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Volume-Data storage, How does the beverage industry keep up with changing customer behaviour, stay relevant, and adapt?
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Data is expanding at an exponential rate that shows no signs of slowing down. In fact, according to IDC, global data generation will reach 175 zettabytes by 2025.
It is, however, more complicated than a simple rise in data volume and rapid expansion. Data comes from a variety of places, is stored in a variety of formats, and comes from a variety of sources. Consider the following: 80% of all data generated will become dormant legacy data, never to be accessed or used again. Regardless, it must be kept up to date and understood at all times. Because of time-sensitive business requirements and litigation-related requests, companies must adhere to data retention and compliance regulations, as well as be able to access information at a moment's notice.
Many IT leaders are struggling to figure out what to do with all of this data: where to store it, how to ensure it is accessible when needed, and how to stay within – or, better yet, free up – budget constraints.
How does the beverage sector keep up with changing customer behaviour, stay relevant, and adapt? In an ever-evolving digital ecosystem, consumer insights are essential.
We realize that business-to-consumer brands can have radically varied outcomes in and within each region of the world, and what better illustration than the beverage industry. The global carbonated market is expected to earn $412.5 billion USD by 2023, when broken down into its many subdivisions.
How does Budweiser using the data they collected
AB InBev, the world's largest global beer corporation and one of the top five consumer products firms, is the parent company of over 500 brands, including Budweiser, Bud Light, and Stella Artois. Its well-known brands are well-known all over the world. AB InBev is a company that not only makes beer, but also markets, distributes, and sells it. The company uses a customer marketing approach that the rest of the industry can learn from, and it revolves around gaining a better understanding of their customers: what they purchase, why they buy it, when they buy it, and how the brand fits into their lives. One thorn in the company's side had always been its data silos, which had no way of connecting until lately.
With its global business consumer data platform, AB InBev engaged Treasure Data to solve its data challenge. Treasure Data collaborated with AB InBev to create a standardized taxonomy that brought together all of the company's diverse data sources into a single database that could be improved and augmented. As a result of these efforts, there is now a single source of truth, thanks to freshly consolidated consumer profiles.
Lucas Borges, senior manager, consumer data strategy at AB InBev, tells AdExchanger, “We had too many brands, too many countries, too many people and too many ways of working.” Many of its brands work with different agencies, each of which is responsible for its own customer marketing campaigns. Without a centralized customer database, there was no way for AB InBev to know if the Corona customer in database A was the same one in Bud Light customer database B.
AB InBev can now deliver better personalisation, execute post-campaign data analysis more efficiently, and obtain deeper insights after laying the basis to structure its data. AB InBev may use a combination of data to deliver the proper product mix and highly targeted marketing initiatives, such as real-time vouchers at the point of sale that are personalized to the right customers.
How Coca Cola uses the their customer data base
Customer analytics, according to Coca-Cola, provides valuable insight into who is drinking their drinks, where they are situated, and what motivates them to mention the brand online. They utilize this information to show consumers more focused advertisements, which are four times more likely to result in a click, according to Coca-Cola.
Furthermore, Coca-Cola has benefited from customer analytics in a number of areas, including product creation. In 2017, it was discovered that data acquired from self-service drinks fountains that allow consumers to mix their own beverages was used to inspire the development of the new Cherry Sprite flavour.
The results of this study were revealed when it was revealed that the choice to introduce Cherry Sprite as a new flavour was based on data obtained from the current generation of self-service soft drink fountains, which allow consumers to mix their own beverages.
Coca-Cola also completely utilizes social media analytics, which is understandable given the company's 35 million Twitter followers and 105 million Facebook admirers. With those types of figures, the corporation is sitting on a gold mine of information. This information is used to track how Coca-Cola products are represented on social media channels. In 2015, this resulted in the calculation that every two seconds, the company's products were discussed somewhere in the world. Information gleaned from social media allows for near-real-time decisions.
Thank you, please comment if you like the information.
Chohan, S. (no date) How Coca Cola Collect Consumer Insights with Creative Campaigns. Available at: https://www.linkfluence.com/blog/how-coca-cola-collects-consumer-insights-with-creative-campaigns (Accessed: 28 June 2021).
‘How Coca Cola uses customer data to sell more’ (2019) AdroitBI, 19 March. Available at: http://www.adroitbi.com/coca-cola-uses-customer-data-sell/ (Accessed: 28 June 2021).
How the Beer Industry Turns Data Into Profits - Treasure Data Blog (no date). Available at: https://blog.treasuredata.com/blog/2020/10/15/how-the-beverage-industry-turns-data-into-profits/ (Accessed: 28 June 2021).
