In today's world, where humans are relying on machines to get their work done, it becomes necessary to manage them well. Machines are being made smart by mounting artificial intelligence in them. Gadgets are interconnected over the internet to serve us better.
Every tech geek must be familiar with the importance of data, why just tech geeks, all of us now know what data is. To make the aforementioned things possible, machines require a lot of data. Now the question is where do they obtain such vast data from and how do they get the exact required data. The answer is pretty simple, from a place where all such data is stored.
We, humans, have created technology, so our traditional ways of managing things would be reflected in our inventions. Like in the olden days, people used to store important documents in one place. Even there used to be lockers to store highly important documents.
Similarly, now we maintain our data digitally. We have digital lockers too. This is a micro-level data management i.e for individuals. When looked at the macro level i.e. for bigger firms, it requires a big setup to store such a vast amount of data and process them when required.
So, humans found a technical solution to this as well, and that is termed Big data analytics. Since everything is technology-driven, the amount of data produced has also increased. In this blog, we will be looking at the definition of big data analytics, as well as its five efficient uses by the companies to serve their consumers better.
Big data analytics means to examine and analyze data on a larger scale. Nowadays, organizations require to understand the patterns in their consumers' behavior, and big data analytics facilitate them with the same. This analytics help them to uncover hidden patterns, correlations, and also give insights to make better business decisions.
There is a question that may arise and that is why do organizations need to rely on big data analytics? The answer is, organizations have understood the need to evolve from a knowing to a learning organization. Moreover, they want to be more objective and data-driven and so they are using the best gift of the human brain— technology. Data analytics help them anticipate any behavior change in their consumers and also such analytics enhance accuracy.
Big data analytics is done using advanced software systems that are efficient and more instantaneous. This ability to work faster and achieve agility offers a competitive advantage to businesses. In the meantime, businesses enjoy lower costs using big data analytics software. Big Data is used in almost every sector be it the food industry, content marketing, or even elections.
So, since now we have understood the role of big data analytics, we should proceed to the main part of the blog i.e. five ways in which businesses are using big data analytics.
"Information is the oil of the 21st century, and analytics is the combustion engine”
-Peter Sondergaard, Senior Vice President, Gartner
Customers are the most valuable asset to any business, be it an already established firm or a growing one. It's the solid customer base that every business craves for and there is no single business that can claim success without having to establish a solid customer base. Big data analytics, as mentioned above, helps businesses understand their consumers' behavior.
The use of big data allows businesses to observe various customer-related patterns and trends. Observing customer behavior is important to trigger loyalty. We, humans, have our traits and characteristics, and we are identified by those traits. Companies too understand this and try to collect as much data possible. They further use this data to modify their approach towards their customers.
When we talk of customers, it covers both the existing as well as potential customers. Big data analytics has facilitated businesses with a lot of information about their customers that is used by businesses to increase customer acquisition as well as retain the existing customers. Understanding customer insights will allow businesses to be able to deliver what the customers want from them. This is the most basic step to attain high customer retention.
(It may interest you to read about the use of big data by Tesco.)
In a time of fierce competition, businesses thrive to retain their positions in the market. A business is successful if they can communicate well with their audience and as we know advertising is a major tool of marketing communications. It requires a lot of insights like consumer behavior, purchase pattern, customers' interest, etc. to create a fruitful advertisement.
Earlier, when there was no technical support, businesses lost millions in running ad campaigns that were not fruitful, and the reason isn't a mystery at all. But nowadays, when we are living in a technology-rich world, why not use them to the fullest. Big data analytics is one such gift that has benefited a lot of businesses.
These days, businesses use big data to design their campaigns. The market insights involve observing the online activity, monitoring the point of sale transactions, and ensuring on the fly detection of dynamic changes in customer trends. These are then used to identify the target group, which is the most important thing to consider while designing a campaign.
Big campaigns can't be designed on mere guessing, but rather on accurate data which is retrieved from the big data analytics. Examples of this are before us every day. We search for a product on any random platform and then our screen is flooded with the ads of that product. This shows how crucial the role has big data analytics achieved.
Also, take a look at how Instagram is using Big Data.
Some statistics to show the importance of Big Data Analytics
For unprecedented situations like the Coronavirus pandemic, and a highly risky business environment asks for better risk management. A risk management plan is a critical investment for any business regardless of the sector. Being able to foresee potential risk and mitigating it before it occurs is critical if the business has to remain profitable.
Big data analytics has helped in risk management in a way that has contributed greatly to the development of risk management solutions. It's been said that ‘prevention is better than cure and it holds for every situation. Why wait for the knife to be put on the throat if it can be avoided.
Risk management requires a concrete strategy and to come up with better ailment, businesses use big data analytics. They try to understand the possible risks and form a strategy accordingly. Interestingly, both of these are done from the big data collected.
“Gone are the days when you could go with your gut”.
To improve the quality and streamline manufacturing performance businesses need to collect huge data. The gut intuition is basically no longer reliable if an organization wants to compete in the 21st Century. This means that these organizations must come up with means for tracking their products, competitors, and customer feedback. And we all now know how these can all be retrieved, from big data analytics.
For any business to develop a new product, it requires them to understand the demands. Every design process has to begin by establishing what exactly fits the customers. There are various channels through which an organization can study customer needs. Then the business can identify the best approach to capitalize on that need based on big data analytics.
Recommended blog - Big Data in Manufacturing
There is nothing mysterious about the role of big data analytics in Supply chain management. When we look at its definition, “Supply chain management is the management of the flow of goods and services and includes all processes that transform raw materials into final products.
It involves the active streamlining of a business's supply-side activities to maximize customer value and gain a competitive advantage in the marketplace.” (Investopedia), it's quite evident how big data can be helpful.
To better manage the supply chain, businesses need accurate and clear insights into the market and this is taken from big data analytics. Through this, businesses can achieve contextual intelligence across the supply chain. The release of goods and services will be monitored based on data retrieval from big data and in this way companies/businesses can avoid the incurrence of huge losses.
There are a variety of approaches for detecting a business's ideal demographic through analytics. The consumer base and social media data of the business are highly valuable data sources.
The competitor's audience can also be examined and publicly available is highly fruitful. By adopting analytics for analyzing the audience, the businesses derive practical and useful data
Tools like Google Analytics make it effective to gather data about users. Analytics plugins can also be added on the sites for understanding the user behavior.
Upon the ideal demographic being determined, tailored content and solutions can be provided. As a result, leveraging analysis can result in more conversions.
Recommended blog - Big Data Analytics in AI
When the audience has been segmented through analytics tools, large-scale personalization can be enabled. Tools can be set for personalizing email marketing content expertly.
The content can be personalized for targeting a wider section of audience and for simultaneously creating personalization. The reach of the business can be enhanced in turn leading to higher conversions.
Brands using Big Data Analytics
Big data analytics is a gift and businesses can invest in this area to better as well as retain their position in the market. Implementation of big data analytics helps businesses to achieve a competitive advantage, reduce the cost of operation, and also customer retention. The five ways in which a business can benefit from big data analytics also makes its implementation understandable.
Every aspect needs attention to achieve success, and in this technology-rich world why not utilize it to look after those aspects. The whole game now relies on better data analytics for any kind of success in any sector. Big data analytics is the best thing to be used.
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