Yellow.ai launches Analyze to revolutionise customer service

Yellow.ai, a global leader in AI-first customer service automation, has announced the launch of Analyze, a new in-house LLM-powered solution aimed at addressing the limitations of traditional automation platforms.

According to Yellow.ai, Analyze provides deeper insights into customer-bot conversations, thereby enhancing the bot's ability to handle a wider array of customer queries autonomously. The company reports that Analyze reduces ticket volume by 30% and increases containment rates by 10%.

Traditional automation platforms typically offer only basic insights such as user numbers or session times. Yellow.ai identified a significant gap in the market for more detailed metrics that could provide a comprehensive understanding of chatbot interaction quality. A recent Yellow.ai survey indicated that 54.5% of customer service professionals are seeking to enhance their data analysis capabilities through AI adoption.

"Customer interactions and contact centre data hold immense potential to elevate customer experience, yet many businesses are missing out due to outdated technology," said Raghu Ravinutala, CEO and Co-founder of Yellow.ai. "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 features several key functionalities aimed at improving the customer service experience. One such feature, referred to as Next-Generation Self-Learning Loopback Technology, enables the system to learn and adapt from each customer-agent interaction. The transcripts of these interactions are used to generate knowledge base articles, enriching the company's resources and bolstering the bot's effectiveness in handling similar queries in the future.

Another feature focuses on Strategic Insights for Topic Clustering. This allows customer service teams to explore AI-generated topic clusters from bot conversations through an intuitive interface. Through this feature, teams can access topic-wise insights on customer sentiments, opportunities for knowledge base article improvements, and containment rate opportunities, making it easier to optimise the bot's performance.

Additionally, Analyze offers Conversation Analysis tools designed to help customer service teams improve resolution quality and customer satisfaction. With access to granular, conversation-level reports, teams can assess resolution status, containment rate opportunities, and other relevant metrics instantaneously.

In terms of assessing user sentiment, Analyze employs deep learning techniques to categorise conversations as positive, negative, or neutral. Ravinutala expressed that this function offers significantly more reliable data compared to traditional self-reported feedback, providing businesses with a clearer understanding of their customer service performance.

"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 maximise their ROI from AI-first automation."