How to Better Manage Growing Data Volumes While Maximizing IT Budget (no date). Available at: https://www.ironmountain.com/blogs/2019/how-to-better-manage-growing-data-volumes-while-maximizing-it-budget (Accessed: 28 June 2021).
(How the Beer Industry Turns Data Into Profits - Treasure Data Blog, no date)(How to Better Manage Growing Data Volumes While Maximizing IT Budget, no date)
Great research work...! I was finding some research on data volume and probably i came to know that According to the 3Vs model, the challenges of big data management result from the expansion of all three properties, rather than just the volume alone -- the sheer amount of data to be managed. An organization can be better equipped to deal with big data challenges through understanding the 3Vs of their big data management.
Gartner analyst Doug Laney introduced the 3Vs concept in a 2001 MetaGroup research publication, 3D data management: Controlling data volume, variety and velocity. More recently, additional Vs have been proposed for addition to the model, including variability -- the increase in the range of values typical of a large data set -- and value, which addresses the need for valuation of enterprise data.
Good job, Pramod! Great article you have written here. I would complement the challenge that companies are facing nowadays about the volume of data. Volume is the V that is most closely linked with big data because volume can be significant. Creating and keeping up data can seem a simple process but can be out of control when the data is growing without managing it. Data is the key to a successful business; however, it is requested to be analyzed to get insights from it. Big data may be used to assess the influence of industry trends on stock consumption and shows the temperature has on product quality to give better value to the consumer.
Very well explained, A greater volume of data is advantageous to enterprises because the more integrated perspective an organization has on a user/customer, derived from both current and historical data, the more insight they can extract. As a result, firms may make better judgments about gaining, keeping, growing, and managing user/customer relationships. To expose in-depth information for judgments, high velocity, high volume, and high variety data must be processed using advanced technologies such as analytics and algorithms. Volume in Data storage also refers to the size of the data which an organization collects which is analysed the processed in further.
It was a nice read and to know how brands like Coca-Cola, Budweiser, Stella are collecting and using data base. One of the most important part of Big data is Volume. The term "big data" refers to a large amount of information. Data volumes that, in fact, can reach unimaginable heights. According to estimates, 2.5 quintillion bytes of data being created every day, resulting in 40 zettabytes of data being created by 2020 – a 300-fold increase from 2005. As a result, huge corporations today routinely store Terabytes – and even Petabytes – of data on storage devices and servers. This information aids in the shaping of a company's future and actions, as well as the tracking of progress. - Mohit Jain
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ReplyDeleteI was finding some research on data volume and probably i came to know that
According to the 3Vs model, the challenges of big data management result from the expansion of all three properties, rather than just the volume alone -- the sheer amount of data to be managed. An organization can be better equipped to deal with big data challenges through understanding the 3Vs of their big data management.
Gartner analyst Doug Laney introduced the 3Vs concept in a 2001 MetaGroup research publication, 3D data management: Controlling data volume, variety and velocity. More recently, additional Vs have been proposed for addition to the model, including variability -- the increase in the range of values typical of a large data set -- and value, which addresses the need for valuation of enterprise data.
ReplyDeleteGood job, Pramod! Great article you have written here. I would complement the challenge that companies are facing nowadays about the volume of data. Volume is the V that is most closely linked with big data because volume can be significant. Creating and keeping up data can seem a simple process but can be out of control when the data is growing without managing it.
Data is the key to a successful business; however, it is requested to be analyzed to get insights from it. Big data may be used to assess the influence of industry trends on stock consumption and shows the temperature has on product quality to give better value to the consumer.
Very well explained, A greater volume of data is advantageous to enterprises because the more integrated perspective an organization has on a user/customer, derived from both current and historical data, the more insight they can extract. As a result, firms may make better judgments about gaining, keeping, growing, and managing user/customer relationships. To expose in-depth information for judgments, high velocity, high volume, and high variety data must be processed using advanced technologies such as analytics and algorithms. Volume in Data storage also refers to the size of the data which an organization collects which is analysed the processed in further.
ReplyDeleteIt was a nice read and to know how brands like Coca-Cola, Budweiser, Stella are collecting and using data base. One of the most important part of Big data is Volume. The term "big data" refers to a large amount of information. Data volumes that, in fact, can reach unimaginable heights. According to estimates, 2.5 quintillion bytes of data being created every day, resulting in 40 zettabytes of data being created by 2020 – a 300-fold increase from 2005.
ReplyDeleteAs a result, huge corporations today routinely store Terabytes – and even Petabytes – of data on storage devices and servers. This information aids in the shaping of a company's future and actions, as well as the tracking of progress.
- Mohit Jain