Logo.

Digital Innovation and Transformation

Mba student perspectives.

  • Assignments
  • Assignment: Competing with Data and…

COCA COLA LEVERAGES DATA ANALYTICS TO DRIVE INNOVATION

coca cola big data case study

Given the size of its operations, Coca Cola generates a substantial amount of data across its value chain – including sourcing, production, distribution, sales and customer feedback. Over the years, the company has embraced Big Data to drive its business strategic decisions.

Coca Cola is the world’s largest beverage company, with over 500 soft drink brands sold in more than 200 countries. Every day, the world drinks more than 1.9 billion servings of their beverages including Coke, Diet Coke, Fanta, Sprite, Dasani, Powerade, Schweppes, Minute Maid and more. [i]

According to a Forbes article, Coca Cola was one of the first globally recognized brands, outside of the tech sector, to embrace Big Data. In 2012, its chief big data officer, Esat Sezer, said “Social media, mobile applications, cloud computing and e-commerce are combining to give companies like Coca-Cola an unprecedented toolset to change the way they approach IT. Behind all this, big data gives you the intelligence to cap it all off.”

More recently, Greg Chambers, global director of digital innovation, has said “AI is the foundation for everything we do. We create intelligent experiences. AI is the kernel that powers that experience.” [ii] It is quite clear that data analytics and AI have been woven into the fabric of Coca Cola.

In a world that is increasingly dynamic, with changing customer behavior, Coca Cola is betting on Big Data to remain relevant.

Pathways to a Just Digital Future

How Coca-Cola uses Big Data

Coca Cola has been investing extensively in research and development, especially in artificial intelligence, to better leverage the mountain of data it collects from customers all around the world. This effort has helped the firm better understand consumer trends in terms of flavors, and customer’s preference for healthier options in certain regions.

In addition, given Coca Cola presence in 200 plus countries with varying customer trends and the rise of innovative brand, it has become increasingly important for the beverage company to understand and track the evolving taste of its customers and introduce a social consciousness to its product offerings.

Product development using data analytics and innovative channels

Image result for coca cola freestyle jack in the box

In 2008, Coca Cola unveiled a new fountain drink machine, which allowed customers to prepare drinks, mixing a variety of flavors, from their smart phone. With smart phones, people can order exact percentages of different mixtures and flavor additions and save them for next time. Based on monitoring data collected from this self-service soft drinks’ fountains, Coca Cola launched Cherry Spirite as a new flavor.

Given the prevalence of smart phones and how it has been woven into the fabric of our daily lives, Coca Cola sort to leverage this platform to connect and engage with customers in a deeper way.

These freestyle fountain machines, which generated invaluable insights into customer preference, led to launch new brands and flavors. “We discovered that there were a lot of people that really preferred Cherry Sprite. This channel has become a powerful outlet for the introduction of new brands or flavors.” Thomas Stubbs, VP/Engineering and Innovation at Coca Cola. [iii]

Coca Cola also uses data to inform how its sources for raw materials. For example, the company accesses data about weather, crop yields, pricing, and taste, combined with satellite imagery, to inform when and how they source oranges for juices. [iv] This data informs an algorithm that matches products to local customer tastes and ingredient availability. [v]

Social data mining

Image result for coca cola social media channel

Coca Cola has over 100 million followers on Facebook and 35 million on Twitter. Their vast reach has expanded even further thanks to AI, as they’re able to analyze the web for mentions of their brand across the Internet.

In 2015, for example, they were able to determine that Coca Cola products were mentioned online once every two seconds. Having access to this information helps them understand who their customers are, where they live, and what prompts them to discuss the brand. They could also use AI image technology to identify when photos of their products were uploaded to social media, and then serve people ads based on the images they uploaded. According to company representatives, such targeted ads are four times more likely to be clicked on than other methods of targeted advertising. These techniques might lead to original advertising created by AI technologies, such as “automated narratives” according to a Coca Cola marketing executive. [vi]

Coca Cola is increasingly betting on data analytics and AI to drive its strategic business decisions. From its innovative free style fountain machine to find new ways to engage with customers in a meaningful way, Coca Cola appears to be well-equipped to remain relevant in the future.

[i] https://www.forbes.com/sites/bernardmarr/2017/09/18/the-amazing-ways-coca-cola-uses-artificial-intelligence-ai-and-big-data-to-drive-success/#57347fe578d2

[ii] https://www.forbes.com/sites/bernardmarr/2017/09/18/the-amazing-ways-coca-cola-uses-artificial-intelligence-ai-and-big-data-to-drive-success/#57347fe578d2

[iii] https://www.warc.com/newsandopinion/news/coke_taps_insight_from_freestyle_machines/40312

[iv] https://www.forbes.com/sites/bernardmarr/2017/09/18/the-amazing-ways-coca-cola-uses-artificial-intelligence-ai-and-big-data-to-drive-success/#57347fe578d2

[v] https://www.forbes.com/sites/bernardmarr/2017/09/18/the-amazing-ways-coca-cola-uses-artificial-intelligence-ai-and-big-data-to-drive-success/#57347fe578d2

[vi] https://www.forbes.com/sites/bernardmarr/2017/09/18/the-amazing-ways-coca-cola-uses-artificial-intelligence-ai-and-big-data-to-drive-success/#57347fe578d2

Student comments on COCA COLA LEVERAGES DATA ANALYTICS TO DRIVE INNOVATION

Great sharing. Interesting to know that Coco cola is using AI in customer analysis and detecting cola photoes. I am wondering for a CPG company with cost constrain, how much would Coco cola willing to spend in Tech(AI) investment?

Leave a comment Cancel reply

You must be logged in to post a comment.

More From Forbes

The amazing ways coca cola uses artificial intelligence and big data to drive success.

  • Share to Facebook
  • Share to Twitter
  • Share to Linkedin

The Coca Cola Company is the world’s largest beverage company selling more than 500 brands of soft drink to customers in over 200 countries. Every single day the world consumes more that 1.9 billion servings of their drinks including brands like Coca Cola (including Diet and Zero) as well as Fanta, Sprite, Dasani, Powerade, Schweppes, Minute Maid and others.

Of course, this also means that it generates mountains of data – from production and distribution to sales and customer feedback, the company relies of a solid data-driven strategy to inform business decisions at a strategic level.

Shutterstock

In fact, Coca Cola was one of the first globally-recognized brands outside of the IT market to speak about Big Data , when in 2012 their chief big data officer, Esat Sezer, said “Social media, mobile applications, cloud computing and e-commerce are combining to give companies like Coca-Cola an unprecedented toolset to change the way they approach IT. Behind all this, big data gives you the intelligence to cap it all off.”

More recently, Greg Chambers, global director of digital innovation, has said “AI is the foundation for everything we do. We create intelligent experiences. AI is the kernel that powers that experience.”

Product development

Coca Cola is known to have plowed extensive research and development resources into artificial intelligence (AI) to ensure it is squeezing every drop of insight it can from the data it collects.

Fruits of this research were unveiled earlier this year when it was announced that the decision to launch Cherry Sprite as a new flavor was based on monitoring data collected from the latest generation of self-service soft drinks fountains, which allow customers to mix their own drinks.

As the machines allow customers to add their own choice from a range of flavor “shots” to their drinks while they are mixed, this meant they were able to pick the most popular combinations and launch it as a ready-made, canned drink.

Coca Cola is also looking to follow the lead of tech giants by developing something similar to their “virtual assistant” AI bots such as Alexa and Siri. The AI will reside in vending machines , allowing greater personalization – for example, users will be able to order their favorite blend from any vending machine, with the machine mixing it to their individual preference. The AI will also adapt the machines’ behavior depending on its location. This could mean more lively and excitable vending machines in malls or entertainment complexes, and more somber, functional behavior in a hospital.

Healthy options

As sales of sugary, fizzy drink products have declined in recent years Coca Cola has also hooked into data to help produce and market some of its healthier options, such as orange juice, which the company sells under a number of brands around the world (including Minute Maid and Simply Orange).

The company combines weather data, satellite images, information on crop yields, pricing factors and acidity and sweetness ratings, to ensure that orange crops are grown in an optimum way, and maintain a consistent taste.

The algorithm then finds the best combination of variables in order to match products to local consumer tastes in the 200-plus countries around the world where its products are sold.

Augmented reality

Augmented reality (AR) where computer graphics are overlaid on the user’s view of the real world, using glasses or a headset, is being trialed in a number of the company’s bottling plants around the world.

This allows technicians to receive information about equipment they are servicing, and get backup from experts at remote locations who can see what they are seeing and help to diagnose and solve technical problems. It is also used to inspect problems with vending machines and dispensers in remote or difficult-to-reach locations, including cruise ships while they are at sea.

Social data mining

With 105 million Facebook fans and 35 million Twitter followers, social media is another hugely important source of data for the company.

Coca Cola closely tracks how its products are represented across social media, and in 2015 was able to calculate that its products were mentioned somewhere in the world an average of just over once every two seconds.

Knowing this gives insight into who is consuming their drinks, where their customers are, and what situations prompt them to talk about their brand. The company has used AI-driven image recognition technology to spot when photographs of its products , or those of competitors, are uploaded to the internet, and uses algorithms to determine the best way to serve them advertisements. Ads targeted in this way have a four times greater chance of being clicked on than other methods of targeted advertising, the company has said.

Looking further ahead, the company is also interested in the idea of using AI to create adverts.

Speaking at Mobile World Congress this year, global senior digital director Mariano Bosaz said “content creation is something that we have been doing for a very long time – we brief creative agencies and then they come up with stories … what I want to start experimenting with is automated narratives.”

Digital transformation

The Coca Cola company is a shining example of a business which has re-ordered itself based on data and intelligence. It has long shown an appreciation of the fact that today’s technology offers unprecedented opportunity to reassess just about every aspect of how business is conducted. Rethinking itself as a technology-driven company with a focus on strategic implementation of data and AI means it is likely to retain its place at the head of the pack for the foreseeable future.

Bernard Marr

  • Editorial Standards
  • Reprints & Permissions
  • Explore AI by Industry PLUS
  • Consumer goods
  • Heavy industry
  • Natural resources
  • Professional services
  • Transportation
  • AI Best Practice Guides PLUS
  • AI White Paper Library PLUS
  • AI Business Process Explorer PLUS
  • Enterprise AI Newsletter
  • Emerj Plus Research
  • AI in Business Podcast
  • The AI Consulting Podcast
  • AI in Financial Services Podcast
  • Precisely – Building Trust in Data
  • Shift Technology – How Insurers are Using AI
  • Uniphore – The Future of Banking CX in APAC
  • Uniphore – The Economic Impact of Conversational AI and Automation
  • Uniphore – The Future of Complaints Management
  • Uniphore – Conversational AI in Banking

Artificial Intelligence at Coca-Cola – Two Current Use-Cases

Artificial Intelligence at Coca-Cola

Today, Coca-Cola is the world’s largest beverage company, selling over 500 soft drinks in more than 200 countries. In 2020, Coca-Cola had over 80 thousand employees worldwide .

Coca-Cola’s Chief Big Data Insights Officer, Esat Sezer, claims that “big data has played an essential role in helping us relate to [our customers] better and bolster our brand advocacy.” He continues to explain that, “social media, mobile apps, cloud computing, and e-commerce are converging to provide firms like Coca-Cola an unprecedented toolbox to transform the way they approach IT.”

This article provides an overview of the current applications of AI-related technologies at Coca-Cola across two applications:

  • AI for Customer Preference Understanding and Product Development – Coca-Cola’s use of big data to understand consumer trends and inform product offering development decisions.
  • OCR for Customer Rewards Experience – How Coca-Cola has used TensorFlow to add a user-friendly proof-of-purchase capability to their online loyalty program. 

AI for Customer Preference Understanding and Product Development

Coca-cola freestyle .

Throughout its value chain, Coca-Cola creates a significant quantity of data, including sourcing, production, distribution, sales, and consumer feedback. As a result, Coca-Cola was faced with the challenge of effectively leveraging the data it collects from its customers across the globe. 

Coca-Cola Freestyle , an innovative fountain drink dispenser, was released in 2008 and allowed customers to combine beverages and flavors from the company’s entire portfolio from the interactive touch-screen display. These fountain drink dispensers became increasingly popular, in 2018 there were 50,000 units in operation around the world, dispensing 14 million beverages each day. 

Collecting data from these self-service machines, Coca-Cola was able to uncover valuable information on client preferences, leading to the launch of new products. In 2019, these insights contributed to the company’s launches of Sprite Lymonade and Orange Vanilla Coke. Chris Hellmann, VP and GM of Coca-Cola Freestyle highlights the company’s goals with the release of Coca-Cola Freestyle 9100 here:

While Coca-Cola doesn’t seem to make it clear exactly how AI is used in this application, an article in GWPrime makes the following assertion:

“In order to use the mobile app, consumers need to register with their social media account. Coca-Cola uses AI to analyse the social media content of their consumers, generating insights on where, when and how its products are consumed. Based on the consumer behaviour and demographics analysis, Coca-Cola can identify which products are popular in which areas.”

The network of Freestyle devices seem to be able to recommend Coca-Cola products to users based not only on the location and past history of the individual machine, but based on the user’s own social account data. We were unable to find a Coca-Cola source to cite precisely how said data is used.

Since its release, the Coca-Cola Freestyle machines have become a lucrative addition to the company’s portfolio. Hellmann claims , “when we introduced Freestyle, it was truly a disruptive innovation. Today it’s a billion-dollar business.” In 2016, Coca-Cola claimed that 48% of the beverages consumed from Freestyle dispensers are products that are outside of the conventional top ten. Today, Freestyle machines continue to provide on-demand access to more than 200 sparkling and still beverages, including more than 117 low- and no-calorie options–as well as more than 100 unique variations exclusively offered through these dispensers. 

OCR for Customer Rewards Experience

Tensorflow’s machine learning framework.

Another recent challenge that Coca-Cola faced was creating a modern solution for its popular loyalty programs which allow customers to enter the product codes printed on beverage bottle caps for a chance to win various promotions or sweepstakes. 

Examples of scannable Coca Cola promo codes

Previously, Coca-Cola’s core loyalty program was accessible at MyCokeRewards.com but their solution to the rise in popularity of smartphones was to replace it with an application available to both iOS and Android users. Recognizing that having to manually input a 14-character code on a mobile device may drive some users away, Coca-Cola sought to find a way to simplify the process of earning rewards points for its customers. Their research led them to an alternate machine learning technology which provided potential for greater accuracy than existing optical character recognition (OCR) solutions: Convolutional Neural Networks (CNNs). 

