Organizations want to know whether certain products or services they plan on releasing will be successful, whether their customer base will expand or shrink based on a strategic decision, or whether their investments will pan out as desired.
Considering the reduced costs of technology, data collection, analysis and storage, in addition to recent innovations and increased power of sophisticated data science and analytics, predictive modeling is now available to both small and mid-sized organizations at reasonable cost.
Several techniques – according to the nature of the business problem and current conditions – can be used when conducting predictive modeling. These include regression techniques, time series models, decision trees, and machine learning methods, among others.