Kustomer Unveils Conversation Intelligence and AI QA, Giving CX Leaders Greater Visibility Into Their Conversations

Kustomer, the AI-native customer experience platform, announced the launch of Conversation Intelligence and AI QA. These two new, native capabilities, built on top of AI Attributes, give customer experience (CX) leaders greater visibility into every customer conversation, moving beyond sample-based analysis to empower data-driven decisions that enhance customer retention, reduce operational costs, and prove CX team impact.

Conversation Intelligence is the type of AI Attribute that evaluates conversations, turning unstructured information into structured data through Classifiers, which sort conversations into labels a business defines; Scores, which evaluate a conversation against a weighted rubric and return a numeric score with a rationale; and Extractors, which pull out or summarize information based on natural-language instructions.

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Brad Birnbaum, CEO & Co-Founder at Kustomer: “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. Conversation Intelligence and AI QA look at every conversation and show their work on every score, so leaders can coach against it and stand behind it. Both are built into the platform our customers already run on, so what we learn goes straight back into the data foundation behind their operations, not into a report nobody has time to read.”

Every CX leader is trying to do three things at once: keep customers longer, spend less doing it, and prove the team’s value to the rest of the business. All three depend on knowing what’s actually happening in customer conversations at scale in time to act on it. Most teams can’t get there because no human can review 100% of the work, so organizations end up managing retention, cost, and their own performance off samples, surveys, and guesswork. By the time any of this surfaces in a report, the moment to fix it has already passed.

Conversation Intelligence and AI QA close that gap by feeding every conversation back into Kustomer’s unified data model. Conversation Intelligence turns every conversation into a structured data point that feeds automated routing and workflows in real time, replacing sample-based guessing with a signal that triggers action on its own. AI QA scores every conversation against criteria the business defines, with adjustable weights and auto-fail logic for anything non-negotiable, and shows the reasoning behind every score so leaders can coach against it and defend it to the business.

With Conversation Intelligence and AI QA CX leaders can:

• Catch risk before it shows up in churn by scoring 100% of conversations instead of the 2-3% that generate a survey response.
• Coach with evidence instead of hunches by reviewing exactly which criteria a conversation hit or missed, and why.
• Fine-tune AI agents faster using the same scoring data applied to human-rep coaching.
• Prove the team’s impact with data, not anecdote by resting every claim on the full picture instead of a sample.

Tom Rosenbaugh, Senior Business Operations Analyst at Turo: “Our agents were categorizing conversations manually, and we knew there was room for human error. When we compare that to what we’re seeing with Conversation Intelligence,, the AI is categorizing conversations more accurately than we were able to with agents alone.”

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Simon Birch, Head of Customer Experience at Loaf: “Conversation Intelligence has given us a much smarter way to understand and route customer conversations. Rather than relying on keywords, it understands the intent behind why a customer is getting in touch, helping us get conversations to the right team more accurately and giving us much better insight into what our customers actually need.”

Conversation Intelligence and AI QA are available now. Both capabilities are introduced alongside Kustomer’s broader “ROI of CX” initiative, including the ROI of CX Report and the upcoming virtual ROI of CX Summit on October 20, 2026, which further explore the business case for data-driven CX investment.

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