Behavioral Signals develops Emotion Cognitive AI technology that analyzes voice data to assess emotional states and predict customer intent. This enables organizations to optimize agent-customer interactions, resulting in measurable improvements such as a 20% increase in agent productivity and enhanced customer satisfaction.
Funding
$13M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Traditional methods of analyzing customer interactions rely on natural language processing (NLP) which primarily focuses on the content of conversations, often missing the crucial emotional context conveyed through tone of voice and behavioral cues. This incomplete understanding limits the ability of organizations to optimize agent performance, predict customer intent, and enhance overall customer satisfaction.
Solution
Behavioral Signals offers an Emotion Cognitive AI platform that analyzes voice data to assess emotional states, understand behavioral cues, and predict customer intent during interactions. By going beyond the literal meaning of words, the technology deciphers how something is being said, providing a deeper understanding of human emotions and intentions. This enables organizations to improve agent-customer matching, optimize call handling, and gain valuable insights into customer behavior. The platform's AI-mediated conversations enhance debt repayment processes, elevate customer experience, and optimize call success rates across various industries, including financial services, utilities, and defense.
Target Audience
The primary target audience includes contact centers, financial institutions, utility companies, defense and intelligence agencies, and any organization seeking to improve customer interactions and gain deeper insights into human behavior through voice analysis.
Features
- Analyzes tonal interactions, including speaking rate, tone variety, speaking time, active listening time, and silence/overlap ratio.
- Detects behavioral cues such as arousal/strength, positivity/emotional valence, politeness, anger/happiness, sadness/frustration, and engagement.
- Provides cross-industry KPIs, including intent prediction, call-level empathy scoring, agent engagement monitoring, duress and stress detection, and mental health monitoring.
- Employs deep AI and multi-task learning to deliver multifaceted behavior predictions.
- Creates detailed customer and agent profiles by capturing and analyzing behavior and emotion metrics from previous interactions.
- Offers a predictive model to strategically match customers with the most compatible agents.
- Provides a user interface designed for data visualization, analysis, user training, and dashboard reports.
- Offers language-agnostic analysis, data security, and multiple secure deployment options (on-premises and cloud).