New AI capabilities analyze every customer conversation to help CX teams identify risks, improve agent performance and connect customer experience initiatives to business outcomes

Kustomer, an AI-native customer experience platform, has launched Conversation Intelligence and AI QA, two capabilities designed to help customer experience (CX) leaders analyze customer interactions at scale. Built on the company’s AI Attributes technology, the tools aim to move organizations beyond sample-based reviews and provide actionable insights into customer needs, service quality and operational performance.

Conversation Intelligence converts unstructured conversations into structured data using three functions: Classifiers, which assign conversations to business-defined categories; Scores, which evaluate interactions against weighted criteria and provide a numerical result with supporting rationale; and Extractors, which retrieve or summarize information based on natural-language instructions.

The capabilities are intended to help organizations make more informed decisions about customer retention, operational costs and team performance by analyzing conversations that might otherwise go unreviewed.

Moving Beyond Sample-Based Analysis

Many CX teams rely on customer surveys and limited conversation reviews to assess service quality and identify recurring issues. Kustomer says this approach can leave organizations without a comprehensive view of customer interactions, making it harder to identify emerging risks and respond quickly.

Conversation Intelligence feeds structured information from customer interactions into Kustomer’s unified data model, enabling organizations to use those insights in automated routing and workflows. Rather than relying solely on keyword matching, the system is designed to identify customer intent and direct conversations to the appropriate teams.

“Most CX teams are making six-figure staffing and strategy calls off the two or three percent of customers who answer a survey. The rest goes unmeasured,” said Brad Birnbaum, CEO and co-founder of Kustomer. He said the new capabilities analyze every conversation and provide reasoning behind scores, allowing teams to use the findings for coaching and operational decisions.

AI-Powered Quality Assurance and Coaching

AI QA evaluates conversations against criteria defined by each business. Teams can configure weighted scoring rubrics and establish automatic failure rules for requirements that must always be met. The system also provides explanations for individual scores, helping managers identify where interactions meet expectations and where improvement is needed.

Kustomer said the combination of Conversation Intelligence and AI QA can help CX teams identify potential churn risks earlier, support evidence-based agent coaching, improve AI agent performance and demonstrate the business impact of customer service operations.

The same scoring data can also be used to assess AI agents, giving organizations a consistent framework for evaluating human and automated interactions.

Customer Feedback Highlights Automation Benefits

Early customer experiences cited by Kustomer point to potential improvements in conversation categorization and routing.

Tom Rosenbaugh, senior business operations analyst at Turo, said the company had previously relied on agents to categorize conversations manually, leaving room for human error. He said Kustomer’s Conversation Intelligence was categorizing interactions more accurately than the previous agent-only process.

Simon Birch, head of customer experience at Loaf, said the technology had improved the company’s ability to understand and route customer conversations by identifying intent rather than relying on keywords. He added that the insights provide a clearer picture of customer needs.

Availability and Broader CX Initiative

Conversation Intelligence and AI QA are available now. Their launch is part of Kustomer’s broader “ROI of CX” initiative, which includes an ROI of CX report and a virtual ROI of CX Summit scheduled for October 20, 2026.

The initiative focuses on the business case for data-driven customer experience investment, as organizations seek stronger ways to connect service operations with customer retention, efficiency and measurable business results.