TensorFlow is a machine learning framework that streamlines the development of deep neural networks, like CNNs, which allows companies like Coca-Cola to quickly develop, test, and improve high-functioning interfaces for their OCR solution. Patrick Brandt , then Senior Solutions Strategist at Coca-Cola explains how the company used TensorFlow to create a user-friendly application: 

“We created a purpose-built training app for iOS and Android devices that ‘trainers’ could use to take pictures of codes and label them; these labeled images were then transferred to cloud storage for training. We did a product run of several thousand product codes on bottle caps and fridge-packs and distributed these to multiple suppliers who used the app to create the initial real-world training set.” 

The data collected from this training set provided a baseline of the app’s prediction accuracy in both simulated and real image examples. Brandt claims that the interface also allows a feedback loop to be created when customers correct the app’s predictions and this improves the accuracy of the character recognition model gradually. 

Coca-Cola TensorFlow

Brandt claims that as a result of this OCR application, Coca-Cola has not only been able to “finally achieve a long-sought proof-of-purchase capability” but also fuel “more than a dozen promotions and… over 180,000 scanned codes” in the six months following the app’s launch in 2017. Brandt discusses how this began one of the companies biggest digital marketing campaigns in a 2018 interview with TensorFlow here:

Coca-Cola can acquire a better knowledge of how tastes and beverage preferences differ among its customers across the world thanks to the AI algorithms in vending machines. This data is critical in determining when, where, and how to manufacture and sell new products. 

Coca-Cola can now create social media material that is more likely to resonate with its target demographic in various regions across the world thanks to AI image analysis, resulting in a more efficient use of marketing expenditures and, ideally, greater sales margins. Additionally, the company claims that its customer engagement has increased significantly since the application of TensorFlow’s machine learning framework to their OCR solution. 

Coca-Cola’s ability to leverage such detailed and comprehensive data should allow them to continue developing their firm and creating new products and new ways to serve customers.

Related Posts

AI has made some inroads in the cybersecurity sector and several AI vendors claim to…

Retailers and financial institutions are adopting artificial intelligence and machine learning in their business to…

Artificial intelligence is changing the way healthcare networks do business and physicians perform their routine…

UBS is a Swiss multinational investment banking and financial services company ranked 30th on S&P…

Banks and other financial institutions can be tight-lipped about how they implement AI technologies within…

Related posts (5)

Artificial Intelligence in Cybersecurity - What's Possible Today

Artificial Intelligence in Cybersecurity – Current Use-Cases and Capabilities

AI has made some inroads in the cybersecurity sector and several AI vendors claim to have launched products that use AI to help safeguard against cyber threats. At Emerj, we’ve seen many cybersecurity vendors offering AI and machine learning-based products to help identify and deal with cyber threats. Even the Pentagon created the Joint Artificial Intelligence Center (JAIC) to upgrade to AI-enabled capabilities in their cybersecurity efforts.

Artificial Intelligence for Payments – Current Capabilities and Use-Cases

Artificial Intelligence for Payments – Current Capabilities and Use-Cases

Retailers and financial institutions are adopting artificial intelligence and machine learning in their business to solve various business problems such as cybersecurity and document digitization. However, many of these companies are also using AI to improve their payment processes for their clients and customers. These types of applications are usually layered into an existing payments technology stack, which could include straight-through processing (STP) or robotic process automation (RPA).

Doctor-Globe-Stethoscope-iStock_000006373054Large

Artificial Intelligence in Epidemiology – Current Use-Cases

Artificial intelligence is changing the way healthcare networks do business and physicians perform their routine activities from medical transcription to robot-assisted surgery. Although the more mature use-cases for AI in healthcare are those built on algorithms that have applications in various other industries (namely white-collar automation), we believe that in the coming three to five years, AI solutions for healthcare will become increasingly specialized to individual use-cases.

Artificial Intelligence at UBS - Current Applications and Initiatives

Artificial Intelligence at UBS – Current Applications and Initiatives

UBS is a Swiss multinational investment banking and financial services company ranked 30th on S&P Global’s list of the top 100 banks. In addition to investment banking and wealth management, the company is looking to improve its tech stack through several AI projects.

Artificial Intelligence at Citi - Current Initiatives

Artificial Intelligence at Citibank – Current Initiatives

Banks and other financial institutions can be tight-lipped about how they implement AI technologies within their businesses. Citi, however, has been relatively open about their current AI initiatives. Since 2017, they have published press releases and other announcements of AI initiatives that are both internal and customer-facing.

  • Market Reasearch and Advisory
  • AI Presentations and Keynotes
  • Emerj Plus Membership
  • AI In Business Podcast
  • AI In Finance Services Podcast
  • Subscribe to our AI Newsletter
  • Advertise with us
  • Terms and Conditions
  • Refund and Cancellation Policy
  • Privacy Policy

coca cola big data case study

  • Data, AI, & Machine Learning
  • Managing Technology
  • Social Responsibility
  • Workplace, Teams, & Culture
  • AI & Machine Learning
  • Diversity & Inclusion
  • Big ideas Research Projects
  • Artificial Intelligence and Business Strategy
  • Responsible AI
  • Future of the Workforce
  • Future of Leadership
  • All Research Projects
  • AI in Action
  • Most Popular
  • The Truth Behind the Nursing Crisis
  • Work/23: The Big Shift
  • Coaching for the Future-Forward Leader
  • Measuring Culture

Winter 2024 Issue

The winter 2024 issue features a special report on sustainability, and provides insights on developing leadership skills, recognizing and addressing caste discrimination, and engaging in strategic planning and execution.

  • Past Issues
  • Upcoming Events
  • Video Archive
  • Me, Myself, and AI
  • Three Big Points

MIT Sloan Management Review Logo

Coca-Cola’s Unique Challenge: Turning 250 Datasets Into One

To make sense of a mountain of complex data, the world’s largest beverage company takes a forward-looking approach.

  • Data, AI, & Machine Learning
  • Analytics & Business Intelligence

Competing With Data & Analytics

Coca-Cola Soda Cola Soft Drink

Mathew Chacko, Coca-Cola’s director of enterprise architecture, and Remco Brouwer, the company’s director of business intelligence, are tasked with integrating data from 250 bottlers around the world — and then giving them back their information in formats they each can read. The goal: make better decisions faster. “We need to be ready for whatever is the next big hype in 2017,” Brouwer says.

At The Coca-Cola Company, pulling together useful data sets is a particular challenge. Coke’s distribution model involves a network of hundreds of independently operated bottlers around the world that use the Coke concentrates to make and bottle Coke drinks (as well as other non-Coke affiliated beverages). Those bottlers send data to Coke, and Coke’s job is to put those data streams into a common system and use it to look back on how things have gone and project how things might be.

Complicated — to say the least!

Just how complicated can be underscored by a few statistics: Coke is the world’s largest beverage company, with more than 500 brands and 3,500 products sold worldwide. In 2013, the company had $46.9 billion in net operating revenues, and a net income of $8.6 billion. It has about 250 bottling partners with 900 bottling plants, and employs over 700,000 system associates worldwide. In addition to its flagship Coca-Cola products, the company’s brands include Minute Maid juice, Fanta and Sprite soft drinks, and Dasani water.

Mathew Chacko, Coca-Cola’s director of enterprise architecture, and Remco Brouwer, the company’s director of business intelligence, spoke with Sam Ransbotham, an associate professor of information systems at the Carroll School of Management at Boston College and the MIT Sloan Management Review guest editor for the Data and Analytics Big Idea Initiative about the challenges of integrating so many data sets, the ways the company is moving toward a predictive analytics model, and the value of visualizations to convey complex information.

When did Coca-Cola first start thinking about analytical approaches, and how did that first get started?

Mathew Chacko: Analytics at Coke actually has a very long history. An important area of analytics is in our volume and sales reporting and forecasting that spans both the company and our bottler franchisee system. In our sparkling drinks business, the Coca-Cola Company makes the concentrate, and then we sell it to bottlers who are not necessarily owned by us. Sometimes we may have a minority or even majority stake, but it’s a franchise model. The bottlers are responsible for making the end consumer product.

The bottlers then sell it to customers — and by customers, I mean entities like Walmart or Tesco or McDonald’s. And the customers then sell it to consumers. So we have this long pipeline, with the Coca-Cola Company quite removed from the data and the end consumer.

Another area of analytics is marketing performance and spend analysis. Traditionally, the Coca-Cola Company has been responsible for interaction with the consumer mostly from a brand perspective — brand marketing via sponsorship of events like the Olympics or the [FIFA] World Cup, using traditional media, radio ads, billboard ads.

Marketers want to answer questions like, how do we spend our marketing dollars efficiently? How can we project that we will get the lift that we need from the marketing campaign?

What has changed over the last three years or so is the advance of much newer technologies to do more forward-looking analytics versus backward-looking analytics . We are used to a lot of dashboarding and reports that say this is what’s happened, this is how we look at our sales, our volume, this is how we look at marketing. We ask our bottlers to give us volume and sales information so that we can understand how the brand and the various products are doing globally.

Get Updates on Transformative Leadership

Evidence-based resources that can help you lead your team more effectively, delivered to your inbox monthly.

Please enter a valid email address

Thank you for signing up

Privacy Policy

Let’s talk about that forward-looking analytics versus backward-looking analytics. Where is predictive forecasting being used in the company?

Chacko: One can argue about whether it’s analytics or just basic reporting, but there is a forecast element to all that reporting. For instance, we use historical data to project a rolling 13-month forecast window.

Can you give us an example of how this forecasting is being used in the supply chain?

Chacko: Let’s take orange juice. Coca-Cola makes both Minute Maid and Simply Orange juice brands, which are manufactured throughout the year. Also, consumer preferences demand a somewhat consistent flavor for the juice throughout the year.

We use varietals from various sources, but the sweetness of the oranges differs depending on whether it’s a Valencia orange from Florida versus an orange from Spain or from Brazil. In addition, the variances in climate, agricultural fruit production, trucking, shipping, etc., create an agricultural supply-chain problem.

We use an internal application that factors in all influencing variables and optimizes the supply chain to produce a consistent juice product for our consumers. Like other companies, we used technology that we had available at the time to work on the particular problem, and we are continuously evaluating new and emerging technologies as appropriate.

You’re taking this approach of applying things like optimization algorithms toward mixing your varietals, but I assume that before those technologies existed, some kind of forecasting was done by people. So how are you going about trying to nudge people along the technology path?

Remco Brouwer: Well, typically it’s done by taking them along a path one step at a time. Start slow and let people embrace visualizations, for example, instead of reports. Do it at their own pace [for] a little bit.

And be hopeful that their own pace is positive progress and not moving away from it?

Brouwer: Well, yeah. The thing is, most employees would agree that the amount of information that they’re being bombarded with is only going to grow. If you’re one of those people that finds a printed report on your desk in the morning because somebody has put it there, and [reading it is] the first thing you do, then, yeah, it’s a bit of a struggle to move to something else.

I think visualizations will not only increase the business understanding for end users, but will also allow them to be more effective by finding out quicker where the opportunities and the threats are. Visualizations will help people trust the system for taking care of the business that is within the acceptable boundaries.

Chacko: But the shift from looking backwards versus prescriptive and predictive analytics is also a shift in people’s thinking.

So what’s the limitation in rolling out prescriptive and predictive analytics? Technology limitations? Data quality? Is it people to do the analysis?

Chacko: It’s all of the above, really. We need to get the technology capabilities in first so that we can ramp up on the people skills and get the data that’s in silos more connected together.

Coke is not a top-down, hierarchical organization that dictates from above. We encourage our markets to innovate and build capabilities for their specific market. So, that way, they can move fast. But on the flip side, it does introduce some duplication in our system and technology. And this is a particular area where we don’t want to duplicate these kinds of large data platforms.

As a result, we’re looking to build a more shared platform for different regions. But with emerging technologies, we want to take a more cautious approach of building and improving it incrementally.

What about people? Are you finding enough data scientists to help guide the company?

Chacko: We do have a knowledge and insights team within the company, and like a lot of companies, we have a mixture of internal and external resources to help with the analytics. And as I said, since we’re moving in this new direction, we want to also start looking at this whole category of data scientists. One of the plans as we go about this journey is to look at data science as a capability within the organization.

We need people who are just interested in data discovery. And by that, I mean just trolling through data to find out insights and be willing to work with messy data, willing to work with different sets of data. Right now, because we are taking this very traditional BI [business intelligence] approach, we have a whole process of figuring out the best ways of getting this data in, creating the model, getting the visualizations, and then getting those to the market analysts. It’s a long climb.

We’re looking to partner with either research institutions or universities as well, for a couple of reasons. First of all, they have cutting-edge research in this area. We also want to work with them in terms of working with their students, giving them opportunities, internships, etc. Hopefully we’ll get a pipeline of students who would be interested in working on analytics problems at Coke.

Can you talk a little bit about the challenges of marrying all these external data sets from your bottlers? That seems like a particular challenge at Coke, where there’s this huge infrastructure of “data middlemen,” for lack of a better term.

Chacko: Well, point-of-sale data, scan data, is actually very big. Our commercial department really wants to have good information about that from one set of customers so that they can take that information and go to other customers and say, “Hey, we have this other customer that did these kinds of campaigns with this kind of strategy, and they were able to see this lift.”

Our team wants to go to our customers with real numbers. It’s important for us when we go to our customers to be able to give them fact-based information. We also want to take in things like event data and social media data and provide these value services back to our customers. That’s a big thing for us.

In some areas we have to have flexibility, and in other areas we can standardize. Currently our bottlers run their own system, and so they send us data in all sorts of different formats. We have to be flexible in being able to inject data. But when we transform that data, we need to transform into those standardized taxonomies or hierarchies.

We also have the reverse problem because we need to transform information back into the bottler’s view — we have to give them back their information in formats they can read. We aspire to provide data as a service, both to our customers and to our bottlers.

Any time I learn more about anything that anybody’s doing, it always seems much harder than I had originally appreciated. I can see where your franchises create an opportunity but also some difficulty in their autonomy.

Brouwer: Yes, it’s a very complex thing. There are over 250 bottlers around the world, and we are in the center of this nucleus. These 250 bottlers are all sending us data. We’re trying to solve some of the day-to-day things like moving more and more into the direction of a one-number system. At the same time, it’s the idea of the shared knowledge because in the end, overall, we want the same thing, and that is to understand the consumers better and be as relevant as possible in the market so that people will buy our products and be delighted by them.

