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During the pandemic, enterprises turned to automation to scale up their operations while freeing customer service reps to handle increasingly challenging workloads. According to Canam Research, 78% of contact centers in the U.S. now intend to deploy AI in the next 3 years. And research from The Harris Poll indicates that 46% of customer interactions are already automated, with the number expected to reach 59% by 2023.
During a session at VentureBeat’s Transform 2021 conference, Salesforce SVP Marco Casalaina, BNP Paribas Group’s Adri Purkayastha, and Five9 EVP of products Callan Schebella discussed the growing role of automation in the call center. The panel touched on how AI assistants can coexist with humans and help them to perform their jobs, while at the same time respecting existing customer service guardrails.
“We’re talking about a spectrum of technologies,” Schebella said of automation broadly. “On the one end, … we’ve got call technology that completely automates one side of the conversation … And then, you’ve got [other forms of automation], from enhancing a conversation through feedback to the agent in real time to a knowledge base that shows information to an agent to make them more capable.”
According to Casalaina, who heads Salesforce’s Einstein machine learning division, adoption cuts across industries including governments and legacy brands in the midst of digital transformations. For example, last year, the New Mexico Department of Workforce Solutions launched a chatbot — Olivia — to answer questions related to standard unemployment as well as pandemic unemployment assistance. Casalaina says that within a week, Olivia had almost 100,000 interactions.
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Chatbot usage exploded during the pandemic as organizations looked to bridge gaps in customer service and onboarding. In 2020, the chatbot market was valued at $17.17 billion, and it is projected to reach $102.29 billion by 2026, according to Mordor Intelligence. There was also a 67% increase in chatbot usage between 2018 and 2020. And Gartner predicts that by 2022, 70% of customer interactions will involve emerging technologies such as chatbots — an increase of 15% from 2018.
“It was definitely a crazy year for us, because we saw the types of customers we have really changing [in terms of customer interactions],” Casalaina said. “[Many deployed] chatbots to deflect a lot of the queries that they frankly didn’t have enough people on staff to be able to handle.”
Schebella noted that the benefits of cross-channel automation can be myriad, offering reduced wait times, personalization, technical support, and faster resolution of customer complaints. He gave the example of TruConnect, a virtual network operator and a Five9 customer, which uses AI to automatically summarize agent-customer conversations while making them available for annotation.
“Just being able to do something like that — summarization — [can] reduce the post-call handle time and post-interaction time by 30 seconds, a minute, or more,” Schebella said. “When you scale that across many hundreds of agents, it adds up … pretty quickly.”
Challenges and looking ahead
Purkayastha says that technological improvements over the past five years have set the stage for the wider adoption of automation in the call center. Superior automatic speech recognition and transcription are accelerating the velocity of deploying solutions, while knowledge graphs — knowledge bases with graph-structured data models — are extracting information pertinent to support agents. Beyond this, automation technologies now better understand the semantics of conversations and continuously learn, optimizing toward business KPIs.
Of course, these systems require data to train, and accumulating the data — along with processing, normalizing, and cleaning it — can take time. Schebella says that it’s not unusual for 30, 60, or 90 days to elapse before a natural language processing model begins to perform satisfactorily. In the future, he expects data collection to become less of a problem as call automation technologies provide more real-time feedback — for example, indicating to a customer service agent whether they’re speaking too quickly or slowly.
Organizations that don’t adopt automation run the risk of alienating customers. According to a Vonage survey, 61% of respondents believe interactive voice response (IVR) menus of call center options create a poor experience. It’s estimated that each customer lost due to frustration with an IVR system costs businesses an average of $262 every year.
On the other hand, companies leading in customer service are adopting new models for work and reimagining their mix of service channels, according to Deloitte. A recent survey from the firm found that customer experience remains the most important strategic focus for service leaders — a focus that’s only expected to increase over the next two years. For example, while only 32% of surveyed organizations were running contact center technologies in cloud by the end of 2022, 75% expect to make the move by 2024.
“An area that’s of interest to myself is this concept of personal virtual agents that understand people at the consumer level,” Schebella said. “[In the future,] these agents could have the type of information that’s representing me, even at work, understanding things like my calendar. That’s an [fascinating] space.”
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