How to Benefit From Predictive Analytics

Evan Pearce
Solutions Manager

Stock image of a computer screen showing various analytical data

Predictive analytics encompasses a variety of statistical techniques including data mining, predictive modeling and machine learning to analyze current and historical data to provide a prediction of what will happen in the future.

AI, big data analytics, and data science are a growing trend in many industry sectors. Growing volumes and types of data paired with the need for competitive differentiation is propelling businesses to uncover complex correlations in their data, identify unknown patterns and get a view into forecasting. Predictive analytics can help solve a variety of issues and uncover new opportunities including:

  • Anomaly / Fraud Detection
  • Sales & Marketing Analysis
  • Improving Operational Efficiencies
  • Risk Reduction

The ability to proactively anticipate outcomes and behaviour based on data is applicable to every industry. Below we’ll explore a few industry-specific examples.

Financial Services

Predictive analytics can help financial services companies with churn prevention, demand forecasting, and fraud detection by monitoring customer transactions and flagging any transactions that deviate from a standard behavior.


Improving profitability is a key driver for predictive analytics in many high tech companies. Advanced analytics are being deployed to more easily identify customer buying behavior, sentiment analysis, and customer issues by exploring patterns in historical data.


Predictive analytics is being used in a wide variety of health care projects, from medical research to patient care. Machine learning can help predict a variety of patient-related risks, such as those at risk of developing chronic disease, high infection rates in a specific geography and where future nursing care shortages may occur.

Consumer Goods

Many CPG companies use analytics to identify the right target audience, improve customer engagement, refine pricing strategies, manage inventory and fraud detection.

Summing It Up

No matter what industry you are in, predictive analytics requires the perfect blend of domain expertise, the right set of tools and the advanced analytics chops to gain accurate, actionable results. At Indellient, we work alongside our clients to provide the IT, data engineering and data science skill sets, using industry-best vendors to ensure complete customer success.

About The Author

Evan Pearce

Hello, I’m Evan Pearce. I’m a Solutions Manager at Indellient. I closely work with our clients to develop solutions by bringing together business acumen, strong technical aptitude and novel methodologies. I help our clients connect the dots when it comes to integrating different pieces of a solution together. I love discovering new ways in which technology can solve challenging problems. Some of my favorite tools are SiSense, Datastage, SSIS, Redshift, Hive, S3, PureData, Periscope, PowerBI and Presto.