In the end it’s about — it’s a bit of an old term, but it is about making better decisions faster. Better decisions by having your data right and your right visualizations, and faster by not spending too much time to get there. That means starting at the bottom and trying to drive clarity in the numbers themselves. As we move more into the direction of big data and cross-measure analysis of everything that big data technologies enable, we’re at the beginning of the path here, there are many answers out there to questions we did not know we had.

We need to be ready for whatever is the next big hype in 2017. We don’t know what it is today, but we do know that we will need to capture its data and analyze it against our own data at some point in time. So we’re trying to solve today’s challenges and at the same time get our solutions ready for whatever tomorrow will bring.

About the Author

Sam Ransbotham is an associate professor of Information Systems at Boston College. He can be reached at [email protected].

More Like This

Add a comment cancel reply.

You must sign in to post a comment. First time here? Sign up for a free account : Comment on articles and get access to many more articles.

Comment (1)

Rui marques.

  • Skip to main content
  • Skip to secondary menu
  • Skip to primary sidebar
  • Skip to footer

Datafloq

Data and Technology Insights

How Coca-Cola Takes A Refreshing Approach On Big Data

Datafloq AI Score

Datafloq AI Score: 84.33

Datafloq enables anyone to contribute articles, but we value high-quality content. This means that we do not accept SEO link building content, spammy articles, clickbait, articles written by bots and especially not misinformation. Therefore, we have developed an AI, built using multiple built open-source and proprietary tools to instantly define whether an article is written by a human or a bot and determine the level of bias, objectivity, whether it is fact-based or not, sentiment and overall quality.

Articles published on Datafloq need to have a minimum AI score of 60% and we provide this graph to give more detailed information on how we rate this article. Please note that this is a work in progress and if you have any suggestions, feel free to contact us .

coca cola big data case study

As the worlds largest non-alcoholic beverage company , Coca-Cola generates Petabytes of data from various sources. Multi-channel retail data, customer profile data from loyalty programs, social media data, supply chain data, competitor data, sales and shipment data from bottling partners as well as transaction and merchandising data. Coca-cola collects vast amounts of data and they take a refreshing approach in exploiting that data and deriving value from it.

Chief Big Data Insights Officer, Esat Sezer, explains that Coca-Cola takes a strategic approach instead of a tactical approach with big data. They use the vast amount of available data sets to change the way they approach IT. They have embraced big data technologies and as such were able to create a shared services centre for their financial transactional activities as well as an employee service centre for HR activities. They moved from a decentralized approach to a centralized approach, where the data is combined centrally and available via the shared platforms across the organization .

In addition, Coca-Cola has almost 70 million Facebook followers and big data enables Coca-Cola to connect to these followers better and be able to grow the brand advocacy. Coca-Cola also leverages Point of Sales data from companies like Walmart (Walmart alone is responsible for $ 4 billion in Coca-Cola sales annually) to build customer profiles, create centralized iPad reporting across the company and enable Collaborative Planning, Forecasting and Replenishment process within their supply chain using all data at hand.

One of the most refreshing approaches on big data is that Coca-Cola uses it to produce orange juice that has a consistent taste year-round, although the oranges used have a peak-growing season of just three months. They have developed an algorithm, called the Black Book model, that combines various data sets such as satellite imagery, weather date , expected crop yields, cost pressures, regional consumer preferences, detailed data about the myriad of 600 different flavours that make up an orange, and many other variables such as acidity or sweetness rates to tell Coca-Cola how to blend the orange juice to create a consistent taste, down to the pulp content .

In a post on BusinessWeek , Bob Cross, architect of Cokes juice model Black Book, calls it one of the most complex applications of business analytics. It requires analysing up to 1 quintillion decision variables to consistently deliver the optimal blend, despite the whims of Mother Nature.

Interested in what the future will bring? Download our 2023 Technology Trends eBook for free.

Of course also throughout other departments within The Coca-Cola Company, such as category management , shopper marketing or the supply chain, vast amounts of data are used to make more and better critical time-sensitive decisions . They have developed an advanced enterprise data warehousing that is capable generating a single view of all multi-channel retail information, which enables Coca-Cola to respond quickly and accurately to changing market conditions. They standardized all data through a series of master data management processes and their ultimate goal is to help Coca-Colas customers become efficient and effective within their stores to drive sales and improve the consumer experience .

With so much data being collected from so many countries, Coca-Cola is available in 206 countries, privacy is a major concern within The Coca-Cola Company. Coca-Cola has already been on a 10-year data governance journey to ensure that culturally specific sensitivities of different societies are respected. On a blog post by Computer Weekly , Katherine Fithen, Chief Privacy Officer at Coca-Cola, explained that in the US it is not creepy that the grocery store knows what we buy. In other cultures, it is considered creepy to track that. The use of GPS data is not creepy for some cultures; it is for others.

It may be clear that The Coca-Cola Company is far ahead in using big data to improve their organizations, products, increase their revenue and reduce their costs. Reportedly , they were able for example to cut overtime costs by 46% just by analysing the data in their employee service centre. And as long as their orange juice taste the same year-round and is readily available anywhere in the world at any moment for the right price, we know that their Black Book algorithm does the job correctly.

Images: Courtesy of The Coca-Cola Company

About dr mark van rijmenam.

Dr Mark van Rijmenam is a strategic futurist, living and breathing cutting-edge technologies to inspire Fortune 500 companies. He is known as The Digital Speaker, and he is a 5x author and entrepreneur.

  • 5 Reasons Why Modern Data Integration Gives You a Competitive Advantage
  • 5 Most Common Database Structures for Small Businesses
  • 6 Ways to Reduce IT Costs Through Observability
  • How is Big Data Analytics Used in Business? These 5 Use Cases Share Valuable Insights
  • How Realistic Are Self-Driving Cars?

Dear visitor, Thank you for visiting Datafloq. If you find our content interesting, please subscribe to our weekly newsletter:

Did you know that you can publish job posts for free on Datafloq? You can start immediately and find the best candidates for free! Click here to get started.

Thanks for visiting Datafloq If you enjoyed our content on emerging technologies, why not subscribe to our weekly newsletter to receive the latest news straight into your mailbox?

  • Privacy Overview
  • Necessary Cookies
  • Marketing cookies

This website uses cookies so that we can provide you with the best user experience possible. Cookie information is stored in your browser and performs functions such as recognising you when you return to our website and helping our team to understand which sections of the website you find most interesting and useful.

Strictly Necessary Cookie should be enabled at all times so that we can save your preferences for cookie settings.

If you disable this cookie, we will not be able to save your preferences. This means that every time you visit this website you will need to enable or disable cookies again.

This website uses Google Analytics to collect anonymous information such as the number of visitors to the site, and the most popular pages.

Keeping this cookie enabled helps us to improve our website.

Please enable Strictly Necessary Cookies first so that we can save your preferences!

AIM logo Black

  • Last updated January 13, 2021
  • In AI Origins & Evolution

Coca-Cola Leans On Data Analytics & AI For Deeper Industry Insights

  • by Anirudh VK

coca cola big data case study

For any brand, the top priority is ensuring that advertising messaging stays constant across markets. This is not only integral to building a brand, but also maintaining brand recognition across markets.

As a company with a global footprint, how does Coke manage consistent marketing? The answer lies in Big Data.

Coke’s Giant Footprint

Coke lists on its website that it sells its products in over 200 countries. These countries are also varied in consumption habits, supply chain mechanics and culture.

The company’s products are not sold in only two countries (North Korea and Cuba) on the planet. With the aim of being recognised the world over, Coco-Cola has made consistent branding and brand recognition a priority. With over 23 million retail outlets, 3500 products and 700,000 associates, Coke has its work cut out for it.

What many might not know is that even the flagship product ‘Coca-Cola’ differs from market to market. This is done to ensure that personal preferences are adhered to and a consistent taste signature is maintained.

This taste is, again, decided by marketing and customer preferences in each region. All of this data is collected by the hundreds of thousands of associates around the world. The dataflow in their systems is on a scale that is rarely seen with companies, as the amount of data points and fields collected is staggeringly high. However, all of this data is used by the company for its next strategy.

Wes Finley, the former Global Digital Marketing Operation Lead at the company, said in a statement:

“[It was difficult]…getting all that data from all those local marketers and bring it together in a cohesive way, to tell the story and to really drive every one of the regions forward in their marketing.”

How Big Data Changed Coke

One of the first places they used big data was to gauge the effectiveness of their social media posts. However, the data held much more information than they thought it did.

The company creates a lot of online content on a regular basis, and picking impressions, engagements and responses to these campaigns alone showed user patterns.

It is common knowledge that social media is one of the more effective ways of spreading an advertising message. Gauging the effect these campaigns had also allowed Coke to see which campaigns did well and which ones didn’t.

One of the initiatives undertaken by Coke to amplify the effect of their social media campaigns is their Social Centres initiative. Over 40 interconnected centres exist, with the aim of monitoring Coke’s huge social media presence.

Using data mining tools, they monitor the brand’s presence across Facebook, Instagram, Twitter and Snapchat. They also use image recognition software to determine if an individual is taking a picture with a Coke brand in the image.

These hubs were the reason for many branding strategies that took place, such as the “Bring Back Surge” campaign. Monitoring this campaign closely made Coke realize that there was a market for the Surge product, which they stopped making in the late 90s.

Big Data Analytics At The Base Of Decision Making

Using AI, the company has begun collecting data from its vending machines. This drove the collection of data to see what flavour customization users choose the most.

Monitoring this flow of data also allowed Coke to release the Sprite Cherry flavour in certain markets. In addition to gaining insights about potential market moves, adding AI to the vending machines also allowed coke to enable modern features to them.

This includes mobile payments and special offers customized for individual customers. In addition to this, the machine also tracks sales, the ad allows for predictive maintenance by monitoring bottles.

Coke has also been using AI for optimizing other tasks such as overtime costs, supply chain management and promotion code scanning using OCR. All in all, looking into the way one of the world’s biggest brands uses Big Data for optimizing market movement.

Access all our open Survey & Awards Nomination forms in one place >>

Anirudh VK

Download our Mobile App

coca cola big data case study

AIM Research

Pioneering advanced ai market research, request customised insights & surveys for the ai industry.

coca cola big data case study

CORPORATE TRAINING PROGRAMS ON GENERATIVE AI

Generative ai skilling for enterprises, our customized corporate training program on generative ai provides a unique opportunity to empower, retain, and advance your talent., 3 ways to join our community, telegram group.

Discover special offers, top stories, upcoming events, and more.

Discord Server

Stay Connected with a larger ecosystem of data science and ML Professionals

Subscribe to our Daily newsletter

Get our daily awesome stories & videos in your inbox, most popular.

coca cola big data case study

Google Challenges Meta’s Llama 2 with Lightweight Open Source LLM, Gemma

Gemma outperforms Llama 2 on several benchmarks, including MMLU, HellaSwag, and HumanEval.

coca cola big data case study

Did Google Gemini 1.5 Really Kill RAG? 

coca cola big data case study

upGrad is Using AI to Translate Learning Materials into Indian Languages

coca cola big data case study

Industry Bodies Recommend Advanced US-India Cooperation To Strengthen Semiconductor Competitiveness

coca cola big data case study

Meet the New Indic LLM, MahaMarathi 7B

Boasting 7 billion parameters, the model is built on Meta Llama-2+Mistral AI framework.

IIT-Hyderabad-Professor-Believes-Indic-Data-is-All-You-Need

IIT Hyderabad Professor Believes Indic Data is All You Need

coca cola big data case study

Hugging Face Introduces Cosmopedia, the Largest Open Synthetic Dataset 

coca cola big data case study

Nimo Planet’s Spatial Computer Brings in a Future Sans Laptops

BharatGPT Open Source

BharatGPT Unveils Hanooman, a NewSuite of Indic Generative AI Models

Our mission is to bring about better-informed and more conscious decisions about technology through authoritative, influential, and trustworthy journalism., shape the future of tech.

© Analytics India Magazine Pvt Ltd & AIM Media House LLC 2024

  • Terms of use
  • Privacy Policy

coca cola big data case study

  • Bahasa Indonesia
  • Sign out of AWS Builder ID
  • AWS Management Console
  • Account Settings
  • Billing & Cost Management
  • Security Credentials
  • AWS Personal Health Dashboard
  • Support Center
  • Expert Help
  • Knowledge Center
  • AWS Support Overview
  • AWS re:Post

Coca-Cola logo

The Coca-Cola Company on AWS

After 20 years of operating its own on-premises data centers, Coca-Cola migrated to Amazon Web Services (AWS) in 2013. Earlier that year, the company’s Super Bowl commercial generated a spike in website traffic that oversaturated its servers, catalyzing Coca-Cola’s decision to move to the cloud. Since its migration, Coca-Cola has reduced its operational costs by 40 percent and IT ticket volume by 80 percent. In addition, many individual bottlers in the company's global network of distributors, such as Coca-Cola Andina and Coca-Cola İçecek, are accelerating their digital transformation. Coca-Cola continues to innovate on AWS, recently using AWS serverless technologies to develop a low-latency, touchless user experience for its Coca-Cola Freestyle beverage-dispensing platform in only 150 days.

Coca-Cola's Cloud Journey on AWS

Coca-Cola's Cloud Journey on AWS

  • Data and Analytics

Keeping data secure and unlocking its value at scale

IoT icon

Internet of Things (IoT)

Building solutions to connect, store, and analyze device data

migration icon

Building efficiencies in the cloud after migration

continuous innovation icon

  • Continuous Innovation

Ongoing improvements to support enterprise transformation

  • Internet of Things

Coca-Cola Andina Builds Data Lake on AWS, Increases Analytics Productivity by 80% for More Data-Driven Decision-Making

Coca-Cola Andina promotes the profitable growth of its business, supports customers, and delivers the best possible experience to more than 54 million consumers in Argentina, Brazil, Chile, and Paraguay. It has created world-class processes to increase productivity and quality of service, including the development of a data lake on AWS. By adopting storage, database, compute, and analytics solutions from AWS, Coca-Cola Andina boosted the productivity of its analytics team by 80 percent, facilitating more data-driven decisions to maintain its competitive advantage and increase company revenue.

Read the data lake case study »

Smiling Coca-Cola employee

AWS was the cloud solution that would meet all the expectations defined for our data lake."

Luis Valderrama Chief Technology Officer, Coca-Cola Andina

Coca-Cola İçecek Improves Operational Performance Using AWS IoT SiteWise

Coca-Cola İçecek (CCI), one of the key bottlers in the Coca-Cola system, built an advanced analytics solution for its production-line sanitation process in 2 months on AWS. As part of its digital transformation strategy, CCI wanted to transition to autonomous smart manufacturing. Working toward asset optimization and operational excellence, CCI digitized its shop floor and built an analytics solution for its sanitation process using AWS IoT SiteWise. With the ability to analyze clean-in-place processes and optimize asset utilization, CCI can gain meaningful insights, save production time, and reduce environmental resource use.

Read the IoT case study »

Coca-Cola bottling

Coca-Cola Bottler Digitizes Manufacturing Processes with AWS

Coca-Cola İçecek (CCI) is modernizing its manufacturing facility by creating a digital plant replica—a digital twin—in the cloud. It hopes to unlock value with advanced analytics, artificial intelligence (AI), and real-time asset monitoring.

Read the digital manufacturing blog »

coca-cola bottles

Smart Manufacturing in CPG with Leyla Delic, Chief Digital and Information Officer, Coca-Cola İçecek

From product design to smart factory and smart products, AWS helps leading manufacturers and bottlers transform their operations with the most comprehensive and advanced set of cloud solutions available today. In this on-demand webinar, learn from Leyla Delic, chief digital and information officer for Coca-Cola İçecek, and AWS leaders about unlocking unseen capacity, optimizing internal operations, leveraging smart manufacturing, and forecasting real-time customer demand.

Watch the smart manufacturing webinar »

Coca-cola webinar placeholder image

Coca-Cola Argentina Uses AWS to Speed App Development and Product Delivery

Coca-Cola Argentina uses AWS to deliver products in under 15 minutes, deploy software features in months instead of a year, and enable consumer packaged goods companies to improve efficiency.  

Read the product delivery case study »

A young beautiful woman rolls a grocery cart and chooses products in the supermarket

Swire Coca-Cola Goes All-In on AWS

Swire Coca-Cola, one of the world’s largest Coca-Cola bottlers representing a total franchise population of 728 million, shut down all of its data centers and migrated its applications to AWS to enhance the company’s operational flexibility and drive digital transformation. The bottler moved critical systems to AWS, including its SAP solution, data warehouse, supply chain management, sales tracking, vending machines management, and mobile applications.

Read the digital transformation case study »

Coca-cola bottles on a shelf

Coca-Cola Freestyle Marketing Uses AWS to Drive Value with Touchless Pouring for Custom Drinks

Coca-Cola Freestyle used AWS to deploy a solution that enables touchless beverage pouring, improving the Freestyle experience and driving marketing outcomes with respect to both customers and consumers.

Read the Coca-Cola Freestyle case study »

Coca-Cola freestyle

Driving Innovation in Consumer Packaged Goods with Coca-Cola

In this AWS re:Invent 2020 video, discover how Coca-Cola Freestyle is working with AWS to rapidly develop and deploy new solutions that increase consumer engagement, reinforce brand, and grow revenue.

Watch the re:Invent presentation »

About Coca-Cola

The Coca-Cola Company is a total beverage company that sells products in more than 200 countries and territories. Coca-Cola has adopted an array of AWS services to maintain its edge in the beverage category and continue to innovate and transform the business. The company works with local bottlers to make its brands globally available to more than 27 million customers.

Get Started

Organizations of all sizes across all industries are transforming their businesses and delivering on their missions every day using AWS. Contact our experts and start your own AWS journey today.

deprecated-browser pixel tag

Ending Support for Internet Explorer

  • Share Facebook LinkedIn Twitter
  • Case Studies

Coca-Cola BIG chooses NTT DATA for SAP SuccessFactors Implementation Across Asia Pacific

After three successful deployments in three countries, NTT DATA became our partner of choice. NTT DATA’s SuccessFactors ready2run Solutions became that leverage that allowed us to have a faster delivery of the right technology solution without sacrificing our ability as HR professionals to understand the technology and align it to our processes.

Teejay Gonzales, Coca-Cola BIG Transformation Director

The Coca-Cola Bottling Investment Group (BIG) is part of the Coca-Cola Company focusing on bottling and distribution of Coca-Cola products with operations in markets in Southeast Asia, India, Middle East and Southwest Asia, covering 16 countries with 39 plants and 28,000 employees, serving over 1.8 billion consumers.

Coca-Cola BIG has initiated a Digital Transformation Initiative for HR that aims to standardize the end-to-end processes involved in identifying all the HR requirements of all their markets, which are in various degrees and sizes, locations, complexity, and functionalities. Despite having identified SAP SuccessFactors as their standard HCM platform, they faced challenges with its initial deployment, so their HR transformation didn’t happen as quickly as they intended. It took them three years to deploy it to 4 markets alone, which led them to reflect and strategize where they want to steer their digital HR journey.

NTT DATA Philippines (NDPH) was brought into Coca-Cola BIG markets (Myanmar and Vietnam) after their successful implementation of SAP SuccessFactors for Coca-Cola Beverages Philippines (CCBPI). Soon, NDPH became Coca-Cola BIG’s partner of choice because they gave them the confidence to demonstrate the ability of translating complicated technology solutions to something that's more tangible in real life. NDPH received positive feedback from stakeholders and users, and with the support of their management team, Coca-Cola BIG was able to firm up their deployment of SAP SuccessFactors in all 16 markets starting this 2021 and will end in 2023.

SAP_Qualified_PartnerPackageSolution_R

Being a large enterprise, their HR Department was burdened with tedious tasks, taking away time to focus on strategic and value adding initiatives. The siloed systems made it time consuming to generate reports hindering management to make strategic decisions regarding their talent workforce. Its isolated solutions were difficult for collaboration and active engagement amongst employees. Adherence and compliance to internal controls were also a concern.

The absence of an end-to-end Hire to Retire process results to inefficiencies and missed opportunities – performance reviews were not tied to rewards and recognition, there’s no consistency in talent management and development leading to over complexity in its business processes and low employee engagement.

This complex process brought difficulties and challenges that affected not only our employees’ productivity but also the business performance as a whole.

  • Manual HR business processes varying across multiple countries
  • Lack of standard HR solution across the region
  • Inefficient HR analytical reporting within their workforce structure
  • Lack of integrated end-to-end Hire to Retire process
  • Ineffective HR management tracking
  • Low adherence to compliance and internal controls
  • Lack of regional and local active employee engagement and collaboration

NDPH helped Coca-Cola BIG achieve their goal of automating and standardizing their HR System across the region. With NTT DATA’s ready2run Solutions , a rapid implementation approach for SAP SuccessFactors HxM solutions, Coca-Cola BIG was able to quickly address their most critical talent and people's strategy objectives.

NDPH’s harmonization workshops to standardize HR processes across multiple markets enabled a consistent approach unifying multiple companies and reducing complexity of its business processes. A connected system to support talent management increased productivity across teams and geographical boundaries. The seamless process irrespective of location and time zone resulted in a happier and more engaged workforce.

Among the many benefits of the new implementation, NTT DATA’s ready2run solution is expected to enable Coca-Cola BIG to achieve:

  • Process Standardization across all countries
  • Elimination of manual Talent Management processes and introduction of paperless and harmonized processes and data across the whole Region from Asia to Middle East countries

Asia to Middle East countries

  • Faster and real time, consolidated, detailed talent reporting to support strategic planning and alignment with the over-all business objectives
  • Remove the reliance on spreadsheet and the likelihood of human error
  • Remove the overhead (difficulty and cost) of managing disparate systems

About the Client

The Coca Cola Bottling Investments Group (BIG) is a conglomerate of bottling operations solely or jointly owned by the Coca-Cola Company. They are located in the Asia Pacific region and is home to a total of 16 countries making them the second largest bottler in the Coca-Cola system.

  • https://investors.coca-colacompany.com/about/segments/bottling-investments-group-big

About NTT DATA Philippines, Inc.

NTT DATA Philippines, Inc. (NDPH), formerly known as Wizardsgroup Inc., is a leading Information Technology organization with the mission of creating high value IT solutions and services for medium-sized to large enterprises. NDPH emphasizes long-term commitment and combines global reach and local intimacy to provide premier professional services, from consulting, application services, and business process and IT outsourcing to cloud-based solutions.

Coca-Cola Consolidated automates their Data Testing with QuerySurge

Cocacola consolidated color white

  • Case Studies

Coca-Cola Consolidated Automates their Data Testing with QuerySurge

As the largest bottler of Coca-Cola in the United States, Coca-Cola Consolidated handles critical business data from a multitude of sources with different technology implementations. Ensuring the validity of this data as it passes through integration points in their system is a key goal of the QA team as these integrations are used to conduct vital business operations. To achieve this goal, the team needed to find a comprehensive data testing solution that was easily adaptable. After reviewing several options, the Coca-Cola Consolidated team decided to implement QuerySurge, which provided them with the features needed to accomplish their data testing objectives.

Coca-Cola Consolidated sources a majority of their master and transactional data from the centralized Coke One North America (CONA) Bottler platform. The data from this platform, along with internal data, moves through several integrations that are connected to local systems which ultimately support their end users. These integrations utilize a variety of technologies such as SAP, web & mobile applications, encrypted flat files, APIs, as well as HANA and Snowflake data warehouse implementations. Their testing efforts focus on verifying that all this data is complete and accurate.

QuerySurge test results provide a comprehensive view into the current state of the data allowing for quick and easy analysis ” Remila Palaniappan IT QA Lead Analyst Coca-Cola Consolidated

The demand associated with testing data from various sources and different technologies outpaced the QA team’s capacity to complete full dataset verifications within the test-cycle timeline. Manual data validation efforts involved several approaches where different toolsets were being utilized to accomplish the data comparison tasks:

  • RedGate for SQL database comparison
  • WinMerge for file comparisons
  • Excel for data validation in files and tables

Saphana snowflake excel

Incorporating results from different tools added additional overhead to an already time-sensitive process, especially when dealing with HR material, which contains PI (Personal Information), where the exported test data needed to follow a strict security protocol. Additionally, each of these toolsets came with limitations in their data verification capabilities, resulting in only a subset of the data being tested. Incidents of bad data often occurred late in the test-cycle.

Implementing QuerySurge allowed the team to consolidate their data verification efforts into a single solution. Instead of focusing on only a subset of data, they are now able to fully validate large datasets from multiple sources in their test cycle. QuerySurge test results provide a comprehensive view into the current state of the data allowing for ​ “ quick and easy analysis” in a centralized location according to Remila Palaniappan, IT QA Lead Analyst.

With over 500 QueryPairs (automated tests) and counting, the team continues to build out new tests each cycle and incorporates existing QueryPairs to aid in regression efforts.

Average table validation:

  • 500,000 records (400 MB)

Largest table validated:

  • 3,500,000 records (3 GB)

All QuerySurge tests have been integrated into Coca-Cola Consolidated’s Azure DevOps pipeline, which has enhanced the team’s CI/CD capabilities. The tests are automatically executed with each pipeline run and results are passed back to Azure DevOps allowing them to continually detect data issues in the delivery pipeline.

Qs azure devops

Implementing QuerySurge was not without its challenges. When questions arose around configurations, connection set up, or upgrades, the Coca-Cola Consolidated team was able to rely on the top-rated QuerySurge support team for answers. According to Retha Williams, IT QA Sr. Manager for Coca-Cola Consolidated, ​ “ our experience with the QuerySurge support team has been excellent…they are extremely responsive and knowledgeable!” Upgrading to QuerySurge 8.0 and the new Projects feature allowed Coca-Cola Consolidated to sequester assets and assured that its PI data was securely protected.

QuerySurge has proven to be a valuable solution for many Coca-Cola Consolidated testing efforts, including their project for upgrading the HR platform. The data validation timeline was reduced from weeks to hours. Their initial manual testing effort estimate was for 5 resources and 20 days or 100 person/days. After installing QuerySurge, 2 resources spent 15 days developing QueryPairs, which took 12 hours to execute during the test cycle — for a total of 31 person/days. This resulted in a cost savings of about $15,000 on that project alone. As with the benefit of all automated regression suites, any additional automated executions would take 1 day versus a manual effort of an additional 100 person/days.

The ability to relay the testing results to the development team quickly and easily has been another key benefit in Coca-Cola’s QuerySurge implementation. Instances of bad data were significantly reduced, and subsequent HR projects benefited from the issues found in their initial QuerySurge tests. Applying the lessons learned from earlier QuerySurge testing efforts prevented those same issues from reoccurring, resulting in much cleaner data.

Out of all our test automation tools, QuerySurge has provided us with our greatest ROI by enabling us to reduce resources and time needed for data validation testing, which ultimately results in cost reductions in our solution delivery processes. Retha Williams IT Sr. QA Manager  Coca-Cola Consolidated

About Coca-Cola Consolidated:

Coca-Cola Consolidated is the largest Coca-Cola bottler in the United States. Our Purpose is to honor God in all we do, serve others, pursue excellence and grow profitably. For over 118 years, we have been deeply committed to the consumers, customers, and communities we serve and passionate about the broad portfolio of beverages and services we offer. We make, sell and distribute beverages of The Coca-Cola Company and other partner companies in more than 300 brands and flavors across 14 states and the District of Columbia to over 66 million consumers.

We are based in the Southeast, Midwest, and Mid-Atlantic portion of the United States. We have 13 manufacturing facilities, 70+ distribution and sales centers, with our Corporate offices located in Charlotte, North Carolina

Coca cola consolidated

About RTTS & QuerySurge:

RTTS, the developer of QuerySurge, is the premier pure-play QA & Testing organization that specializes in Test Automation. Headquartered in New York, RTTS has had 1,000+ successful engagements at over 700 corporations since 1996.

Rtts Logo

QuerySurge is the smart data testing solution that automates the data validation and ETL testing of Big Data, Data Warehouses, Business Intelligence Reports and Enterprise Applications with full DevOps/DataOps functionality for continuous testing.

