Big Data is a term that is already part of everyday business. Big Data defines the immeasurable volume of data (structured or not) that impact business in your day-to-day life. Much more important than the amount of data that is generated daily is what companies can effectively do with this data in order to increase the quality of their performance. According to IBM, there are now three times more devices connected to the Internet than people in the World. This data is more than enough proof of the amount of information that is generated every minute, which is a challenge for companies. But how can they take advantage of the data generated daily? In this article we will talk about the main opportunities created by the big data.
The data come from the most diverse channels and through Big Data it is possible to centralize them and group them by affinities. It is possible to be closer to the customer through the collection of data through questionnaires, applications, loyalty cards, among other instruments. The data collected is essential for assertive planning of marketing and communication actions. By having a better knowledge of the characteristics of customers, it is also possible to offer better after-sales service, thereby increasing customer satisfaction and retention rate.
Information is growing at a very fast pace, which makes its analysis increasingly difficult. The ideal solution is to analyze the data in real time to make the most of the information. Products like Multipeers allow us to analyze every second what is happening with the business. In this way, you can make the most of the data to make the best decisions for the business. Combining the large amount of data generated in companies with a real-time analysis allows you to get insights essential to business success and allows decisions to be made in a timely manner.
Data controllers should be able to quickly define various forecasting problems. Companies should focus on simple predictive models and find possible solutions. In this way, they don’t spend as much time as they would if they created a model of a very sophisticated machine that consumes more resources and more expenses. Although the Big Data issue seems very complex, the trick is to simplify processes and invest more time in data extraction and analysis.