More companies are turning to predictive analytics to optimize their processes, achieve better business results and increase their market share.
Organizations use internal predictive analytics to forecast trends, understand and predict customer behavior, improve performance and drive strategic decision making.
You may be interested in: “What are predictive models and what are they used for?“
Some of the most common internal uses of predictive analytics are:
Fraud Detection: Help to reduce and eliminate losses generated by fraudulent activities before they occur, obtaining greater accuracy and better performance. With predictive models it is possible to analyze all the actions of a network in real time to detect anomalies that may indicate fraud, vulnerabilities and threats.
Marketing: Improve relationships with customers, anticipating their behavior, to promote sales opportunities, attracting, retaining and identifying the most profitable customers.
Operations: Help forecast inventory needs and manage the organization’s resources to optimize expenses and costs.
Risk: Credit scoring, for example, is used to assess the likelihood that a potential home, car or insurance buyer will default on payment. They are also used in other related processes, such as in claims and collections.
Customer Loss: Predict which customers, when and why they will terminate their relationship with the organization. Predictive models are fundamental in this area, since the cost of losing a very good customer can be much higher than the investment in tools to detect these situations in time and prevent them from happening.
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Sales Forecasting: analyzes previous history, seasonality, market events, etc. to provide a realistic prediction of the demand for a product or service. It can be applied in the short, medium or long term.
Finance: translating a set of hypotheses about the behavior of markets or agents into numerical predictions, these predictive models are used to support companies in decision-making processes about investments or returns.
Also read: “Data Science: Most used models in business.”
At PREDIK Data-Driven we develop all kinds of predictive models for our clients. Learn more about how we do it.