Laivly adds AI, ML and automation to improve CX

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It’s a simple – and obvious –  fact: Businesses can’t exist without customers. In no uncertain terms, they are their lifeblood. 

Along with this, companies would be nothing without their first line of defense: Their customer service agents

While this seems like a basic understanding, customer service has suffered in recent years with the advent of chatbots, online messaging and similar automated tools. While seemingly more convenient, these technologies are impersonalized and can lead to more customer frustration – and sometimes even their abandonment of a company or brand altogether. 

But human-centered customer experience (CX) is undergoing a renaissance of sorts – what Jeff Fettes, founder and CEO of Laivly, calls “self-service 3.0.” To survive in this new landscape, organizations must arm their agents with the best possible tools, Fettes said. The company today announced the launch of its artificial intelligence (AI) platform, designed specifically for contact centers. 

“Your frontline team is dealing with your customers; they are the conduit to your customers,” Fettes said. “A good customer experience starts with a good agent experience.”

The new frontier of AI and CX

According to Grand View Research, the global contact center software market will reach $149.58 billion by 2030, registering a CAGR of more than 23%. Likewise, according to Markets and Markets, the global cloud-based contact center market was $17.1 billion in 2022 and is expected to grow to $54.6 billion by 2027. This represents a compound annual growth rate (CAGR) of just over 26%. 

The Markets and Markets report emphasizes, “Incorporating cutting-edge technologies such as AI, ML and analytics enables organizations to connect with their customers for better, efficient, and insightful customer experiences.”

AI is powering this new era of CX, with companies such as Laivly, Zendesk, Genesys and Nice specializing in such tools. Some of the largest players have staked a claim in the growing market, as well, including IBM’s Watson Assistant or Google Cloud’s Contact Center AI, for instance, or similar offerings from Microsoft and Amazon Web Services. 

“The pendulum is finally swinging back from hyper-automation to human-led conversation, but we’ve got some work to do,” said Christina McAllister, senior analyst with Forrester. Organizations are beginning to “embark on a journey” to change the culture of their contact centers. “Service delivered by human agents (not robots) is what drives positive customer outcomes.”

Forrester predicts that companies will continue to leverage and accelerate AI programs, particularly when it comes to agent-facing use cases. As they do so, they must address agent burnout, advocate for agent career development, and transition from cost-centric key performance indicators (KPIs) to customer-centric ones. 

“Gone are the days of bolt-on AI applications,” McAllister wrote. “Forward-thinking companies will infuse AI across the employee workflow, facilitating greater collaboration among humans and their machine counterparts.”

A GPS for the call center 

Laivly’s platform – dubbed SIDD (for systems integrated distributed dashboard) – sits on an agent’s laptop and layers AI, ML and automation onto existing technology. This helps to streamline workflows, analyze customers in real-time and guide agents to the best outcomes, according to Fettes. 

SIDD can draft email and chat responses, recommend and perform agent tasks, and can even block actions to avoid agent mistakes. For instance, disabling a refund button until it recognizes that an agent has worked through the designated workflow sequence. The tool also provides summaries of upcoming calls based on existing customer information and input, and guides them through the process of dealing with that particular case. 

“We liken it to a GPS system for a call center agent,” said Fettes. “SIDD really acts like a person would. It collects information using automation, reacts using automation, and it does it based on what is happening in real time. It is able to interrupt its own workflow intuitively.”

The results, Fettes said, are simplified processes and task performances, consistent customer experiences, reduction in technical loads, and “agents who are able to devote more of their attention to providing empathetic service.” 

“Your AI is watching the screen all the time, providing additional oversight, assistance and support,” he said. 

Adding AI and ML to the tech stack

The company’s tailored orchestration layer ties an agent’s tech stack together without the use of back-end application programming interfaces (APIs), Fettes said, allowing for near-instant integration and the flexibility to change along with business needs. 

Contact center systems typically have “pretty extensive” tech stacks, he pointed out – anywhere from a handful to up to more than a dozen. “We wanted to add AI, ML and/or automation anywhere inside that tech stack,” he said.

Laivly employs human-in-the-loop AI, partnering its automated ML tuners with a team of human tuners. This creates a “unique scenario” and adds “an extra layer of common sense to the tuning,” Fettes said. It also allows companies and agents to gain insights more quickly. 

Fettes described many existing AI and automation customer service tools as “a little more fluffy and nebulous in terms of what they do.” Many of these apply a top-down approach that is dependent on management teams to then take action on collected data. 

“What’s different about Laivly is it’s a bottom-up approach,” