Coca-Cola collects big data for competitive advantage.

Coca-Cola collects big data for competitive advantage.

Coca-Cola “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” (Marr, 2017).

Coca-Cola collects big data for competitive advantage. In 2015, Coca-Cola began a digitally led loyalty program. There was an interview of the director of data strategy at Coca-Cola by ADMA that disclosed that that dig data analytics is powerfully behind retention of customers (Tan, 2017). Coca-Cola has a huge item portfolio that leads to a large variety of items that can be selected for customers which is one of the top qualities. Coca-Cola has over 20 bands that are billion-dollar brands (Press Release, 2015). Of these billion-dollar brands, there are 18 that are available in the low or no calorie options. Due to the desire for products that are better for individuals wellbeing, Coca-Cold has developed a large array of products that support the healthier lifestyle.

Values of data mining or a business include it is helpful to predict trends, customer habits, helps with decision making, provides quick fraud detection, and can increase revenue. Data mining is helpful to predict trends because it carries all the information about their customers (The value of data mining, 2019). Because the information about the customers is available, data mining signifies customers habits as well as helps in decision making. Data mining can identify fraud by collecting data and identifying the fraudulent acts and products (The value of data mining, 2019).

Challenges of a data mining project include incomplete data, distributed data, and data privacy and security (Wideskills, 2015). Incomplete data could result from “errors of the instruments that measure the data or because of human errors” (Wideskills, 2015). Incomplete data can cause data mining to be challenging. “Real world data is usually stored on different platforms in distributed computing environments. It could be in databases, individual systems, or even on the Internet” (Wideskills, 2015). Due to this, it is often times hard to bring all the data together. Due to the nature of data mining, there is typically “serious issues in terms of data security, privacy and governance” (Wideskills, 2015).

Resources:

Marr, B. (2017, September 18). The amazing ways coca cola uses artificial intelligence and big data to drive success. Retrieved March 19, 2021, from https://www.forbes.com/sites/bernardmarr/2017/09/18/the-amazing-ways-coca-cola-uses-artificial-intelligence-ai-and-big-data-to-drive-success/?sh=6ff58a6678d2

Press release. (2015, February 05). Growing roster of Billion-Dollar Brands. Retrieved March 19, 2021, from https://www.coca-colacompany.com/press-releases/coca-cola-grows-roster-of-billion-dollar-brands-to-20

Tan, A. (2017, March 20). How Coca-Cola uses data to supercharge Its SUPERBRAND status. Retrieved March 19, 2021, from https://www.adma.com.au/resources/how-coca-cola-uses-data-to-supercharge-its-superbrand-status

The value of data mining. (2019, September 19). Retrieved March 22, 2021, from https://vividus.com.au/value-data-mining/#:~:text=Effective%20data%20mining%20will%20teach,appropriate%20channel%20to%20increase%20conversions.&text=Understanding%20your%20customers%20better%20provides,on%20its%20own%20at%20least.

Wideskills. (2015). Retrieved March 22, 2021, from https://www.wideskills.com/data-mining/challenges-in-data-mining