring hiring partner events Hiring Partners hotels housing housing data housing predictions housing price hy-vee Income Industry Experts Injuries Instructor Blog Instructor Interview insurance italki Job Job Placement Jobs Jon Krohn JP Morgan Chase Kaggle Kickstarter las vegas airport lasso regression Lead Data Scienctist Lead Data Scientist leaflet league linear regression Logistic Regression machine learning Maps market matplotlib Medical Research Meet the team meetup methal health miami beach movie music Napoli NBA netflix Networking neural network Neural networks New Courses NHL nlp NYC NYC Data Science nyc data science academy NYC Open Data nyc property NYCDSA NYCDSA Alumni Online Online Bootcamp Online Training Open Data painter pandas Part-time performance phoenix pollutants Portfolio Development precision measurement prediction Prework Programming public safety PwC python Python Data Analysis python machine learning python scrapy python web scraping python webscraping Python Workshop R R Data Analysis R language R Programming R Shiny r studio R Visualization R Workshop R-bloggers random forest Ranking recommendation recommendation system regression Remote remote data science bootcamp Scrapy scrapy visualization seaborn seafood type Selenium sentiment analysis sentiment classification Shiny Shiny Dashboard Spark Special Special Summer Sports statistics streaming Student Interview Student Showcase SVM Switchup Tableau teachers team team performance TensorFlow Testimonial tf-idf Top Data Science Bootcamp Top manufacturing companies Transfers tweets twitter videos visualization wallstreet wallstreetbets web scraping Weekend Course What to expect whiskey whiskeyadvocate wildfire word cloud word2vec XGBoost yelp youtube trending ZORI