Big data refers to large amounts of data, stored by companies, that are unable to be processed by traditional data processing. The number of sources of data is ever increasing. This has led to an exponential growth in the amount of structured and unstructured data being created and is fast becoming the norm for companies every day. Big data is relative to the amount of computing power a company has. A small company may consider big data thousands of gigabytes, while a large enterprise may consider big data hundreds of terabytes. In order to gain a competitive edge, organizations, big or small, must learn to utilize their data effectively.
Big data is often spoken of in conjunction with broad terms like predictive analytics and behavioral analytics. Data analytics programs are used with more specific tools like data mining to gain insights from large amounts of data, which will enable businesses to make predictions and conclusions that will aid an organization in making effective business decisions and increase share of wallet.
A survey by PricewaterhouseCoopers revealed that 43 percent of all companies obtain little tangible benefit from their information, while 23 percent derive no benefit whatsoever. Data is available for analysis, but many companies haven’t integrated it at all.
The potential for big data is similar to a dating service. Rather than matching people to other people, big data can match people to products. It also helps make informed decisions regarding customers and the business at every level. Customers need to stop receiving offers that don’t apply to them and begin receiving things that will help them. They want to deal with companies that understand where they are coming from and can offer contextual products and services while anticipating needs. Big data gives companies that power.
The landscape of organizations is being changed by big data. Data is emerging as the newest resource for competitive advantage. It’s being used to make informed decisions at every level and bringing teams from around the company together. No area is using big data more than customer experience (CX). In fact, 64 percent of organizations see CX as the primary goal for big data. In addition, 1/3 of big data projects were initiated by line-of-business owners with vested interest in customers.
Applications for big data are as large as the data sets themselves. Yet, they all have the same end goal: to make the customers’ experience as seamless as possible. The customer-company relationship is precarious and has to be perfectly balanced in order to endure long term.
The customer experience should be helpful, but not intrusive. Big data opens the door to companies so that a perfect balance can be achieved and the customers can maintain their seamless experience. Finding a place to get started can be difficult, especially in the face of overwhelming data with the imminent realization that exponential amounts will shortly arrive.
Big data is daunting. Even though it has been touted as the holy grail of business problems, it does have significant limitations. While big data provides hundreds of correlations through analysis, it cannot prioritize those and come to conclusions as to which ones are most significant. In addition, there is already a dearth of data specialists and big data is only compounding that. Supercomputers can process huge amount of data but even with that, there still needs to be application to business solutions, done by data scientists. Big data isn’t the silver bullet to all problems, but it is a fantastic tool to aid in solving them.
Big data is not something to fear. When properly integrated, analyzed, and used, it can create wonderful opportunities to connect with customers by providing a more seamless and personalized experience. Companies can halt meaningless offers sent to customers and start providing them offers that will help their lives.
We believe that big data should be used to solve business issues. This is done by collecting, analyzing and applying big data. Using advanced data collection and analyzation techniques such as text analytics, data mining, and predictive analytics, data insights are collected that will allow the customers to have a more personalized experience. This will create customers that continuously make purchases, are loyal to the brand, all of which ultimately affect a company’s bottom line. The dividends of big data may take time. However, in the end, it is an investment well made.