The future is uncertain, however, using historical data can help predict it. More and more businesses are utilizing predictive analytics to determine patterns and forecast possible future outcomes and trends. Predictive analytics extracts information from data. The goal of predictive analytics is to provide a near accurate assessment of what may happen in the future and to streamline the decision-making process.
Applying predictive analytics to your business will help you better understand your organization, industry and clients, recognize trends and help your business identify weaknesses and threats.
Predictive analytics approaches and techniques can be broadly grouped into regression techniques and machine learning techniques.
- Regression models are the cornerstone of predictive analytics. Its focus involves establishing a mathematical equation as a model to represent the interactions between the different variables. Depending on the circumstance, there are several models that can be applied while performing predictive analytics.
- Machine learning is the science of getting computers to act without being explicitly programmed. It is a branch of artificial intelligence that was originally used to develop techniques to enable computers to learn..
Incorporating predictive analytics into your organizational framework will empower your business to anticipate customer needs, predict buying patterns and offer complementary products and services to them.