Qs logo

All Courses

  • Interview Questions
  • Free Courses
  • Career Guide
  • PGP in Data Science and Business Analytics
  • PG Program in Data Science and Business Analytics Classroom
  • PGP in Data Science and Engineering (Data Science Specialization)
  • PGP in Data Science and Engineering (Bootcamp)
  • PGP in Data Science & Engineering (Data Engineering Specialization)
  • Master of Data Science (Global) – Deakin University
  • MIT Data Science and Machine Learning Course Online
  • Master’s (MS) in Data Science Online Degree Programme
  • MTech in Data Science & Machine Learning by PES University
  • Data Analytics Essentials by UT Austin
  • Data Science & Business Analytics Program by McCombs School of Business
  • MTech In Big Data Analytics by SRM
  • M.Tech in Data Engineering Specialization by SRM University
  • M.Tech in Big Data Analytics by SRM University
  • PG in AI & Machine Learning Course
  • Weekend Classroom PG Program For AI & ML
  • AI for Leaders & Managers (PG Certificate Course)
  • Artificial Intelligence Course for School Students
  • IIIT Delhi: PG Diploma in Artificial Intelligence
  • Machine Learning PG Program
  • MIT No-Code AI and Machine Learning Course
  • Study Abroad: Masters Programs
  • MS in Information Science: Machine Learning From University of Arizon
  • SRM M Tech in AI and ML for Working Professionals Program
  • UT Austin Artificial Intelligence (AI) for Leaders & Managers
  • UT Austin Artificial Intelligence and Machine Learning Program Online
  • MS in Machine Learning
  • IIT Roorkee Full Stack Developer Course
  • IIT Madras Blockchain Course (Online Software Engineering)
  • IIIT Hyderabad Software Engg for Data Science Course (Comprehensive)
  • IIIT Hyderabad Software Engg for Data Science Course (Accelerated)
  • IIT Bombay UX Design Course – Online PG Certificate Program
  • Online MCA Degree Course by JAIN (Deemed-to-be University)
  • Cybersecurity PG Course
  • Online Post Graduate Executive Management Program
  • Product Management Course Online in India
  • NUS Future Leadership Program for Business Managers and Leaders
  • PES Executive MBA Degree Program for Working Professionals
  • Online BBA Degree Course by JAIN (Deemed-to-be University)
  • MBA in Digital Marketing or Data Science by JAIN (Deemed-to-be University)
  • Master of Business Administration- Shiva Nadar University
  • Post Graduate Diploma in Management (Online) by Great Lakes
  • Online MBA Program by Shiv Nadar University
  • Cloud Computing PG Program by Great Lakes
  • University Programs
  • Stanford Design Thinking Course Online
  • Design Thinking : From Insights to Viability
  • PGP In Strategic Digital Marketing
  • Post Graduate Diploma in Management
  • Master of Business Administration Degree Program
  • MS in Business Analytics in USA
  • MS in Machine Learning in USA
  • Study MBA in Germany at FOM University
  • M.Sc in Big Data & Business Analytics in Germany
  • Study MBA in USA at Walsh College
  • MS Data Analytics
  • MS Artificial Intelligence and Machine Learning
  • MS in Data Analytics
  • Master of Business Administration (MBA)
  • MS in Information Science: Machine Learning
  • MS in Machine Learning Online
  • Data Analytics Course with Job Placement Guarantee
  • Software Development Course with Placement Guarantee
  • MIT Data Science Program
  • AI For Leaders Course
  • Data Science and Business Analytics Course
  • Cyber Security Course
  • Pg Program Online Artificial Intelligence Machine Learning
  • Pg Program Online Cloud Computing Course
  • Data Analytics Essentials Online Course
  • MIT Programa Ciencia De Dados Machine Learning
  • MIT Programa Ciencia De Datos Aprendizaje Automatico
  • Program PG Ciencia Datos Analitica Empresarial Curso Online
  • Mit Programa Ciencia De Datos Aprendizaje Automatico
  • Program Pg Ciencia Datos Analitica Empresarial Curso Online
  • Online Data Science Business Analytics Course
  • Online Ai Machine Learning Course
  • Online Full Stack Software Development Course
  • Online Cloud Computing Course
  • Cybersecurity Course Online
  • Online Data Analytics Essentials Course
  • Ai for Business Leaders Course
  • Mit Data Science Program
  • No Code Artificial Intelligence Machine Learning Program
  • Ms Information Science Machine Learning University Arizona
  • Wharton Online Advanced Digital Marketing Program
  • Artificial Intelligence
  • Python Libraries
  • NumPy Tutorial
  • Data Cleaning In Python
  • Understanding EDA In Python
  • Machine Learning Algorithms
  • Logistic Regression
  • Confusion Matrix
  • Pubg Data Analysis
  • AI as a Service
  • OpenCV Tutorial
  • Edge Detection
  • Facial Recognition Using Python
  • NLTK Tutorial With Python
  • Label Encoding In Python
  • Text Summarization In Python
  • Expert Systems In Artificial Intelligence
  • A* Search Algorithm In Artificial Intelligence
  • Artificial Intelligence Strategies

How Artificial Intelligence and Big Data Together Drive Success – Top 5 Case Studies

  • AI, Big Data and soft drinks 
  • AI, Big Data and Education
  • The case for AI, Big Data and Fake News
  •         Use of digital menus
  •         Customer Experience
  • Autonomous ships, Big Data and AI
  • Healthcare, Big Data and AI
  • Big Data, AI and Security

There is one thing that you will agree with me—that the fourth industrial revolution is here, thanks to AI and Big Data. In fact, according to a report done by CNN there is no accurate figure on the amount of data in Big Data. It is estimated that more than 90% of all data existing right now was created last year – and it keeps increasing.  Even though this is a lot of data, it is useless in its raw form. This is where AI comes in to make sense of the data . As a result, more companies are now embracing AI. According to a survey done by New Vantage Partner more than 95% of Fortune 1000 executives in sixty companies were investing in AI and Big Data. Artificial intelligence and Big Data have revolutionized every industry and companies are continually seeking out ways to make AI and Big Data work for them.  

AI in softdrink industry

Elsevier is one of the global leaders in the publishing of medical and scientific information. Over the years Elsevier has leveraged AI and Big Data to improve its operations. Due to the massive amount of data that the company has collected in its 140-year existence it has built advanced analytics systems using AI and Big Data.  Traditionally, getting information from any of their publications meant that you had to get a paper-based publication or book. However, as Internet usage spread, Elsevier decided to leverage this and digitize its literature. After digitizing the company saw another challenge – information overload. It is estimated that data in the world doubles every two years.  Not all this data is useful, and Elsevier realized that they needed to find a way to cut through the noise and give their readers valuable and actionable data. This is where AI and Big Data came in. AI and Big data were used to study the reading habits of their clients and analyze which kind of data was being consumed a lot. Using these insights they then deployed machine learning to present relevant information to their readers.

AI in entertainment

AI, Big Data and food

McDonald’s, one of the biggest fast-food chains on the planet, is one company that needs no introduction. For a long time, the fast-food chain did not see the need to implement AI and Big Data but upon seeing the success that their competitors were having, they revised their strategy. As the largest fast-food chain in the world, serving close to 70 million people daily, it’s clear that it generates a lot of data. Moreover, they have leveraged that data in many ways as shown below

         Use of digital menus

Digital menus are a common phenomenon these days, but McDonald’s has taken it a notch higher by introducing digital menus that change based on real-time data analysis. The menus vary also based on parameters like weather and time of day. Due to this innovation, they recorded a 3% increase in sales in Canada. 

         Customer Experience

McDonalds are leveraging the application to make it a win-win situation for them and their clients. Users of their app get various benefits like:

  • Exclusive deals on the app.
  • Avoiding long queues at the counter and drive-thru 

On the other hand, when customers pay through the application, McDonald’s not only got money but also vital customer data that includes metrics like:

  • Where and when the client goes to the restaurant
  • The frequency of their visits
  • Preference between a drive-thru or a restaurant

By using this data, McDonald’s can make recommendations and promote deals to increase sales. As a result of this data, they have noticed a more than 30% increase in sales in Japan for clients that used the app. 

Most people know that the future lies in autonomous automobiles, but not many people know that there are also plans to launch autonomous ships. This is due to a collaboration between Google and Rolls-Royce to create autonomous and smart ships. Rolls-Royce will be using the Machine Learning Engine on Google Cloud in its applications to make its vision of smarter and autonomous ships come true.  At first, AI algorithms will be trained using machine learning to identify objects that can be encountered at sea and classify them based on hazard they may pose. The Machine learning algorithms that are currently being used by Google Voice and image search applications. They will also be augmented by massive data sets produced from various devices like sensors, cameras, and cameras on vessels. By combining the cloud-based AI and Big Data application enable data to be shared in real-time to any ship and also to on-shore control centres. 

One of the issues that many healthcare systems face is matching staffing volumes to patient numbers. At one time you can have very few patients and a huge staff roster. During other times, you have an overflow of patients and a strained workforce. So how do you solve this problem? Embrace AI and Big Data by following the example set by some hospitals in Paris. Four hospitals in Paris have managed to leverage AI and Big Data to enable nurses, doctors, and hospital administrators to forecast admission and visit rates for two weeks. This enables them to draft in extra staff when they expect high patient volumes leading to reduced wait times and better-quality care.  So how does the system work? Using an open-source AI Analytics platform, the hospitals compiled admission data for the last ten years and external data sets like flu patterns, weather and public holidays. The insights were then used to predict admission rates at different times. Apart from just being used to predict admission rates, such data can be used to reduce wastage and enhance healthcare delivery by forecasting the demand for services. 

When it comes to security screening, most of us expect that you will find a security person screening you individually using a face-to-face approach. Although customs and immigration officers are highly trained to detect someone that is lying about their intentions mistakes do still happen. Also, there is the fact that humans get tired and can be distracted leading to errors. So how do we avoid such human errors? Apply AI and Big Data to screen passengers.  Homeland security has developed a new system called AVATAR that screens people’s facial expressions and body gestures and picks up small variations that may raise suspicion. The system has a screen with a virtual face that asks the passenger questions. It monitors the person’s responses for changes in voice tone as well as differences in what was said. Data collected is compared to a database and compared against factors that show someone might be lying. If the passenger is flagged as being suspicious then they are highlighted for further inspection. AI and big data are indeed the fourth revolutions. The potential for AI and Big Data is endless. No industry has been disrupted by AI and Big data, and the future belongs to those that leverage it to their benefit. 

Avatar photo

Top Free Courses

coca cola big data case study

El Impacto del Aprendizaje Automático en el Mercado Laboral LATAM

ridge regression

What is Ridge Regression? [Updated]

Time complexity

What is Time Complexity And Why Is It Essential?

artificial intelligence tutorial

Artificial Intelligence Tutorial for Beginners in 2024 | Learn AI Tutorial from Experts

deep learning

Top 20 Applications of Deep Learning in 2024 Across Industries

coca cola big data case study

Basics of building an Artificial Intelligence Chatbot – 2024

2 thoughts on “how artificial intelligence and big data together drive success – top 5 case studies”.

' src=

Thanks for sharing really insightful real life usecases . Great read

Avatar photo

Thank you. Glad you found it helpful!

Leave a Comment Cancel Reply

Your email address will not be published. Required fields are marked *

Save my name, email, and website in this browser for the next time I comment.

Table of contents

Aguijón-morado_Imagineer

  • Customer Experience
  • Digital Experience
  • Employee Experience
  • Partner Experience
  • Business Process
  • Business Model
  • Design Thinking
  • Loyalty Strategy
  • Value Proposition
  • Buyer Persona

Customer Journey

Marketing Automation

  • Account Based Marketing

Growth Driven Design

Inbound Marketing

Customer Relationship Management

  • eCommerce B2C
  • eCommerce B2B
  • Adobe Experience Manager
  • HubSpot CRM
  • Liferay Portal
  • Magento Commerce
  • Marketo Marketing Automation
  • Salesforce CRM
  • Tableau Analytics
  • Red Hat BPM
  • CX Insights
  • English - United States

IMPROVE YOUR CX

Case study: How does Coca-Cola do it in the digital world?

Imagineer favicon

Coca-Cola is undoubtedly one of the most recognized brands in the world, with a market presence that dates back to its beginnings in 1886 when John Pemberton served the first Coca-Cola. Today, the Coca-Cola Company sells hundreds of beverage brands in more than 200 countries. It is calculated that the average person consumes approximately 275 cans of Coca-Cola annually in the United States alone.

  • The digital challenge for Coca-Cola and the "Share a Coke" campaign is a success story.
  • The digital challenge for Coca-Cola.

CocaCola-digital

The digital challenge for Coca-Cola

The challenge for companies like Coca-Cola is that their products' brand presence and positioning are no longer the main issues; instead, they look at marketing strategies oriented toward connection, loyalty, and innovation with their consumers. All this is what James Sommerville, VP of Global Design of Coca-Cola Company, commented for Adobe Summit: We are a 130+-year-old brand that has always been in the experience business. An ice-cold Coke, ice, and lemon in a big glass, there's a fizz and a tingle when you drink it, and that's all very sensory, so we still believe in a physical analog world, which is at the heart and soul of our product, but at the same time, we want to transfer and transform our business, to be able to deliver that experience on a digital platform. The important thing for brands today is to listen to the consumer. Coca-Cola sells almost 2 billion servings daily, and one of the goals we would like to achieve is 2 billion daily conversations.  Two-way conversations so that we not only provide the perfect beverage at the moment they need it but also digital interaction with the customer.  For a company like Coca-Cola that handles large volumes of consumers, regions, products, and channels, it is challenging to have the right platforms to organize communication strategies and effectively serve their customers. Here is where Coca-Cola has developed multiple communication, promotion, and loyalty programs, through digital platforms such as mobile applications, eCommerce B2B / B2C, production of enterprise digital content, and even the creation of the first Coca-Cola flavor in the metaverse.  The "Share a Coke" campaign is a case of success.

Let's examine one example to understand how Coca-Cola uses technology to connect with its consumers. Many will remember the "Share a Coke" campaign in which the logo on the can was replaced with famous names, encouraging customers to share a Coke with a friend or family member. This massively successful social marketing campaign underpinned its process with two main elements to achieve the digital rollout.

share Coca Cola

The first element was the Customer Experience Management platform, which is necessary to manage the campaign data:

  • Segmentation
  • Customer profiling
  • Identity management
  • AI-powered learning
  • Creation of customer experience applications

The Adobe Experience Platform is the foundation that helps companies like Coca-Cola develop a robust foundation for delivering the right experiences to consumers across all channels. >> Case study: Starbucks success with the Inbound Marketing methodology<<

Adobe Experience Platform

The management of digital assets in this Coca-Cola campaign was also an important task to solve, with crucial aspects such as:

  • Personalized and consistent content for each profile
  • Content suitable for each channel/profile
  • Automation rules to be able to scale with minimum effort
  • Ease of creating, distributing, and optimizing experiences on a large scale.

