Conversation Intelligence Improves Outcomes for Contact Centers, Observe.AI Research Shows

By | Managed Services News

Jun 29

However, two-thirds of contact centers still rely on manual processes for critical workflows like agent coaching and quality assurance.

Intelligent workforce platform Observe.AI has unveiled its latest research that says conversation intelligence leads to better financial and employee outcomes for contact centers.

That said, as consumer expectations and technology investments continue to rise, customer experience and business outcomes fail to improve. The findings highlight the contact center industry’s continuing struggle with the customer experience paradox. Despite increased technology budgets and spending, many contact center leaders feel unprepared to succeed and that their agents are underperforming.

In State of Contact Center Conversation Intelligence 2022, the report details the current landscape of conversation intelligence – software that uses AI to analyze speech or text to derive data-driven insights – in contact centers. Observe.AI commissioned Zogby Analytics to survey 307 North American contact center leaders across industries.

Contact centers adopting conversation intelligence report higher agent-customer interaction visibility that drives more robust coaching programs, majority top-performing agents and greater confidence about the future of their business.

Observe.AI's Swapnil Jain

Observe.AI’s Swapnil Jain

Swapnil Jain is CEO and co-founder of Observe.AI.

“There’s no longer a debate on whether conversation intelligence is worth the investment. Adoption is no longer a question of if, but when,” Jain said. “Whether a contact center’s focus is on service, sales, or both, visibility into agent-customer interactions is key to accelerating workflows that drive revenue and growth.”

The above slideshow reveals the key takeaways from the report, including the current landscape of conversation intelligence in contact centers. This includes technology investments, business needs and challenges, use cases, future planning and outlook.

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