NICE has unveiled Industry Benchmarks, a solution that allows businesses to compare their service teams’ performance against industry standards.
By launching the solution, NICE leverages its wealth of anonymized contact center conversation data to create benchmarks across 75 verticals.
These benchmarks cover many metrics, including customer satisfaction, handling times, schedule efficiency, complaint levels, and more.
In addition, Industry Benchmarks tracks insights such as agent behaviors, call reasons, coaching levels, sales effectiveness, automation maturity, and more.
As a result, contact centers can uncover how they stack up against the competition while spotting opportunities to differentiate and excel.
Moreover, they may do so “with a click of a button”. Indeed, leaders can extract insights by simply entering written prompts; the large language models (LLMs) NICE leverages will do the rest.
By harnessing LLMs this way, NICE brings another innovative generative AI use case to the contact center table and expands its Enlighten AI suite.
Industry Benchmarks will sit inside the Enlighten Actions module, which includes GenAI-powered tools to help contact center leaders isolate automation opportunities.
There, Barry Cooper, President of the CX Division at NICE, believes it’ll add significant value to NICE CXone users.
“The ability to ensure the highest level of service is key to creating and increasing brand loyalty and to creating differentiating CX,” he said.
The addition of Industry Benchmarks to Enlighten Actions is a significant leap forward and is quickly becoming a must-have for organizations in their constant effort to enhance and optimize their customer experience.
Indeed, the offering will make external benchmarking a much more viable option for contact centers.
After all, the initiative often comes with a warning label: not all contact centers measure metrics in the same way.
A Safer Way for Contact Centers to Benchmarks
Consider first contact resolution (FCR). Some contact centers track repeat contacts; others send post-contact surveys.
Moreover, the timeframe for tracking repeat contacts can swing wildly. Meanwhile, some contact centers will wait longer to send a post-contact survey than others.
As a result, external FCR data is frequently unreliable, which often causes contact center leaders to jump to the wrong conclusions.
That is just one contact center metric. Definitions for other KPIs, such as customer satisfaction, shrinkage, and agent occupancy, are often poles apart.
Even the definitions different vendors put forward with their reporting tools often clash.
Yet, with Industry Benchmarks, contact centers can rest assured that there are no discrepancies in the data. It’s much more trustworthy.
As such, contact centers can confidently use it to support various initiatives, including those that aspire to identify opportunities to apply customer experience AI.
“Brands across all industries are looking for practical ways to apply conversational AI to improve employee performance and bottom-line results,” adds Dan Miller, Lead Analyst at Opus Research.
NICE’s Industry Benchmarks opens up a broad opportunity for executives to harness the power of generative AI and large language models to ensure their customer and employee experiences exceed those of their competition.
NICE Is At the Forefront of Contact Center GenAI Innovation
Industry Benchmarks has become the latest in a series of GenAI announcements from NICE, as the CCaaS Magic Quadrant leader pushes LLM-driven innovation in the space forward.
Notably, the vendor was among the first to innovate with the technology, with the initial launch of Enlighten Actions.
Since, NICE has also released Enlighten Copilot and Enlighten Autopilot. These help to automate mundane contact center agent tasks and increase the scope of conversational AI.
As its innovation cycle accelerates, it’ll be exciting to watch what NICE comes out with next.