All of this may seem like a Herculean task. Still, it is with the help of specialized platforms that companies like Coca-Cola manage to implement these initiatives and achieve their objectives.

The second element is the Marketing Automation tool, required for a campaign that reached in the beginning alone more than 550 million personalized Coca-Cola, around 340,000 posts on Instagram with the hashtag #shareacoke, and a result by consumers of 96% with positive or neutral feelings towards the campaign.

All this is possible thanks to marketing automation platforms, where Marketo is a fundamental pillar to achieving engagement with customers throughout the customer lifecycle and delighting them to keep them as buyers and brand advocates.

Marketo Engage's always-on marketing principle was able to support Coca-Cola in automating the indispensable aspects of campaigns like this one: >> Main Advantages of Marketo<<

  • Audience segmentation : Profiling communications consider behavioral, demographic, and channel data.
  • Multichannel personalization : Tailored landing pages with conversion-oriented forms for customers receiving profiled communications from websites, emails, SMS, social networks, and events.
  • Customer scoring (lead scoring) : Used this to determine the level of interest of each customer and drive the level of engagement at each stage of the funnel.
  • Active marketing activities : Respond on time to a large contact base. Used automation to respond in real-time when a consumer activates a CTA, sending personalized content.
  • Performance per campaign : Measuring performance in terms of ROI, revenue, investment, and funnel stage allows us to determine which investments yield the best returns.

marketo-automation

Related blog: Case study: Panasonic and its growth with Marketo .

We see how in an increasingly digital world, the challenge for many companies, like Coca-Cola, is how to replicate the physical experience of their products in the digital arena.

Here is where marketing efforts have to lead to the digitization of the experience, where digital processes, strategies, technology, and the consumer as the center of the digital ecosystem must converge.

Finally, the secret ingredient of any digital initiative that Coca-Cola has been developing is innovation in a Customer Experience that moves a consumer thirsty for new and better experiences.

About this blog

Customer Experience Insights is a blog to share ideas, experiences and the vision of how to adopt better Customer Experiences in our organizations. Digital Transformation

Subscribe today

For weekly special offers and new updates!

Recent Posts

Posts by topic.

  • Customer Experience (76)
  • Strategy (70)
  • Methodology (44)

fondoD-1

Improve your presence in digital media

Other Blogs

You may be interested.

author

ABM strategy, the gateway to closing B2B Deals

If 86% of marketers say their ABM strategies acquire more customers than traditional methods, improving customer lifetime value by reporting up to a 76% higher ROI, and their sales and marketing teams have worked exceptionally well together, why haven't all...

Transforming data into business decisions

In daily life, we are constantly bombarded with information. Hundreds of WhatsApp messages, an inbox full of unread emails , and a constant and infinite flow of posts on social media.

Operational Model for Success in 2024

In the dynamic business landscape of 2024, navigating towards the future poses an imperative challenge for organizations seeking sustainable success. The design and implementation of an Operational Model for success take on fundamental significance. This model

         

Customer Commerce Experience

Customer Omnichannel CRM

Customer Portal Experience

Customer Process Automation

Customer Web Experience 

Methodologies

Sales Automation

Lead Conversion

Miami, Florida 333 SE 2nd AVE. 33131

New York, New York City 555 Madison AVE, Manhattan 10022 

San Rafael de Escazú, Costa Rica Centro Corporativo Plaza Roble, 10203. Teléfono: +506 2201 1450

                                            

  • Our company
  • Sustainability
  • Social impact

years of refreshing the world

The Coca‑Cola Company has been refreshing the world and making a difference for over 136 years. Explore our Purpose & Vision, History and more.

  • Purpose & Company Vision
  • The Coca‑Cola System
  • Our Board of Directors
  • COCA-COLA HISTORY
  • Our Origins
  • Our First Bottle
  • Sustainability History
  • Advertising History

brands worldwide

We've established a portfolio of drinks that are best positioned to grow in an ever-changing marketplace.

From trademark Coca‑Cola to Sports, Juice & Dairy Drinks, Alcohol Ready-to-Drink Beverages and more, discover some of our most popular brands in North America and from around the world.

  • Coca‑Cola
  • + View More
  • COFFEE & TEA
  • Costa Coffee
  • Gold Peak Tea
  • JUICES & DAIRY
  • Minute Maid
  • Fresca Mixed
  • Jack Daniel's & Coca‑Cola
  • Simply Spiked
  • Topo Chico Hard Seltzer

OUR PLANET MATTERS

Our purpose is to refresh the world and make a difference. See how our company and system employees make this possible every day and learn more about our areas of focus in sustainability.

  • Water Stewardship
  • 2030 Water Strategy Key Goals
  • Sustainable Agriculture
  • Principles for Sustainable Agriculture (PSAs)
  • Sustainable Packaging
  • Collection Strategy
  • Packaging Design
  • Partnership
  • In Our Products
  • Sugar Reduction
  • 2022 Business & Sustainability Report
  • Sustainability & Governance Resource Center

We aim to improve people's lives, from our employees to those who touch our business to the many communities we call home.

  • Diversity, Equity and Inclusion
  • Leadership Council
  • Employee Groups
  • People & Communities
  • Women Empowerment
  • Project Last Mile
  • HUMAN RIGHTS
  • Human Rights Governance
  • Stories of IMPACT
  • Coca‑Cola Foundation
  • Partnerships
  • Supplier Diversity
  • Sports & Entertainment

We believe working at The Coca‑Cola Company is an opportunity to build a meaningful career while helping us make a real difference on a global scale.

  • LIFE AT COCA-COLA
  • Career Development
  • Work With Us
  • CAREER AREAS
  • Early Career
  • Experienced Professionals
  • Accessible Workplace
  • HIRING PROCESS
  • Application Process
  • Coca‑Cola Company Jobs
  • Coca‑Cola System Jobs

GET THE LATEST

Catch up on the latest Coca‑Cola news from around the globe - from exciting brand innovation to the latest sustainability projects.

  • WHAT OTHERS ARE READING
  • Taste the Transformation: Coca‑Cola and Grammy-Award Winning Artist Rosalía Break Boundaries With Limited-Edition Coke Creation
  • Coca‑Cola Brings Together Iconic Andy Warhol Painting with Illustrious Roster of Master Classics and Contemporary Works in New Global 'Masterpiece' Campaign
  • A Deeper Look  at Coca‑Cola's Emerging Business in Alcohol
  • LATEST ARTICLES
  • Coca‑Cola Zero Sugar Invites Fans to #TakeATaste
  • Simply Mixology Raises the Bar of the At-Home Mocktail and Cocktail Experience
  • Sprite, Fresca and Seagram's Tap Mark Ronson and Madlib to Create a 'Clear' Connection
  • View all news

Coca‑Cola Reports Fourth Quarter and Full-Year 2023 Results

Global Unit Case Volume Grew 2% for the Quarter and 2% for the Full Year

Net Revenues Grew 7% for the Quarter and 6% for the Full Year; Organic Revenues (Non-GAAP) Grew 12% for the Quarter and 12% for the Full Year

Operating Income Grew 10% for the Quarter and 4% for the Full Year; Comparable Currency Neutral Operating Income (Non-GAAP) Grew 20% for the Quarter and 16% for the Full Year

Fourth Quarter EPS Declined 2% to $0.46; Comparable EPS (Non-GAAP) Grew 10% to $0.49; Full Year EPS Grew 13% to $2.47; Comparable EPS (Non-GAAP) Grew 8% to $2.69

Cash Flow from Operations Was $11.6 Billion for the Full Year, Up 5%; Full-Year Free Cash Flow (Non-GAAP) Was $9.7 Billion for the Full Year, Up 2%

Company Provides 2024 Financial Outlook

ATLANTA, Feb. 13, 2024  – The Coca‑Cola Company today reported fourth quarter and full-year 2023 results. “During the year, our people and partners rose to meet new challenges, allowing us to excel globally and deliver in a dynamic world,” said James Quincey, Chairman and CEO of The Coca‑Cola Company. “As we begin a new year, we’re confident that our all-weather strategy, powerful portfolio and harmonized system will continue to create value for our stakeholders in 2024 and for the long term.”

Quarterly / Full-Year Performance

- Revenues : For the quarter, net revenues grew 7% to $10.8 billion, and organic revenues (non-GAAP) grew 12%, driven by 9% growth in price/mix and 3% growth in concentrate sales. The quarter included one additional day, which resulted in a 1-point tailwind to revenue growth. For the full year, net revenues grew 6% to $45.8 billion, and organic revenues (non-GAAP) grew 12%, driven by 10% growth in price/mix and 2% growth in concentrate sales. For both the quarter and the full year, organic revenue (non-GAAP) performance was strong across all operating segments.

- Operating margin : For the quarter, operating margin was 21.0% versus 20.5% in the prior year, while comparable operating margin (non-GAAP) was 23.1% versus 22.7% in the prior year. For the full year, operating margin was 24.7% versus 25.4% in the prior year, while comparable operating margin (non-GAAP) was 29.1% versus 28.7% in the prior year. Operating margin performance included items impacting comparability and currency headwinds. For both the quarter and full year, comparable operating margin (non-GAAP) expansion was primarily driven by strong topline growth, partially offset by an increase in marketing investments versus the prior year, as well as currency headwinds.

- Earnings per share : For the quarter, EPS declined 2% to $0.46, while comparable EPS (non-GAAP) grew 10% to $0.49. EPS performance included the impact of a 14-point currency headwind, while comparable EPS (non-GAAP) performance included the impact of a 13-point currency headwind. For the full year, EPS grew 13% to $2.47, and comparable EPS (non-GAAP) grew 8% to $2.69. EPS performance included the impact of an 8-point currency headwind, while comparable EPS (non-GAAP) performance included the impact of a 7-point currency headwind.

- Market share : For both the quarter and the full year, the company gained value share in total nonalcoholic ready-to-drink (NARTD) beverages.

- Cash flow : Cash flow from operations was $11.6 billion for the full year, an increase of $581 million versus the prior year, driven by strong business performance and working capital initiatives, partially offset by a transition tax payment and currency headwinds. Free cash flow (non-GAAP) was $9.7 billion for the full year, an increase of $213 million versus the prior year.

Company Updates

-  Connecting with consumers through experiences and digital engagement: The company continues to leverage its marketing transformation to build globally scaled marketing platforms tailored to local consumers. In the fourth quarter, “The World Needs More Santas” campaign was executed in over 80 markets, continuing the company’s rich history of celebrating the holidays. The company leveraged the success of its first AI-based platform, “Create Real Magic”, by inviting consumers to create sharable, digital greeting cards featuring iconic brand assets such as cherished depictions of Santa Claus and the Coca‑Cola polar bear. Local initiatives generated buzz and excitement, such as the Coca‑Cola Caravan Truck Tour, which travelled throughout nearly 60 countries around the world making over a thousand stops and meeting over 16 million consumers to share in the magic. In total, the holiday campaign experiences garnered approximately 9 billion impressions on social media. By combining the company’s global scale with local relevancy, the holiday activation contributed to Trademark Coca‑Cola® volume and value share gains as well as unit case volume and transactions growth for both the quarter and for the full year.

-  Building a system that is increasingly positioned for sustainable long-term growth: Since the start of 2023, the company completed the refranchising of company-owned bottling operations in Vietnam to a subsidiary of Swire Pacific Limited (Swire), completed the sale of its stake in the bottler in Pakistan to Coca‑Cola İçecek and completed the sale of its stake in the bottler in Indonesia to Coca‑Cola Europacific Partners (CCEP). More recently, the company completed the refranchising of a portion of its company-owned bottling operations in India to existing franchise bottlers and received regulatory approval to sell its bottling operations in the Philippines to CCEP and Aboitiz Equity Ventures, which is expected to close towards the end of February 2024. Additionally, the company recently completed the sale of its stake in the largest bottler in Thailand to Swire and existing shareholders of the bottler. Our franchise business model has enabled the company to develop a strong global footprint with a local touch in markets around the world. The company continuously works to optimize the system with trusted, capable and motivated bottling partners allowing it to focus on building and growing consumer-loved brands.

-  Delivering on our purpose by empowering people to drive growth: The company’s strategy is centered around people, starting with the employees who are critical in bringing this strategy to life. In November, the company was ranked #1 on the 2023 American Opportunity Index, which assessed how effectively companies enable employees to progress in their careers in the United States. Around the world, the company provides thousands of jobs and is invested in the long-term success of its employees. Over the year, the company enhanced its learning and related technologies, making strides towards nurturing a more innovative and informed workforce. The company’s 2023 Culture & Engagement Survey results underscore the strong levels of employee pride and growth opportunities with a strong number of respondents saying they are proud to work at The Coca‑Cola Company and see good opportunities to learn and grow in their roles.

Operating Review – Three Months Ended December 31, 2023

coca cola big data case study

Operating Review – Year Ended December 31, 2023

coca cola big data case study

In addition to the data in the preceding tables, operating results included the following:

Consolidated

- Unit case volume grew 2% for the quarter. Developed markets were even as growth in Mexico and Germany was offset by declines in the United States and Chile. Developing and emerging markets grew 4%, driven by growth in Brazil and India. For the full year, unit case volume grew 2%. Developed markets grew 1%, driven by growth in Mexico and Germany. Developing and emerging markets grew 2%, driven by growth in India and Brazil, partially offset by the suspension of business in Russia in 2022.

Unit case volume performance included the following:

- Sparkling soft drinks grew 2% for both the quarter and the full year, primarily driven by growth in Latin America and Asia Pacific. Trademark Coca‑Cola® grew 2% for both the quarter and the full year, primarily driven by growth in Latin America and Asia Pacific. Coca‑Cola Zero Sugar grew 4% for the quarter and 5% for the full year, driven by growth in Latin America and North America. Sparkling flavors grew 1% for both the quarter and the full year, primarily driven by growth in Asia Pacific.

- Juice, value-added dairy and plant-based beverages grew 6% for the quarter and 2% for the full year. This performance benefited from growth in Minute Maid® Pulpy in China, Mazoe® in Africa and fairlife® in the United States.

