AI Glossary · AI Analytics
Predictive Analytics
Using historical data and ML to forecast future outcomes — churn, upsell, delinquency, part failure, agent attrition.
Definition
What is Predictive Analytics?
Predictive Analytics is using historical data and ML to forecast future outcomes — churn, upsell, delinquency, part failure, agent attrition.
- Category
- AI Analytics
- Glossary set
- 7 related terms
- Audience
- Enterprise AI leaders
Why does Predictive Analytics matter in enterprise AI?
Predictive Analytics matters in enterprise AI programs because it helps business and technology leaders align vocabulary, scope, ownership, and measurable outcomes.
Related terms in AI Analytics
- Anomaly Detection
- Identifying data points or events that deviate from expected patterns — fraud, outages, churn signals, quality defects.
- Cohort Analysis
- Grouping users or accounts by shared traits and tracking behavior over time — foundational for retention, LTV and AI-experiment readouts.
- Conversation Intelligence
- Mining sales and support conversations for coaching, deal-risk and product signals (Gong, Chorus, Genesys AI, NICE Enlighten).
- Forecasting
- Time-series prediction of demand, staffing, revenue or risk; ML models routinely outperform spreadsheet baselines.
- Prescriptive Analytics
- Going beyond prediction to recommend the action that maximizes an objective; the analytics stage that connects to agentic AI.
- Segmentation
- Grouping customers or accounts by behavior and value using clustering; drives targeting, service tiering and lifecycle marketing.