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Predictive Analytics: an anticipation strategy to strengthen your businesses

Predictive Analytics: an anticipation strategy to strengthen your businesses

Have you ever wondered if your company was able to predict the future? That would be quite an advantage, wouldn't it? Yes! As it would be possible to anticipate customer needs and be much more accurate in the creation and development of products and services. What if we tell you that there is a tool that can help in this regard? It's predictive analysis! 

Logically, this tool is not a crystal ball. However, it is a solution that has been adopted by companies from the most diverse segments to solve problems and innovate. 

Want to know what predictive analytics is? Read on and find out how it works and what its benefits are.

What is predictive analytics?

Predictive analytics is a technique that statistically combines historical data with algorithms to identify the likelihood of future results. It will therefore not tell us what will happen in the future, but what could happen with some degree of probability. 

It includes a series of so-called data mining techniques, which exploit statistical analysis, machine learning, and also the modeling of data with queries, typical of database systems. Analysts have long been exploiting its potential. But if areas such as prediction and risk aversion and fraud detection are territories already successfully explored by this methodology, the world of digital marketing represents a scenario that predictive analysis has only recently appeared on.

Benefits of Predictive analytics in businesses

Reduce losses with resource allocation

Cost management plays a crucial role in the organization's results, and this requires resources to be allocated intelligently. Whether in relation to human or material resources, management based on predictive models is much more successful, as it allows you to assess the impacts of different scenarios.

 For instance, if the expansion of the business demands an increase in the service capacity, the predictive models may suggest more viable alternatives such as the outsourcing of part of the call center - or, at least, for a transition period. And to hire an outsourced call center, the company, once again, will be able to use its structured information to determine which size of the operation to negotiate.

Create differentiated strategies in the market 

Being ahead of the competition is another advantage that predictive analytics can provide. By identifying market patterns and trends, the company can make decisions in advance. A chain of beauty products can identify the increase in consumers in a given region and, thus, direct its strategy of expanding franchises to that location. 

Another scenario exemplified by the adoption of predictive analysis is the revelation that interest in sustainable products has grown. In this way, the company has enough information - and reliability - to decide to develop a test line well ahead of its competitors.

Aid for fraud prevention

The combination of different analytical models makes it possible to find patterns of fraud and prevent the occurrence of wrong behavior. This issue is even more important for cyber security, as all network actions are evaluated in real-time to signal abnormalities, vulnerabilities, and persistent threats. It is also worth reinforcing credit operations, which are safer with the help of forecasts. This aspect is even more important for credit card transactions since the system can issue alerts or activate protection mechanisms.

Conclusion

Finally, predicting the future is something that has become more accurate with the evolution of predictive analysis systems. In businesses, this can represent an enormous gain in competitiveness and management intelligence. 

After all, several business processes can be improved, such as the segmentation of marketing actions, the management of inventory, or the pricing of offers. But it is worth remembering that it's not necessary to apply predictive analysis on all fronts of the virtual store. The rational stance, here, is important not only to put aside thinking but also to know which areas would be most impacted by the analysis.