What Is Predictive Analytics?

Predictive analytics allows companies to use multidimensional factors to identify growth opportunities and risks, particularly when used to examine insights found within big data.

Written by Anthony Corbo
Published on Jan. 03, 2023
What Is Predictive Analytics?
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Peter Grant | Jan 06, 2023

Predictive analytics is a form of advanced analytics that uses historical data, statistical modeling, data mining techniques and machine learning to uncover patterns and form predictions about future outcomes. 

Where Can I Use Predictive Analytics?

  • Marketing and e-commerce
  • Financial forecasting
  • Long and short-term lending
  • Insurance
  • Healthcare
  • Company operations and logistics
  • Meteorology and weather forecasts

Related Reading on Built In5 Probability Questions to Test Your Data Skills


What Is Predictive Analytics Used For?

Predictive analytics is used to heighten competitive advantage and increase revenue by using insights uncovered from data.

Predictive analytics can be exceptionally useful in a number of areas, including:

  • Recommending similar purchases to shoppers 
  • Developing algorithms to suggest relevant content based on user interests and preferences
  • Fraud detection and risk reduction
  • Determining whether to extend credit to a person or organization by using previous credit history and income factors to determine the likelihood of defaulting on a loan
  • Predicting when and why patients may be readmitted to the hospital
  • Creating and optimizing marketing campaigns to account for factors such as seasonality, customer behavior and cross-selling opportunities
  • Improving operations within a company by using forecasting models to determine the best allocation of resources

These are just a few areas in which predictive analytics are routinely employed. There are many, many more.

The Fundamentals of Predictive Analytics. | Video: Decisive Data


What Does a Predictive Analyst Do?

Predictive analysts examine data and build analytical models that predict future outcomes of ongoing events or trends.

Predictive analysts are responsible for analyzing data volumes and uncovering insights that can be proven based on trends in data. These analysts then build predictive forecasting models to predict how these trends will expand over time and what threats companies should be aware of. 

Becoming a predictive analyst, sometimes referred to as an operations research analyst depending on the context, requires all of the prerequisites for becoming a data scientist, such as a bachelor’s degree in math, science or a similar field, a master’s degree in data science or statistics, and extensive data training and experience.

According to the Bureau of Labor Statistics, the median annual wage for operations research analysts was $86,200 in May 2020, with the lowest ten percent earning less than $48,050 and the highest ten percent earning more than $144,330. For more salary information submitted directly by industry professionals, see Built In’s salary tool.

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