In the past few years D2C businesses have leveraged customer interaction data to learn and adapt and grow
Big Data Analytics helps extract meaningful insights from vast datasets by combining both structured and unstructured data from these sources.
Ms. Anjna Bhati, CTO, BluePi
Big data analytics has come a long way since the spreadsheet days to now specialized data platforms. Earlier analytics was the domain of centralized teams gathering data, running queries, building reports and then socializing the findings. However now, data democratization is the key to push the data analytics downstream and enable smart decision making for all departments and functions. In the past few years D2C businesses have leveraged customer interaction data to learn and adapt and grow. Right now the trend is all invasive, with large conglomerates realizing they are sitting on a gold mine with decades of not only customer data, but market data, sales, finance, marketing, supply chain, operations just to name a few. The next decade belongs to enterprising organizations who can enable their teams to access, analyze and use the insights on demand.
Being a key tool in Business Intelligence and decision-making, more organizations are leveraging data analytics solutions across Sales, Marketing, finance, vendor management, supply chain and Customer Service functions to improve the performance metrics of the available data. This increase in the use of digital solutions and the adoption of specialized databases are further fuelling the big data analytics market. According to Fortune Business Insights, the global big data analytics market size, which was USD 271.83 billion in 2022, is projected to grow from USD 307.52 billion in 2023 to USD 745.15 billion by 2030, establishing a CAGR of 13.5% during the forecast period. This high growth reveals how data today is considered a valuable asset for businesses, providing the key to future growth. The huge volumes of data generated every day need to be gathered and analyzed, which is where big data analytics plays a significant role in the entire process.
In the next few lines, we will explore how data analytics can drive an organization’s revenues and business growth and take a look at how to get started with the process.
Provides better actionable insights
Today’s businesses have to choose data from several sources that provide information about customers. Data can be extracted from purchase history, customer support calls, reports, social media activities, computer cookies, and more. Big Data Analytics helps extract meaningful insights from vast datasets by combining both structured and unstructured data from these sources. Patterns can be identified and market trends predicted with a good understanding of customer preferences for taking the right action.
Customer understanding and acquisition are made easy
For businesses, nothing is as important as gaining a deep understanding of their customers, their preferences, and their requirements. Big Data Analytics enables observing the patterns of consumers and using them to gain brand loyalty by identifying other aspects that make them happy. Then organizations can provide suggestions to customers, develop targeted marketing campaigns, provide customer product offerings, enhance the customer experience, and exceed customer expectations. Greater brand loyalty helps improve revenues for the organization.
Operational efficiencies are enhanced
Data Analytics is critical to improving operational efficiency in organizations across various industries. Unplanned downtime and production costs can be achieved with predictive maintenance. The solution can analyze operational data, like supply chain information, the performance of the employees, and production metrics. With this procedure, businesses can quickly spot bottlenecks, streamline processes, reduce waste significantly, and increase throughput. The approach also enables better allocation of resources and enhances productivity, business outcomes, and financial performance, further driving sustainable operations and continuous improvement.
Enables discovery of new trends
Pattern recognition is the most important part of big data analytics. When these patterns keep recurring, it clearly sheds light on emerging market trends. Organizations can then focus on innovation and developing new products to cater to these new market trends and opportunities while staying ahead of the curve. Businesses can update products and innovate new ones. They can even track customer feedback, get an idea of what competitors are doing, and develop products that will succeed.
Furthermore, big data analytics can also predict upcoming risks, and any tasks that are not required for operations can be eliminated, clearing the path for smooth business growth.
Implementing a big data analytics solution is complex, challenging, and requires expertise. Only with proper planning and execution can businesses extract insights from data to establish a competitive edge. A suitable service provider with previous experience in configuring and implementing the most appropriate solution for the organization’s requirements can achieve this. It is also important to note that data analytics is a long process, and it is extremely important for businesses to remain patient to make better decisions in the future.
By revolutionizing the business landscape, big data analytics solutions are offering unprecedented opportunities for fast yet sustainable growth, an increase in revenues, and long-term success.
