Modern Customer Experience Requires AI, CX Connect Speakers Stress
Despite all the praises that have been heaped upon them for their handling of the COVID-19 pandemic, "contact centers are still failing," the CEO of Replicant AI warned attendees at the opening day of CX Connect, a three-day virtual conference sponsored by the producers of the SpeechTEK, CRM Evolution, and Smart Customer Service conferences.
"Contact centers have not changed much in 30 or 40 years," said Gadi Shamia, co-founder and CEO of Replicant, during his keynote to kick off the first day of the online event. "The business processes have not really changed."
Contact centers, he said, still struggle to balance agents, technology, and processes while keeping costs low.
"It's crazy," Shamia said, noting that automation touched everything from how we deposit checks to the factory floor, "but in the contact center, it's still run like we're in the 1980s. There has been very little automation."
Contact centers, Shamia added, still rely very heavily on humans. Interactive voice response systems can take callers to the right agent, but the agent still does most of the work, and then, when the call is completed, the agent has to do post-call wrap-up work. "That's not much different than it was 30 years ago," he stated.
And that is having adverse effects on agent attrition, customers who are forced to wait on hold, and companies that are spending a lot of money and not getting the results they want, according to Shamia.
"What contact centers are missing most is elasticity," Shamia said, which he defined as the ability to dynamically change staffing as needs change. "We've created elasticity everywhere else, but not in the contact center," he said.
Shamia noted that artificial intelligence is a largely under-used technology advance that has great potential in the contact center. It's being used for routing, agent coaching, and getting information, but not in a way that can really change contact centers in a big way. "It's hard to get people excited about a marginal, 5 percent improvement," he said.
To be truly game-changing, AI must deliver the following, according to Meghna Suresh, head of product at Replicant.
- Resolution of tier 1 cases;
- 24/7 support;
- Scalable customer service elasticity; and
- Go-live in weeks, not months.
AI has great potential, Suresh argued, pointing to natural language processing as one of the biggest advances in technology in years.
AI can fully resolve many issues today, she said, pointing out that AI today can handle longer and more complicated interactions.
But, companies need to invest in technologies that can capture error cases and reprogram themselves to deal with them, she said, adding that companies also need to invest in prebuilt conversational components, improve conversational performance, and get deeper insights into every conversation with improved analytics.
Benjamin Gleitzman, co-founder and chief technology officer of Replicant, sees the need for AI in even simpler terms. "There are so many possibilities today with voice AI. You can leverage AI for better and faster conversations with customers," he said.
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Equally important is sentiment analysis, which Andy Bird, vice president of products at Concentrix, highlighted as a key differentiator during the second presentation of the day.
Sentiment analysis, he said, is the bridge between empathy and optimization.
"Empathy and automation are not diametrically opposed. You can do both," he added, "because you can have an agent who is influenced by AI."
The need for contact center AI was further demonstrated during an afternoon roundtable discussion. During that session. Gary Williams, director of sales and consultancy for U.K. and international markets at Spitch, said that with the volume of data collected by contact centers, AI becomes a real necessity. Contact centers today need to analyze and make sense of call recordings, saved text chats, saved social media interactions, and so much more, and then be able to search, filter, and report on that data, Williams said, and that can only be done with AI.
Still, companies are not doing that at scale, according to Terry Kocon, product marketing manager at Calabrio. The keys to outstanding customer experiences are hidden in the contact center, she said, but the average contact center only analyzes about 2 percent of its interactions, mostly for quality assurance purposes.
AI lets contact centers do so much more. "With AI, contact centers can take predictive and prescriptive actions," she said.
AI can also be used for sentiment analysis, according to Kocon. "As contact center leaders, we need to ask if we are delighting customers, and emotion and sentiment analytics gets us that information," she said.
AI can also be used in the contact center for staffing when tied to workforce optimization applications, according to Kocon. AI lets contact center leaders anticipate call volume and optimize service levels, she said.
Once compiled, organized, and analyzed with AI, contact center data has tremendous value to the entire organization, not just the contact center, Kocon maintained. Contact center data can really benefit finance, customer experience, and marketing teams, she said.
Derek Roberti, vice president of technology at Cognigy, said AI also lets contact centers act "at scale."
"A good customer experience depends on conversation automation," he said. Without it, contact centers are challenged to deliver consistent experiences at scale.
The only way to carry on conversations at scale with customers across channels and devices at scale is with conversation automation, Roberti said.
And then, contact centers need a single view of the customer, according to Shekar Hariharan, vice president of marketing at Jitterbit.
This is not easy, though, because companies today are still working with so many disconnected business applications, data silos, processes, and workflows, he said.
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