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Customer Signal Detection

Classify customer messages into actionable signal types (churn risk, escalation, upsell, bug report, feature request, positive feedback) and recommend next actions. Replaces batch NPS analysis (24h delay) and keyword rules (50% accuracy) with semantic signal detection at 25ms.

Real-time not batch — 25ms detection while the customer is still chatting. Gainsight tells you tomorrow; LFM tells you now

6 signal types — Churn, upsell, escalation, bug, feature request, positive. Not just a sentiment score

No custom ML team — Add new signal types via LEAP in minutes. Not a $500K-1.5M custom ML build

The Problem

Churn signals hide in support tickets. Gainsight detects risk 1-3 days later. Salesforce Einstein: 67% accuracy, daily batch. By the time CSM knows, the customer has churned.

How LFM Compares

Batch analytics detect churn signals a day or more after the conversation. Usage-based tools miss language cues. LFM detects churn, upsell, and escalation in real time at 25ms.

What LFM Unlocks

Real-time signal detection at 25ms in the event stream. Churn, upsell, escalation detected while customer is still chatting.

Analyze Customer Message

This demo is fine-tuned on sample data. Results improve with your data.

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