- Water, sports, coffee and tea was even for the quarter and grew 1% for the full year. Water grew 1% for the quarter and 2% for the full year, primarily driven by growth in Latin America. Sports drinks declined 1% for the quarter and were even for the year. Full year performance was benefited by growth in Powerade® in Latin America, offset by a decline in BODYARMOR®. Coffee declined 7% for the quarter and grew 3% for the year. Full year performance was benefited by strong performance of Costa® coffee in the United Kingdom and China. Tea was even for the quarter and declined 1% for the full year, as growth in Latin America and Europe, Middle East and Africa was more than offset by declines in North America and doğadan® in Türkiye.

- Price/mix grew 9% for the quarter and 10% for the full year, primarily driven by pricing actions in the marketplace, including the continued impact of hyperinflationary markets, and favorable mix. For the quarter, concentrate sales were 1 point ahead of unit case volume, primarily due to one additional day.

- Operating income grew 10% for the quarter and 4% for the full year, which included items impacting comparability and currency headwinds. Comparable currency neutral operating income (non-GAAP) grew 20% for the quarter and 16% for the year. For both the quarter and the full year, performance was driven by organic revenue (non-GAAP) growth across all operating segments, partially offset by an increase in marketing investments.

Europe, Middle East & Africa

- Unit case volume grew 1% for the quarter, driven by growth in water, sports, coffee and tea as well as juice, value-added dairy and plant-based beverages. Growth was led by Germany and Nigeria.

- Price/mix grew 24% for the quarter, approximately one-third of which was driven by the continued impact of pricing in hyperinflationary markets and the remaining driven primarily by pricing actions across operating units. For the quarter, concentrate sales were 1 point ahead of unit case volume, primarily due to one additional day.

- Operating income grew 30% for the quarter, which included a 22-point currency headwind. Comparable currency neutral operating income (non-GAAP) grew 50% for the quarter, primarily driven by organic revenue (non-GAAP) growth across all operating units.

- For the year, the company gained value share in total NARTD beverages, led by share gains in Türkiye, Nigeria and Germany.

Latin America

- Unit case volume grew 4% for the quarter, driven by growth in Trademark Coca‑Cola and water, sports, coffee and tea. Growth was led by Brazil and Mexico.

- Price/mix grew 14% for the quarter, primarily driven by the continued impact of inflationary pricing in Argentina and pricing actions, partially offset by incremental investments in the marketplace. For the quarter, concentrate sales were 6 points ahead of unit case volume, primarily due to one additional day and the timing of concentrate shipments.

- Operating income grew 10% for the quarter, which included a 15-point currency headwind and items impacting comparability. Comparable currency neutral operating income (non-GAAP) grew 24% for the quarter, primarily driven by strong organic revenue (non-GAAP) growth, partially offset by an increase in marketing investments.

- For the year, the company gained value share in total NARTD beverages, led by share gains in Brazil, Colombia and Mexico.

North America

- Unit case volume declined 1% for the quarter, as growth in juice, value-added dairy and plant-based beverages and Trademark Coca‑Cola was more than offset by a decline in water, sports, coffee and tea.

- Price/mix grew 8% for the quarter, primarily driven by pricing actions already in the marketplace, timing related adjustments and favorable category mix. For the quarter, concentrate sales were 2 points behind unit case volume, primarily due to the timing of concentrate shipments, partially offset by one additional day.

- Operating income grew 19% for the quarter, which included items impacting comparability. Comparable currency neutral operating income (non-GAAP) grew 5% for the quarter, primarily driven by organic revenue (non-GAAP) growth.

- For the year, the company gained value share in total NARTD beverages, driven by sparkling soft drinks and value-added dairy beverages.

Asia Pacific

- Unit case volume grew 2% for the quarter, primarily driven by growth in juice, value-added dairy and plant-based beverages and sparkling flavors. Growth was led by India and China.

- Price/mix grew 10% for the quarter, primarily driven by pricing actions in the marketplace and favorable category mix. For the quarter, concentrate sales were 1 point ahead of unit case volume, primarily due to one additional day.

- Operating income grew 6% for the quarter, which included items impacting comparability and a 13-point currency headwind. Comparable currency neutral operating income (non-GAAP) grew 18% for the quarter, driven by organic revenue (non-GAAP) growth across all operating units and lower operating costs, partially offset by an increase in marketing investments.

- For the year, the company gained value share in total NARTD beverages, led by share gains in India, the Philippines, South Korea and Japan.

Global Ventures

- Net revenues grew 10%, and organic revenues (non-GAAP) grew 5% for the quarter, primarily driven by the strong performance of Costa® coffee in the United Kingdom and China.

- Operating income and comparable currency neutral operating income (non-GAAP) both had robust growth for the quarter, driven by organic revenue (non-GAAP) growth and lower costs.

Bottling Investments

- Unit case volume declined 1% for the quarter, as growth in India and the Philippines was more than offset by the impact of refranchising bottling operations.

- Price/mix grew 7% for the quarter, driven by pricing actions across most markets.

- Operating income grew 38% for the quarter, which included items impacting comparability and an 8-point currency headwind. Comparable currency neutral operating income (non-GAAP) grew 66% for the quarter, driven by organic revenue (non-GAAP) growth, partially offset by higher operating costs.

Capital Allocation Update

-  Reinvesting in the business: The company continued to invest in its various lines of business and spent $1.9 billion on capital expenditures in 2023, an increase of 25% versus the prior year.

-  Continuing to grow the dividend: The company paid dividends totaling $8.0 billion during 2023. The company has increased its dividend in each of the last 61 years.

-  M&A initiatives: In 2023, the company did not make any significant acquisitions. The company continues to evaluate inorganic growth opportunities through brands and capabilities. In 2023, with respect to divestitures, the company made progress towards refranchising company-owned bottling operations.

-  Share repurchases: In 2023, the company issued $0.5 billion of shares in connection with the exercise of stock options by employees and purchased $2.3 billion of shares. Consequently, net share repurchases (non-GAAP) were $1.7 billion. The company’s remaining share repurchase authorization is approximately $6 billion.

The 2024 outlook information provided below includes forward-looking non-GAAP financial measures, which management uses in measuring performance. The company is not able to reconcile full-year 2024 projected organic revenues (non-GAAP) to full-year 2024 projected reported net revenues, full-year 2024 projected comparable net revenues (non-GAAP) to full-year 2024 projected reported net revenues, full-year 2024 projected underlying effective tax rate (non-GAAP) to full-year 2024 projected reported effective tax rate, full-year 2024 projected comparable currency neutral EPS (non-GAAP) to full-year 2024 projected reported EPS, or full-year 2024 projected comparable EPS (non-GAAP) to full-year 2024 projected reported EPS without unreasonable efforts because it is not possible to predict with a reasonable degree of certainty the exact timing and exact impact of acquisitions, divestitures and structural changes throughout 2024; the exact timing and exact amount of items impacting comparability throughout 2024; and the exact impact of fluctuations in foreign currency exchange rates throughout 2024. The unavailable information could have a significant impact on the company’s full-year 2024 reported financial results.

Full Year 2024

The company expects to deliver organic revenue (non-GAAP) growth of 6% to 7%.

For comparable net revenues (non-GAAP), the company expects a 2% to 3% currency headwind based on the current rates and including the impact of hedged positions, in addition to a 4% to 5% headwind from acquisitions, divestitures and structural changes.

The company’s underlying effective tax rate (non-GAAP) is estimated to be 19.2%. This does not include the impact of ongoing tax litigation with the IRS, if the company were not to prevail.

Given the above considerations, the company expects to deliver comparable currency neutral EPS (non-GAAP) growth of 8% to 10% and comparable EPS (non-GAAP) growth of 4% to 5%, versus $2.69 in 2023.

Comparable EPS (non-GAAP) percentage growth is expected to include a 4% to 5% currency headwind based on the current rates and including the impact of hedged positions, in addition to an approximate 2% headwind from acquisitions, divestitures and structural changes.

The company expects to generate free cash flow (non-GAAP) of approximately $9.2 billion through cash flow from operations of approximately $11.4 billion, less capital expenditures of approximately $2.2 billion. This does not include any potential payments related to ongoing tax litigation with the IRS.

First Quarter 2024 Considerations

Comparable net revenues (non-GAAP) are expected to include an approximate 4% currency headwind based on the current rates and including the impact of hedged positions, in addition to an approximate 2% headwind from acquisitions, divestitures and structural changes.

Comparable EPS (non-GAAP) percentage growth is expected to include an approximate 8% currency headwind based on the current rates and including the impact of hedged positions, in addition to an approximate 1% headwind from acquisitions, divestitures and structural changes.

The first quarter has one less day compared to the first quarter of 2023.

- All references to growth rate percentages and share compare the results of the period to those of the prior year comparable period, unless otherwise noted.

- All references to volume and volume percentage changes indicate unit case volume, unless otherwise noted. All volume percentage changes are computed based on average daily sales in the fourth quarter, unless otherwise noted, and are computed on a reported basis for the full year. “Unit case” means a unit of measurement equal to 192 U.S. fluid ounces of finished beverage (24 eight-ounce servings), with the exception of unit case equivalents for Costa non-ready-to-drink beverage products which are primarily measured in number of transactions. “Unit case volume” means the number of unit cases (or unit case equivalents) of company beverages directly or indirectly sold by the company and its bottling partners to customers or consumers.

- “Concentrate sales” represents the amount of concentrates, syrups, beverage bases, source waters and powders/minerals (in all instances expressed in unit case equivalents) sold by, or used in finished beverages sold by, the company to its bottling partners or other customers. For Costa non-ready-to-drink beverage products, “concentrate sales” represents the amount of beverages, primarily measured in number of transactions (in all instances expressed in unit case equivalents) sold by the company to customers or consumers. In the reconciliation of reported net revenues, “concentrate sales” represents the percent change in net revenues attributable to the increase (decrease) in concentrate sales volume for the geographic operating segments and the Global Ventures operating segment after considering the impact of structural changes, if any. For the Bottling Investments operating segment for the fourth quarter, this represents the percent change in net revenues attributable to the increase (decrease) in unit case volume computed based on total sales (rather than average daily sales) in each of the corresponding periods after considering the impact of structural changes, if any. For the Bottling Investments operating segment for the full year, this represents the percent change in net revenues attributable to the increase (decrease) in unit case volume after considering the impact of structural changes, if any. The Bottling Investments operating segment reflects unit case volume growth for consolidated bottlers only.

- “Price/mix” represents the change in net operating revenues caused by factors such as price changes, the mix of products and packages sold, and the mix of channels and geographic territories where the sales occurred.

- First quarter 2023 financial results were impacted by one less day as compared to first quarter 2022, and fourth quarter 2023 financial results were impacted by one additional day as compared to fourth quarter 2022. Unit case volume results for the quarters are not impacted by the variances in days due to the average daily sales computation referenced above.

Conference Call

The company is hosting a conference call with investors and analysts to discuss fourth quarter and full-year 2023 operating results today, Feb. 13, 2024, at 8:30 a.m. ET. The company invites participants to listen to a live webcast of the conference call on the company’s website, http://www.coca-colacompany.com, in the “Investors” section. An audio replay in downloadable digital format and a transcript of the call will be available on the website within 24 hours following the call. Further, the “Investors” section of the website includes certain supplemental information and a reconciliation of non-GAAP financial measures to the company’s results as reported under GAAP, which may be used during the call when discussing financial results.

Forward-Looking Statements

This press release may contain statements, estimates or projections that constitute “forward-looking statements” as defined under U.S. federal securities laws. Generally, the words “believe,” “expect,” “intend,” “estimate,” “anticipate,” “project,” “will” and similar expressions identify forward-looking statements, which generally are not historical in nature. Forward-looking statements are subject to certain risks and uncertainties that could cause The Coca‑Cola Company’s actual results to differ materially from its historical experience and our present expectations or projections. These risks include, but are not limited to, unfavorable economic and geopolitical conditions, including the direct or indirect negative impacts of the conflict between Russia and Ukraine and conflicts in the Middle East; increased competition; an inability to be successful in our innovation activities; changes in the retail landscape or the loss of key retail or foodservice customers; an inability to expand our business in emerging and developing markets; an inability to successfully manage the potential negative consequences of our productivity initiatives; an inability to attract or retain a highly skilled and diverse workforce; disruption of our supply chain, including increased commodity, raw material, packaging, energy, transportation and other input costs; an inability to successfully integrate and manage our acquired businesses, brands or bottling operations or an inability to realize a significant portion of the anticipated benefits of our joint ventures or strategic relationships; failure by our third-party service providers and business partners to satisfactorily fulfill their commitments and responsibilities; an inability to renew collective bargaining agreements on satisfactory terms, or we or our bottling partners experience strikes, work stoppages, labor shortages or labor unrest; obesity and other health-related concerns; evolving consumer product and shopping preferences; product safety and quality concerns; perceived negative health consequences of certain ingredients, such as non-nutritive sweeteners and biotechnology-derived substances, and of other substances present in our beverage products or packaging materials; failure to digitalize the Coca‑Cola system; damage to our brand image, corporate reputation and social license to operate from negative publicity, whether or not warranted, concerning product safety or quality, workplace and human rights, obesity or other issues; an inability to successfully manage new product launches; an inability to maintain good relationships with our bottling partners; deterioration in our bottling partners’ financial condition; an inability to successfully manage our refranchising activities; increases in income tax rates, changes in income tax laws or the unfavorable resolution of tax matters, including the outcome of our ongoing tax dispute or any related disputes with the U.S. Internal Revenue Service (“IRS”); the possibility that the assumptions used to calculate our estimated aggregate incremental tax and interest liability related to the potential unfavorable outcome of the ongoing tax dispute with the IRS could significantly change; increased or new indirect taxes; changes in laws and regulations relating to beverage containers and packaging; significant additional labeling or warning requirements or limitations on the marketing or sale of our products; litigation or legal proceedings; conducting business in markets with high-risk legal compliance environments; failure to adequately protect, or disputes relating to, trademarks, formulas and other intellectual property rights; changes in, or failure to comply with, the laws and regulations applicable to our products or our business operations; fluctuations in foreign currency exchange rates; interest rate increases; an inability to achieve our overall long-term growth objectives; default by or failure of one or more of our counterparty financial institutions; impairment charges; an inability to protect our information systems against service interruption, misappropriation of data or cybersecurity incidents; failure to comply with privacy and data protection laws; evolving sustainability regulatory requirements and expectations; increasing concerns about the environmental impact of plastic bottles and other packaging materials; water scarcity and poor quality; increased demand for food products, decreased agricultural productivity and increased regulation of ingredient sourcing due diligence; climate change and legal or regulatory responses thereto; adverse weather conditions; and other risks discussed in our filings with the Securities and Exchange Commission (“SEC”), including our Annual Report on Form 10-K for the year ended December 31, 2022, and our subsequently filed Quarterly Reports on Form 10-Q, which filings are available from the SEC. You should not place undue reliance on forward-looking statements, which speak only as of the date they are made. We undertake no obligation to publicly update or revise any forward-looking statements.

