What Is Machine Learning?
Machine learning trains algorithms on historical data to make predictions or decisions. Unlike traditional software where a programmer writes rules ("if revenue $1M, route to junior rep"), ML systems learn optimal rules from data ("customers with 5+ support tickets are 3x more likely to churn"). Plura's conversation analysis uses ML to automatically detect intent, sentiment, and quality patterns from thousands of conversations.
Supervised vs. Unsupervised Learning
Two main ML approaches:
Supervised: Train on labeled data ("these conversations converted, these didn't"). Model learns to predict which new conversations will convert. Used for lead scoring, churn prediction.
Unsupervised: Find patterns in unlabeled data ("group these customers by similarity"). Used for customer segmentation, anomaly detection.
Real-World Example: Train ML on 10,000 past conversations labeled "converted" or "didn't convert." Model then predicts conversion likelihood for new conversations in real-time.
Why Machine Learning Matters for BI
ML enables decisions at scale. Manual analysis of 10,000 conversations takes weeks. ML analyzes them in minutes and improves automatically as it processes more data. Organizations using ML-powered insights make decisions 10x faster and with higher accuracy.
How Plura Uses Machine Learning
Plura applies ML across the platform:
Intent Detection: ML identifies buying signals in real-time conversations
Sentiment Analysis: Classifies customer emotions (positive, negative, neutral) from text and tone
Lead Scoring: Predicts conversion likelihood based on conversation patterns
Quality Coaching: Identifies high-performing agent behaviors for team-wide adoption
Common ML Applications in Business
ML drives these business capabilities:
Churn Prediction: Identify at-risk customers before they leave
Lead Scoring: Rank prospects by conversion likelihood
Customer Segmentation: Group customers by behavior, value, or needs
Demand Forecasting: Predict future sales volume or seasonality
Recommendation Engines: Suggest products/services customers will buy