Enghouse’s AI-based Voice of the Customer technology has enjoyed great success as the agent’s secret augmentation, offering real-time coaching and information while they deal with customers.
Now, the new SmartQuality analytics platform extends the functionality to offer greatly enhanced call centre quality management, by automating key aspects of the agent evaluation process. Supporting call centre supervisors and agents at the same time by offering objective scoring across all multi-channel interactions, including voice, email and web-chat, it enables supervisors to focus directly on key coaching opportunities, as well as helping businesses to improve the identification of key customer insights.
The agent evaluation programme aggregates interaction data to enable comprehensive analysis of every conversation, on every channel - supporting business intelligence and direction at the macro perspective, as well as individual agent development.
At the one-to-one end, it means that agents can be evaluated fairly, on the totality of their work, and coached and supported appropriately. As product director Steve Nattress explained, this intelligent system can spot and flag liabilities at varying levels, from compliance breaches to account at risk:
“We [Enghouse] are not dictating what makes a good call - the client configures SmartQuality according to their own criteria and policies, to mirror and scale their evaluation process and scorecard - but without the human bias and noise, and addressing 100% of the interaction across all channels,” he explained.
“It helps the human supervisor identify specific coachable moments, to address individually, in a completely fair way.”
From Individual Improvement to Data-Driven Trend Identification
As well as supporting the skills development of each agent, the intelligence of the system can glean additional insights from the language and shape of each call, and recommend follow-up actions - looking at the data from a much larger perspective, and zeroing in on trends emerging.
“One of the key differentiators is the risk detection module in our AI engine,” Nattress continued. “This can identify churn risk in a call, where the customer is indicating an intent to take their business elsewhere.”
Because of the human nuances of language, this may not be explicitly threatened or stated during the call - but the sheer volume of voice-of-customer data the AI is ingesting means that pattern recognition is possible, and the interaction can be flagged.