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6 ways in which Starbucks uses big data

  • Ritesh Pathak
  • Nov 17, 2020
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Technology is being leveraged by companies to stay ahead in the market. Artificial intelligence, Machine Learning, Cloud Computing, Big Data are among the top technologies that have sought a lot of usage in the recent past. But can you think of a company that just serves us beverages yet is taking the services of one of these technologies? Yes, a beverage company that has merely any relation with technology is using one. Such has been the evolution and increase in the demand for technology. We are talking about Starbucks here. 


Also Read: Big Data in Manufacturing


Starbucks is among the top two names, at least in India, when we think of a cup of coffee. It is an international brand and its Indian counterpart Café Coffee Day grabs equal attention. There should be no comparisons and we won't be going into a deeper version of the same. However, it's a human tendency to compare things, and why not if we have options. 


Starbucks is almost two decades older than CCD. In India, you can find a CCD outlet more frequently than a Starbucks outlet and the reason is obvious. Starbucks is a bit costlier than CCD but you won't find a major difference in the taste whatsoever. The two top names in the coffeehouses category have their own ways of serving people. We won't be discussing any irrelevant information and move to our main motive. 


So, what we will be discussing in the blog is a bit about Starbucks to just understand its expansion and position in the market. Later in the blog, we will look at the use of Big data by the company to better serve its customers. 



About Starbucks Corporation


Starbucks Corporation is an American multinational chain of coffeehouses and roastery reserves that has its headquarters in Seattle, Washington. It is the largest coffeehouse chain in the world. As of September 2020, the company had 32,660 stores in 83 countries, including 16,637 company-operated stores and 16,023 licensed stores.


“Our mission: to inspire and nurture the human spirit – one person, one cup, and one neighborhood at a time.”

-Starbucks Corporation


Starbucks was founded by Jerry Baldwin, Gordon Bowker, and Zev Siegl in 1971. Its first-ever store was opened near the historic Pike Place Market in Seattle. The company has continuously grown from thereon. 


In 1982, Howard Schultz joined Starbucks as director of retail operations and marketing. Next year, Schultz went on a trip to Italy where he was impressed with the popularity of espresso bars in Milan and saw the potential to develop a similar coffeehouse culture in Seattle. Schultz's first tenure as chief executive, from 1986 to 2000, led to an aggressive expansion of the franchise, first in Seattle, then across the U.S. West Coast. Starbucks entered the Indian market in 2012 when they had already over eighteen thousand stores across different markets. 


Starbucks stores serve hot and cold beverages, entire bean espresso, micro-ground moment espresso known as VIA, coffee, caffe latte, full-and free leaf teas including Teavana tea items, Evolution Fresh squeezes, Frappuccino drinks, La Boulange baked goods, and bites including things, for example, chips and wafers; a few contributions (counting their yearly fall dispatch of the Pumpkin Spice Latte) are occasional or explicit to the region of the store.


Now, we should move to the main part of the blog i.e. use of big data by Starbucks. 


“There are two transformative elements for modern-day retail. The first is you have to create a customer experience in your brick-and-mortar store to make it a destination. And you have to extend that experience to a digital customer relationship. And if you fail to do both of those, you will struggle.”

-Kevin Johnson, CEO, Starbucks


Referred Blog: How Amazon uses Big data?



6 applications of big data in Starbucks


For a massive multinational chain like Starbucks, the amount of data collected is also huge and maintenance of that data is not a handful job at all. The company completes over 100 million transactions per week.



The image shows the six ways in which Starbucks uses big data which are supply chain management, personalised promotions, insight-driven products, sophisticated real estate planning, dynamic menus and in-store experience.

Six ways in which Starbucks uses big data


The manner in which Starbucks utilizes information and present-day innovation for the upper hand is educational for all organizations. For instance, it's a pioneer in joining loyalty systems, installment cards, and mobile applications. Yet, that just starts to expose what's underneath. 


So, let us look at six interesting examples of how Starbucks uses data. 


1. Personalized Promotions


The exemplary utilization of user information is customizing your proposal to an individual purchaser's inclinations, and Starbucks is the same. With more than 16 million individuals in the U.S. alone, its dependability program represents almost 50% of all U.S. store exchanges. 


Realizing singular client request inclinations and purchasing behaviors permits Starbucks to send customized offers bound to be pertinent i.e. users can merely refuse to such offers. Utilizing A.I. to decide such missions is turning into a standard use of artificial Intelligence, and Starbucks has been doing this since 2017 with its "Digital Flywheel" program. 


A significant focal point of this sort of work is recommending new items a buyer may appreciate, in view of what else they request or ask for. 


