Join top executives in San Francisco on July 11-12, to hear how leaders are integrating and optimizing AI investments for success. Learn More
Everyone has experienced a negative or unhelpful customer service interaction. And agents themselves are fully aware of the problem. According to a new survey commissioned by software developer Pegasystems, more than half of customer service agents admit to botching how they record customer requests during calls. Due to distractions, nearly 40% also said they regularly fail to understand customer needs.
This is unacceptable, according to Sabrina Atienza, Pegasystems’ director of product management. Now more than ever, customers simply expect quick, context-aware, empathetic responses. “That is no longer seen as going ‘above and beyond,’” Atienza said. “Customer expectations have skyrocketed to the point where exceptional service is now demanded as standard across every interaction.”
Pegasystems (NASDAQ: PEGA) is hoping to streamline and improve the experience — for customers and agents alike — with its two new products, Voice AI and Messaging AI. The Cambridge, Mass.-based company is a leading developer of software for customer relationship management, robotic process automation, and business process management.
Enter the omnichannel contact center
As traditional call centers evolve into omnichannel contact centers, more and more companies are relying on enhanced, detailed performance information provided by real-time analytics, else they overlook significant customer service improvements, according to a report by McKinsey & Company. Leaders in the space include Brightlink, Nice, LiveVox, Talkdesk, Genesys Cloud CX, and Success KPI.
Join us in San Francisco on July 11-12, where top executives will share how they have integrated and optimized AI investments for success and avoided common pitfalls.
The differentiator for Pegasystems’ Voice AI and Messaging AI are their real-time, hands-free functionality, Atienza said. Integrated into the Pega Customer Service platform, they essentially serve as agent “co-pilots” providing support through the use of natural language processing, speech-to-text analytics, and intelligent automation.
Many other voice and messaging analytics products focus on what happened after the fact through transcript analysis, according to Atienza. And often that is a small polling — typically 5-10%.
Pegasystems tools are “really listening to the conversation as it’s happening, detecting intent and kicking off appropriate workflows,” said Atienza. “It’s not just a sampling of the calls, it provides visibility on 100% of the calls.”
Voice AI and Messaging AI populate data from conversations as they are happening, automatically recommend service actions, retrieve relevant information, prompt next steps based on contextual knowledge, and ensure real-time script guidance and compliance. Voice AI also works with existing softphones.
For example, if a customer is calls into a healthcare company, details such as their name, claim ID, date of service and facility where they received care are automatically populated on the agent screen. The system also verifies their identity for HIPAA compliance. And if they’re looking to add a new member to their plan, the system can suggest next steps. Or in financial services, the system can nudge agents when it comes to securing disclosures and can pull up relevant documents on fees and how they are calculated.
Automating tedious, error-prone manual tasks helps to enable faster, more accurate service — improving experiences on both sides of the conversation, Atienza said. Agents are better engaged and not distracted by manual data entry, so they can focus on providing efficient, empathetic service and allow customers to “feel heard, validated, valued.” Average handling times are reduced, resolutions are quicker, compliance is improved, and agents are trained more efficiently.
“We can drive better and faster customer service,” Atienza said. “We can ensure that agents have productive conversations, that customers have productive experiences.”
From custom-service agents to knowledge workers
The need for these types of tools is more critical than ever, as agents are becoming more like knowledge workers, she added. Digital self-service is increasingly being used for basic information gathering, with more complex issues going to agents. They are also navigating more intricate products.
“As demands on customer service teams become increasingly complex and agents feel more burnout, organizations need to empower agents with high-productivity tools to ease some of the burden and enable them to effectively respond to customer needs,” said Atienza.
In a typical customer service interaction, agents juggle reading knowledge papers, following appropriate workflows, and searching databases, all while listening to the caller and identifying their needs. That can be a lot to do in real-time, Atienza said, while also being empathetic and accurate.
Indeed, in the commissioned survey — conducted by research firm Savanta and polling agents from six countries in the Americas, Europe, and Asia-Pacific — 64% of respondents said they become distracted when taking down information. This decreased their ability to be “present” and fully understand customer needs, while also increasing the likelihood of data entry errors. Moreover, 51% said they were confident that they accurately took down customer information when entering it manually.
Respondents pointed to outdated technologies and a lack of training in searching relevant knowledge spaces as hampering their work. And the overwhelming majority said that embracing new technologies would improve their working lives and the overall experience: from having all apps available on one screen, to immediate access to knowledge centers, to not having to constantly switch between applications, copy and paste, or manually enter information.
“It goes back to being distracted,” said Atienza.
Atienza outlines goals
A member of the 2018 class of the Forbes 30 under 30, Atienza began developing a cloud-based service that analyzes voice calls in real-time with Qurious.io. She cofounded the company in 2016, and it was acquired by Pegasystems in 2021. Looking ahead, her goals are to continue to beef up post-call analytics, import emotion into the tools, and further bolster their accuracy.
“How do we capture even more analytics and insight about voice and messaging and use that to provide more targeted suggestions?” she said.
She underscored the importance of companies adopting these new technologies, particularly as social media prevails. “As expectations continue to rise, organizations must prepare themselves by investing in the right solutions to delivering the outcomes their customers not only demand, but also deserve, or risk being left behind,” she said.
“Every service agent is a brand ambassador; one bad interaction can go viral.”
VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact. Discover our Briefings.