Built on an in-house LLM model, Analyze reduces ticket volume by 30% and boosts containment rates by 10, the company said
Analyze enhances customer support through four key features
Analyze provides comprehensive metrics that enhance containment opportunities and drive more effective automation: Yellow.ai cofounder
Customer service automation startup yellow.ai
has rolled out a solution to improve bot interactions with in-depth conversational insights and advanced self-learning capabilities.
Built on an in-house LLM model, Analyze reduces ticket volume by 30% and boosts containment rates by 10, the company said in a statement.
Traditional automation platforms provide limited insights, focusing only on basic metrics like user numbers or session times. This gap leaves businesses lacking a comprehensive understanding of chatbot interaction quality.
According to a recent Yellow.ai survey, 54.5% of customer service professionals seek to enhance their data analysis capabilities through AI adoption. They are turning to AI-first solutions to gain comprehensive insights into bot effectiveness, user satisfaction, conversation topics, and opportunities for improvement in bot interactions.
Addressing this demand, Yellow.ai’s Analyze not only delivers detailed insights but also uses this information to continuously improve the bot’s ability to handle a broader range of customer queries without human intervention, the statement added.
“With the launch of Analyze, we aim to help enterprises close gaps in their customer service strategies. Analyze provides comprehensive metrics that enhance containment opportunities and drive more effective automation,” Raghu Ravinutala, CEO & cofounder of Yellow.ai, said.
Analyze enhances customer support through four key features. Its self-learning loopback technology automates and improves bot performance by feeding escalated customer queries back into the system, generating knowledge base articles for future use.
It provides strategic insights for topic clustering, allowing customer service teams to explore AI-generated clusters with insights into customer sentiments, knowledge base improvements, and conversation opportunities.
In addition, conversation analysis offers detailed reports on resolution quality, enabling teams to assess various metrics like containment rate and conversation share instantly. Finally, sentiment analysis uses deep learning to categorise conversations, providing reliable insights into user satisfaction and resolution quality, surpassing traditional feedback methods.
Founded in 2016, Yellow.ai serves 1,100+ enterprises in 85 countries, including Pelago (part of Singapore Airlines), Waste Connections, Sony, Domino’s, Hyundai, Volkswagen, Decathlon, Randstad and the Lulu Group International, among others.
It offers products across 35 channels (text and voice platforms like mobile, social media, messaging, web, voicebots and more) and supports 135 languages. It also claims to automate 16 Bn+ platform conversations annually.
Yellow.ai claims to have achieved 5x rise in global revenue in the past three years and built a team of 650+, Inc42 reported earlier. It claimed $30-40 Mn in annual recurring revenue (ARR) in FY24 (February 1, 2023-January 31, 2024), with India accounting for 30-40% of its business.
The global conversational AI market, widely adopted by enterprises for its efficiency and cost-saving benefits, is growing rapidly, expanding from $10.7 Bn in 2023 to a projected $29.8 Bn by 2028, with a compound annual growth rate (CAGR) of 22.6%.