However, it's not just about customized advancements. A huge part is as yet conveying traditional mass missions, however direct to every shopper in the objective fragment. These might remember cold beverages for hot days, product launches, or occasional menus.



2. Insight-driven products


One amazing way Starbucks utilizes information emerges from the purchasing propensities, or what we call buying behaviors, across enormous buyer numbers. Experiences from this information recommend varieties and improvements from existing items. For instance, there was an amazing thought more than 15 years prior to the present pumpkin-flavored beverages at Halloween. This has become an entire scope of worldwide pumpkin-enlivened items. One result is a colossal spike in footfall during the autumn months. 


A subsequent sort is utilizing information across channels. The main cause of this is likely the company's drive into the espresso at home space in 2016. This was the standard dispatch of items into grocery stores, for clients to make espresso at home. In-store information gave it a solid reason for choosing which items to focus on for the home consumer. It could even street test bring home items like moment espresso in the customary stores. 


It likewise added items like unsweetened variants of home items. Another variety that in-store utilization of information recommended was variants with and without milk.


Referred Blog: 5 ways in which Big data is helping businesses



3. Sophisticated Real estate planning


In 2008, Howard Schultz returned as CEO to a flopping Starbucks and needed to close down several stores. Pushing ahead, he demanded that the organization adopt a substantially more investigative strategy in where they place their stores. Presently, they utilize a combination of "craftsmanship and science" to guarantee their store areas are set for progress. 


Starbucks contracts with a location-analytics organization called Esri to utilize their innovation stage that dissects guides and retail locations. It utilizes information like populace thickness, normal livelihoods, and traffic examples to distinguish target regions for another store. Starbucks utilizes a both neighborhood and corporate level way to deal with new stores. 


They have 20 examination specialists around the globe breaking down guides and geographic data frameworks information, yet in addition engage territorial groups to give contribution on the spot, store plan, and other issues. From the entirety of this information, Starbucks can gauge the benefit of a store, and consequently choose whether another store opening will be monetarily suitable.



4. Dynamic Menus


Starbucks likewise utilizes information to help adjust its menu and product offerings with consumer preferences. For instance, when working out its basic food item lines of k-cups and packaged refreshments, Starbucks utilized both information from its stores as well as client statistical surveying to choose which items to make. One finding was that numerous tea consumers don't place sugar in their tea, so Starbucks made two unsweetened tea k-cups. 


The image shows a Starbucks barista. The company uses big data to change its menu.

Starbucks utilizes big data to decide menus


Starbucks is reinforcing its capacity to utilize information to drive its menu with its new advanced menu sheets. Starbucks has begun testing computerized menu sheets in a modest bunch of U.S. areas. 


The digital boards will permit Starbucks to change which items it highlights to drive and build deals deliberately. The boards can highlight various things dependent on time of day, climate, and more (for example lunch things in the early evening, cold beverages when the climate is more sultry). In principle, the boards can likewise be utilized to dynamically change costs for the duration of the day and season to reflect shifts sought after.



5. Supply Chain management


Starbucks has additionally put Big Data at the core of its main goal to associate its whole flexible chain—a move which has assisted with improving straightforwardness and recognizability. The association's 'bean to cup' pilot utilized blockchain innovation to empower clients to utilize their telephones to check a code on a sack of espresso to see where the espresso beans were developed. As per another ongoing Starbucks story, it's trusted that this will assist with making a coordinated association between ranchers over the globe and somebody drinking espresso at, state, a Starbucks in Seattle or Shanghai.



6. In-store experience


The company's interior AI stage, which is called Deep Brew, is at the essence of Starbucks' present information system. The product's abilities incorporate following the stock that travels through its stores and naturally figuring recharging orders. This opens up countless hours for store staff, who previously checked everything by hand. Deep Brew is additionally used to anticipate staffing prerequisites so Starbucks can add laborers where and when required. This has greatly improved planning measures.


“Deep Brew will increasingly power our personalization engine, optimize store labor allocations, and drive inventory management in our stores.”

- Kevin Johnson, Starbucks CEO





Starbucks is a pretty regular case of a main present-day worldwide business. How Starbucks utilizes information is a model of overseeing information and innovation to incredible impact. There's nothing significantly amazing about its utilization of information and A.I. Nor are there any stunning advancements about A.I. or analytics.


Yet, the manner in which Starbucks utilizes information is a common case of how to begin an excursion to utilize information deliberately, executing plans methodically and completely. The development shows up, yet in what you do in your center business on account of A.I., not really in the A.I. itself. What's more, IoT is only a characteristic expansion of this, alongside the cloud.

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