Getting Digital Transformation Right Through AI & Analytics
Digital transformation projects and opportunities are now top-of-mind for enterprise call centres. Expedient support and resolution options that meet customers in their preferred channel are soon to become the norm, not the exception. The critical link between customer satisfaction during “these unprecedented times” and the ability to expedite first contact resolution can be the difference between a good and bad (or at least uncomfortable) earnings call or NPS survey result.
The surge of contact centre communication over the course of this pandemic is unlike anything the industry has ever seen, or is likely to see again. To make matters worse, many enterprises or “brands” had only scratched the surface of their digital transformation projects focusing on more efficient call deflection and offering omnichannel self-service options.
Day after day, the pandemic floodwaters continued to rise while many organisations were left unprepared with the tooling equivalent of some mops and buckets.
As part of a recent three-part webinar series, Opus Research joined experts from Verint to explore how AI and Analytics are empowering organisations during this acceleration of digital transformation initiatives. “An organisation should be striving toward an enterprise approach to self-service…we’re not talking about applications anymore, we’re talking about building centres of excellence,” said Tracy Malingo, Global VP & GM, Intelligent Self-Service at Verint.
Have you thanked your contact centre employees recently?
As contact centre costs continue to raise eyebrows in the C-suite, automation and performance analysis is critical. For organisations with standalone customer support solutions, that analysis often remains a manual, time-consuming effort, including conversation reviews, metrics dashboard exports merged into excel pivot tables, etc. Rarely is this analysis performed in partnership with contact centre agents, the actual subject matter experts who reside in the contact centre. Does this sound familiar?
It’s a familiar cycle of looking backwards in order to determine the next step forward. By the time you’ve determined your next conversational support strategy, new and organic, real-time changes to your products or services—or the weather, or the arrival of a pandemic—are impacting your contact centre in brand new ways. All these processes benefit from AI-driven solutions to automatically identify customer needs and enable employee actions.
“The reality is, AI needs to be embedded in self-service, but it also needs to be embedded in human service,” said Verint’s Daniel Ziv, VP, Global Product Strategy, Speech and Text Analytics, as part of the Verint-Opus Research webinar series.
Offerings for real-time customer insights and automation are maturing in the Conversational AI market and available regardless of the sophistication of an organisation’s current support offering. A common strategy of simply forwarding a text blob of a chatbot conversation to an agent as part of a chat escalation strategy, for example, is human-error prone and not scalable for long-term success.
Organisations are consistently underestimating the value of conversations they have with their customers.
Leveraging AI and machine learning for analysis, classification, and labelling of a company’s conversational data can go a long way in improving automated self-service and building competitive advantage.
Measure a lot, resolve once
There are numerous real-time conversation measurements or “tells” that can help improve the client and agent experience and remove friction in support of first-contact resolution. In-conversation analytics solutions such as Verint’s Agent Assist serve as co-pilots to intervene mid-conversation and provide additional support suggestions to the agent by leveraging transcript context (i.e., “linguistic triggers”), acoustic elements (e.g., long holds, emotional responses), user details (e.g., membership status), and relevant product offers.
These insight-based actions and opportunities tie directly back to an organisation’s containment and KPI goals. Real-time analysis and multi-turn conversational pivots are what customers will soon come to expect. And it’s a powerful tool that can measurably reduce the strain on contact centre resources.
Despite the evolution and sophistication of digital-first, self-service applications, no one is predicting an end to human-to-human support in the contact centre. Verint’s Real-Time Agent Assist shows the promise of using predictive, contextualised interactions to expedite resolutions when human assistance is critical. Enabling real-time context and analytics empowers agents with greater insight into resolution paths and more credibility with the connected customer. That credibility can improve the customer experience and allow agents to become more opportunistic.
Hear more from the Opus Research team in our on-demand three-part webinar series as they discuss with other Verint team experts “How to Empower Transformation with AI & Analytics.”
Leave a ReplyWant to join the discussion?
Feel free to contribute!