Bengaluru: Yellow.ai, an AI customer service leader, unveiled Analyze today. This innovative solution enhances bot interactions with deep insights and advanced self-learning capabilities. Using an in-house LLM model, Analyze cuts ticket volume by 30% and increases containment rates by 10%.
Traditional automation platforms lack detailed insights, only covering basic metrics like user numbers. Businesses face a knowledge gap in understanding chatbot interaction quality. A Yellow.ai survey showed 54.5% of customer service experts aim to boost data analysis with AI. They turn to AI-first solutions for comprehensive insights on bot performance, user satisfaction, conversation themes, and areas for improvement.
Yellow.ai’s Analyze meets demand by providing detailed insights and enhancing the bot’s capabilities to handle more customer queries autonomously.
Raghu Ravinutala, CEO & Co-founder of Yellow.ai said, “Customer interactions and contact center data hold immense potential to elevate customer experience, yet many businesses are missing out due to outdated technology. With the launch of Analyze, we aim to meet this market need and help enterprises close gaps in their customer service strategies. Analyze provides comprehensive metrics that enhance containment opportunities and drive more effective automation.”
Analyze accomplishes this through four key features:
- Next-Generation Self-Learning Loopback Technology: Analyze’s self-learning boosts bot automation. When queries go to humans, transcripts improve knowledge base for better future bot interaction.
- Strategic Insights for Topic Clustering: Customer service teams can use an intuitive interface to explore AI-generated topic clusters from bot conversations. They can access insights on customer sentiments, knowledge base improvements, conversation share, and containment rate opportunities.
- Conversation Analysis for Improved Customer Support: It analyzes customer conversations to improve the quality of resolution and customer satisfaction. With Analyze, teams can access granular, conversation-level reports instantly, allowing them to assess details such as, resolution status, containment rate opportunity, conversation share and more.
- Sentiment Analysis for Higher User Satisfaction: Using deep learning, Analyze categorizes conversations as positive, negative, or neutral, offering deeper insights into resolution quality. This analysis, applied to topic clusters, provides more reliable data compared to traditional self-reported feedback.
“Insights into bot and user conversations are crucial for us. Analyze by Yellow.ai has the potential to be transformative with in-depth conversation intelligence. The Self-Learning Loopback using LLMs to study human agent conversations, create KB articles and enhance bot automation, stands out. We are excited to see how this can help drive high quality customer service automation,” said Eric Hansen, Chief Information Officer, Waste Connections.
“This solution evolves with the business, becoming increasingly powerful and adept at meeting customer needs with each interaction,” said Ravinutala. “We believe it represents a breakthrough in customer service analytics, giving businesses a significant edge to maximize their ROI from AI-first automation.”
To book a demo, visit: https://yellow.ai/platform/analyze/
