Convert Mobile Data to Money
In recent years, huge amounts of data are produced every day. This big data phenomenon is shifting the global economy toward complex profitable data analysis and management. Entrepreneurs and giant companies are analyzing this fact and looking for ways to monetize such data. You are certainly creating not only business opportunities, but also employment opportunities.
Big Data is embracing the economy, one business sector at a time. In fact, with the vast amount of data of approximately 2.7 Zetabytes in today’s digital universe. It is sure to create jaundice opening opportunities that were never considered possible. In this article we will discuss convert mobile data to money.
Here’s Five Best Ways to Convert Data into Money
Through automated algorithms, managers can make better decisions through more accurate data analysis. Instead of predictive analysis, they generate predictive analysis using hypothesis testing through a controlled experiment. With this, they can test the one that works best with the strategy with little risk.
Customer or service specialization
Businesses can better reach their target consumers through segmentation. In this way, they see the most appropriate products and / or services for the consumer segment. For example, Facebook links features and ads to users. By combining data from different applications, they create behavior patterns and therefore make appropriate suggestions. Meanwhile, Amazon offers a variety of dynamic content and pricing, using real-time analytics, for different sets of users, and makes changes as they go.
Product or service innovation
Crowdsourcing is more effective through social networks. Consumer information can be obtained from various tweets (converted into usable data) that companies use to develop and innovate products and services. Additionally, the data is becoming a stand-alone product as analysts use it to provide companies with a more complete picture to improve operations, thereby creating new sources of revenue.
Instead of learning backwards, preventive measures can now be taken through predictive analytics. GE, for example, can help its airlines monitor customer GE jet engine performance, thus anticipating maintenance needs.
By analyzing and comparing data across warehouse branches, a particular retail company can properly distribute warehouse performance and consumer behavior with product distribution, limiting overstocking.
Organizations and business leaders will need to inventory their data assets to identify potential value creation opportunities. While this creates employment opportunities, it also requires equipping people. Technology development is central because only a few people can handle large amounts of data, not to mention that they can effectively manipulate, aggregate, and analyze such data.
Privacy and security remain a problem for the IT industry and business. Policymakers have yet to address legal concerns, establishing an intellectual property framework and creating policies that balance privacy concerns with value capture.
Before you go, I hope this above article convert mobile data to money is helpful and informational for you.