Download Q4 and Full-Year 2023 Earnings Results

Related Content

Coca‑Cola Collaborates with Tech Partners to Create Bottle Prototype Made from 100% Plant-Based Sources

100-plant-based-banner

Coca‑Cola Launches ‘Real Magic’ Brand Platform, Including Refreshed Visual Identity and Global Campaign

coca-cola-real-magic-billboard

Iteration, for Good: How Project Last Mile is Supporting COVID-19 Vaccine Distribution in Africa and Beyond

iteration-for-good

Coca-Cola revenue tops estimates on robust demand, higher prices

Traffic passes a Coca-Cola digital billboard in the Times Square area of Manhattan

Reporting by Ananya Mariam Rajesh in Bengaluru; Editing by Arun Koyyur

Our Standards: The Thomson Reuters Trust Principles. , opens new tab

coca cola big data case study

Thomson Reuters

Ananya reports on the U.S. Consumer and Retail Sector covering breaking and business news on publicly listed retailers, apparel makers, cruises, luxury brands, beverage companies and restaurants groups.

A keyboard and a shopping cart are seen in front of a displayed Shein logo in this illustration picture

Singapore's UOB revises down 2024 loan growth, Q4 profit beats forecasts

Singapore's United Overseas Bank (UOB) on Thursday cut its 2024 loan growth projections to low single-digits from mid-single digits after posting a stronger-than-forecast 22% jump in fourth quarter net profit.

Media tour at the Amazon's Fulfillment center in Tepotztlan

coca cola big data case study

FILE - Bottles of Coca Cola are shown in a market in Pittsburgh on Jan. 26, 2023. Coca Cola reports results on Tuesday, Feb. 13, 2024. (AP Photo/Gene J. Puskar)

Cans of Coca-Cola Spiced, the beverage company’s first new permanent offering to its North American portfolio in three years, are introduced at a livestream media event, Tuesday, Feb. 6, 2024, in New York. (AP Photo/Bebeto Matthews)

  • Copy Link copied

Coca-Cola reported higher-than-expected revenue in the fourth quarter as growth in Mexico, Germany and other markets offset lower demand in the U.S.

Revenue rose 7% to $10.8 billion for the October-December period, the Atlanta beverage giant said Tuesday. That topped Wall Street’s forecast of $10.7 billion, according to analysts polled by FactSet.

Coke’s revenue got a 10% boost from higher prices in 2023, but the company said that was partly due to hyperinflationary conditions in a handful of markets like Argentina. The company expects full-year organic revenue to grow at a more moderate pace of 6% to 7% this year, down from last year’s 12% growth.

“We anticipate hyperinflationary pricing will continue to play a role in 2024 but will moderate throughout the year,” Coke Chief Financial Officer John Murphy said in a conference call with investors.

An employee straightens displays at a Kohl's store in Clifton, N.J., Friday, Jan. 26, 2024. A year ago, the store had tables stacked high with sweaters and shirts in a rainbow of colors as well as dress racks crammed with a wide assortment of styles. Now, it boasts a more edited approach — tables have slim piles of knit shirts that focus on fewer colors, and many dress racks have been reduced to just three or four styles. (AP Photo/Seth Wenig)

Unit case volumes rose 2% in the quarter, led by sparkling soft drinks, juices and Coca-Cola Zero Sugar. Sports drinks, coffee and tea all saw lower demand.

In North America, unit case volumes declined 1% as growing sales of juice, dairy and Coca-Cola were offset by falling demand for water, sports drinks, coffee and tea. Coke said its North American prices rose 8% in both the fourth quarter and the full year.

Chairman and CEO James Quincey said price increases have clearly squeezed some consumers who are going out less often and buying more drinks for the home. But he said Coke continues to see strong buying power from other consumers, who are opting for higher-priced beverages like Fairlife milk, Core Power protein shakes and Simply juices.

“There’s clearly multiple things going on in the landscape in terms of categories and price points and we’ve been working to address both ends of those,” Quincey said.

Unit case volumes rose in Coke’s other global markets, although Coke said it did see some slowdown in demand due to the war in the Middle East. Several other big U.S. companies, including Starbucks and McDonald’s , have also reported disruptions in sales due to the war.

Net income fell 3% to $1.9 billion, or 46 cents per share. Without one-time items, including restructuring costs, the company earned 49 cents per share. That was in line with Wall Street’s forecast.

Coke shares were unchanged in early trading.

coca cola big data case study

IMAGES

  1. Coca Cola Market Penetration Case Study; PESTEL & SWOT Analysis

    coca cola big data case study

  2. 7 Ways Coca-Cola Uses AI and Big Data

    coca cola big data case study

  3. Avoid repetitive work and develop data thinking: Tableau helps COFCO

    coca cola big data case study

  4. Coca-Cola Case Study Analysis

    coca cola big data case study

  5. Coca Cola Market Research Case Study

    coca cola big data case study

  6. Big Data & Coca-Cola

    coca cola big data case study

COMMENTS

  1. Coca Cola Leverages Data Analytics to Drive Innovation

    [i] Given the size of its operations, Coca Cola generates a substantial amount of data across its value chain - including sourcing, production, distribution, sales and customer feedback. Over the years, the company has embraced Big Data to drive its business strategic decisions.

  2. The Amazing Ways Coca Cola Uses Artificial Intelligence And Big Data To

    In fact, Coca Cola was one of the first globally-recognized brands outside of the IT market to speak about Big Data, when in 2012 their chief big data officer, Esat Sezer, said "Social...

  3. Tech and Big Data Accelerate Innovation Strategy

    Coca‑Cola North America's Decision Science and Data Strategy Center of Excellence analyzes all data captured across Coke's digital ecosystem, giving teams across the company a big-picture view of opportunities.

  4. Artificial Intelligence at Coca-Cola

    Artificial Intelligence at Coca-Cola - Two Current Use-Cases Last updated on July 19, 2021, published by Megan Jarrell Today, Coca-Cola is the world's largest beverage company, selling over 500 soft drinks in more than 200 countries. In 2020, Coca-Cola had over 80 thousand employees worldwide.

  5. Coca-Cola's Unique Challenge: Turning 250 Datasets Into One

    To make sense of a mountain of complex data, the world's largest beverage company takes a forward-looking approach. Mathew Chacko, Coca-Cola's director of enterprise architecture, and Remco Brouwer, the company's director of business intelligence, are tasked with integrating data from 250 bottlers around the world — and then giving them ...

  6. (PDF) Innovation business model of Big Data------ Taking Coca-Cola as

    Big data enables Coca-Cola to connect to the preferences of these followers, and can promote the . ... The paper choose s the case of Coca-Cola to study based on the concept model of business .

  7. Coca-Cola: Real-World Data Analytics Example

    Data is changing the way Coca-Cola approaches its marketing strategies. Coca-Cola uses data gathered from consumer feedback to create advertising that speaks...

  8. How Coca-Cola Takes A Refreshing Approach On Big Data

    One of the most refreshing approaches on big data is that Coca-Cola uses it to produce orange juice that has a consistent taste year-round, although the oranges used have a peak-growing season of just three months. They have developed an algorithm, called the Black Book model, that combines various data sets such as satellite imagery, weather ...

  9. Build Data Lake using AWS

    2021 Coca-Cola Andina Builds Data Lake on AWS, Increases Analytics Productivity by 80% for More Data-Driven Decision-Making

  10. Coca-Cola Leans On Data Analytics & AI For Deeper Industry Insights

    Coca-Cola, one of the biggest companies in the world, is the poster child to show how big data analytics can be used to optimize marketing. It is not only one of the biggest companies in the world, but also, arguably, the biggest brand in the world. For any brand, the top priority is ensuring that advertising messaging stays constant across ...

  11. Coca-Cola overcomes challenges to seize BI opportunities

    The Coca-Cola Co. understands that analytics challenges can be overcome and that a team approach helps businesses take advantage of BI opportunities. Imagine integrating data from 74 unique databases, all using distinct software to store and analyze data. Imagine trying to stitch together this patchwork of homegrown and small-scale analytics ...

  12. Coca-Cola Employing Business Intelligence to Transform its Business

    Case Studies Technology Coca-Cola Employing Business Intelligence to Transform its Business Abstract Case Intro 1 Case Intro 2 Excerpts Excerpts Business Intelligence (BI) BI consisted of all the processes and methods of collecting, storing, and analyzing data from business operations to provide a complete view of the business.

  13. PDF Coca-Cola

    Case Study Coca-Cola 'Pay by the Drink' Flexibility Creates Major Eficiencies and Revenue for Coca-Cola's International Bottling Investments Group (BIG) 2

  14. Swire Coca-Cola Case Study

    Swire Coca-Cola Case Study. 2019. Get Solutions. For 200 years, Swire has grown into a highly diversified business group working in the aviation, beverage, food, industrial, marine services, and property industries, guided by a commitment to operational excellence and a forward-looking approach. Swire Coca-Cola, a division of Swire, has the ...

  15. The Coca-Cola Company on AWS: Case Studies, Videos, Innovator Stories

    2021 Coca-Cola Andina Builds Data Lake on AWS, Increases Analytics Productivity by 80% for More Data-Driven Decision-Making Coca-Cola Andina promotes the profitable growth of its business, supports customers, and delivers the best possible experience to more than 54 million consumers in Argentina, Brazil, Chile, and Paraguay.

  16. Valuing your talent: Coca-Cola

    Valuing people. This case study provides insight into Coca-Cola Enterprises' (CCE) data analytics journey. Given the complexity of the CCE operation, its global footprint and various business units, a team was needed to provide a centralised HR reporting and analytics service to the business. This led to the formation of a HR analytics team ...

  17. Coca-Cola BIG chooses NTT DATA for SAP SuccessFactors Implementation

    Abstract The Coca-Cola Bottling Investment Group (BIG) is part of the Coca-Cola Company focusing on bottling and distribution of Coca-Cola products with operations in markets in Southeast Asia, India, Middle East and Southwest Asia, covering 16 countries with 39 plants and 28,000 employees, serving over 1.8 billion consumers.

  18. Coca-Cola Consolidated Automates their Data Testing with ...

    As the largest bottler of Coca-Cola in the United States, Coca-Cola Consolidated handles critical business data from a multitude of sources with different technology implementations. Ensuring the validity of this data as it passes through integration points in their system is a key goal of the QA team as these integrations are used to conduct vital business operations.

  19. How Artificial Intelligence and Big Data Together Drive Success

    AI, Big Data and soft drinks. Everyday people consume 1.9 billion servings of Coca Cola drinks. Due to this huge market share in the beverage space, Coca Cola generates a lot of data that it uses to make strategic decisions. Coca Cola was the earliest non-IT company to adopt AI and Big Data. Coca Cola is known for investing heavily in research ...

  20. Study on Use of AI and Big Data for Commercial System

    ... Huge datasets can be analyzed by AI algorithms to find patterns, trends, and preferences, which can lead to new and creative ideas that appeal to the target audience. This enables advertisers...

  21. Case study: How does Coca-Cola do it in the digital world?

    Coca-Cola is undoubtedly one of the most recognized brands in the world, with a market presence that dates back to its beginnings in 1886 when John Pemberton served the first Coca-Cola. Today, the Coca-Cola Company sells hundreds of beverage brands in more than 200 countries. It is calculated that the average person consumes approximately 275 ...

  22. A Case Study on Coca-cola Strategy in using AI and Big Data to Drive

    A Case Study on Coca-Cola: Strategy in using AI and Big Data to Drive Success VI. Implementation The Coca-Cola Company is one of the world's largest beverage company offering for over 500 various brands to people in more than 200 countries across the globe.

  23. Coca Cola

    Coca Cola beverages Africa is number Coca Cola bottler in Africa and eighth largest brand on global revenue. This is possibly achieved by the brand due to adaptation of Microsoft Technologies like Dynamics 365, Microsoft 365 and Azure. It has resulted in reducing its IT costs from 2.85% of net sales revenue to just below 1.4% ! While they have

  24. After 39 Long Years, Coca-Cola Just Made a Big Announcement, and It All

    Especially if we're talking about a really, really big mistake. Case in point: The rollout of "New Coke" in April 1985, just shy of 39 years ago. During the first half of the 20th Century, Coca ...

  25. Coca‑Cola Reports Fourth Quarter and Full-Year 2023 Results

    Cash Flow from Operations Was $11.6 Billion for the Full Year, Up 5%; Full-Year Free Cash Flow (Non-GAAP) Was $9.7 Billion for the Full Year, Up 2%. Company Provides 2024 Financial Outlook. ATLANTA, Feb. 13, 2024 - The Coca‑Cola Company today reported fourth quarter and full-year 2023 results. "During the year, our people and partners ...

  26. Coca-Cola revenue tops estimates on robust demand, higher prices

    Coca-Cola sees annual adjusted profit to be between 4% and 5%, compared to LSEG estimates of a 4.5% growth. Its net revenue rose 7.4% to $10.95 billion beating expectations of $10.68 billion while ...

  27. Coca-Cola Has a Sparkling Outlook for 2024. What Investors Need to Know

    Management put some hard numbers behind those positive comments. Coke is projecting organic sales growth of between 6% and 7% (compared to Pepsi's 4%) for 2024. The company is also expecting ...

  28. Coca-Cola Rises as Full-Year Outlook Beats Expectations

    0:23. Coca-Cola Co. rose after the company gave a 2024 organic revenue outlook that beat expectations. The beverage giant expects organic revenue growth of 6% to 7%, ahead of analysts ...

  29. Coca-Cola overcomes falling demand in North America and puts up strong

    Unit case volumes rose 2% in the quarter, led by sparkling soft drinks, juices and Coca-Cola Zero Sugar. Sports drinks, coffee and tea all saw lower demand. In North America, unit case volumes declined 1% as growing sales of juice, dairy and Coca-Cola were offset by falling demand for water, sports drinks, coffee and tea.