Opus Describes a New CRM Software Category

Conversational experience orchestration (CXO), defined by Opus Research as the operating model that unites conversational artificial intelligence, conversational intelligence, and agentic automation, is “the next frontier” in customer experience, according to Ian Jacobs, Opus Research vice president and lead analyst.

“In the quality world of contact centers, we used to live in the land of 2 percent,” Jacobs notes. “A handful of calls per agent per month, chosen at random, and we called it QA. It was closer to QA tourism than QA practice. You parachuted in, took a few snapshots, and left with a vague sense that things were fine.

“Then conversation intelligence vendors showed up promising the opposite extreme, able to analyze 100 percent of your customer interactions. On the surface, that sounds like progress. If a little data is good, surely all the data must be amazing, but that’s not the right framing,” he adds.

Instead, companies today really need analytics running across most or all interactions that automatically surfaces outliers; then humans can spend their limited attention on the strange, the risky, and the brilliant. Full coverage can be helpful, but primarily as machine coverage, not human coverage, according to Jacobs.

Rather than the fragmented approach offered by conversational AI, conversational intelligence, and agentic automation taken as separate items, CXO offers a single, cohesive operating model that combines insight, reasoning, and action, Jacobs explains.

CXO, he adds, entails the following processes:

• Conversational intelligence platforms become the real-time intelligence layer, continuously interpreting conversations and triggering the next right action.
• Conversational AI, copilots, and autonomous agents don’t exist on the side; instead, they are orchestrated as part of coordinated experience.
• Behavior is governed by shared policies, guardrails, and objectives.
• Experience and business metrics, including customer satisfaction, first-contact resolution, revenue per transaction, etc., are live optimization goals. The orchestration layer does not just report on these metrics, it actively steers toward them.

“CXO creates an intelligent layer where agents learn from every interaction, proactively plan next steps, and initiate complex workflows, driving unparalleled customer and business value,” Jacobs says.

CXO relies on a strong conversational intelligence layer to understand intent and context of interactions, then uses agentic AI to plan and act, closing the loop by measuring the impact on real outcomes.

Opus Research also identified the following companies as the top providers of conversational intelligence:

• CallMiner, which provides comprehensive, in-depth voice analytics and omnichannel coverage across diverse customer interaction channels. According to the report, CallMiner’s platform emphasizes strong compliance capabilities, meeting the regulatory and governance requirements of contact centers. The platform’s unified network manages and analyzes performance of human and AI agents.
• Cresta, whose platform focuses on real-time support through an autonomous AI agent architecture that prioritizes enterprise AI scalability, low-latency performance, and deep integration with contact center systems. The company’s unified AI platform and Opera, the company’s workflow engine, enable companies to create and customize AI workflows.
• Invoca, whose platform combines marketing, e-commerce, and contact center intelligence in a unified platform that emphasizes strong closed-loop attribution between conversations and revenue outcomes.
• NiCE, which, through its Cognigy acquisition, gained a technical architecture offering a sophisticated approach to conversational AI through domain-specific CX models based on extensive datasets. Its hybrid methodology balances AI capabilities with deterministic, rules-based controls to ensure reliability and governance.
• SESTEK, whose Knovvu platform uses tightly integrated proprietary automatic speech recognition and acoustic analysis with generative AI, using a multi-agent agentic AI framework. Its technology is designed to orchestrate autonomous AI-driven workflows and human-assisted processes.
• Verint, whose differentiation comes from the substantial scale of its data assets. The company provides breadth through its packaged automation bots and open platform architecture. This breadth enables organizations to deploy prebuilt solutions while also having the flexibility for customization.

“We’ve yet to truly see detailed business calculations and a clear, documented ROI in the use of genAI among customer care organizations,” the report says. “But this small data snapshot provides growing evidence that genAI-powered solutions are transforming how organizations analyze conversations and extract insights, driving both operational improvements and better customer experiences.”