How to use predictive analytics to help your businessAug 19, 2019 | 109 views
Predictive analysis is nothing more than the use of statistical algorithms and machine learning to anticipate future results based on historical data. It sounds like science fiction, but this tool is already a reality and is revolutionizing the market and making a difference in business decision making.
In addition to generating revenue increase, the use of data allows you to customize offers based on the purchasing profile of each consumer, thus also improving the customer experience. The goal of using this type of technology is to go beyond statistics and provide a better assessment of what will happen in the future. The result is the generation of new insights about products, markets, sales, information such as average ticket and other data that make a difference in decision making.
The differential in using predictive analytics is that it supports organizations making decisions looking to the future, not just at what has already passed. The data allow the creation of predictive models, according to each business, and help predict market needs and problems with the intention of anticipating solutions.
It is up to each company to seek a solution of big data and analytics, as has the GPA Group to achieve goals, which can vary between:
- qualify the customer base;
- identify trends;
- better understand your market;
- decide whether or not to continue a product or service.
With a technological solution, it is possible to cross-data with existing platforms, such as Facebook, for example. One of the great pains Big Data tries to solve is unstructured data. For example, information that may be contained in a video posted on the social network.
In this sense, it is also possible to analyze a brand's reputation through online monitoring, in real time, to identify strengths and even to contain the negative impact of possible crises.
Another frequent use of analytics is the company's 360-degree analysis, which helps identify fraud risks. A bank, for example, through predictive data analysis can identify which customer has a greater predisposition to consume a given credit service.
The applications of predictive analytics for insights into products, services and other aspects of business are numerous. The value of data analysis to support business decision-making increases significantly while data generation also only increases.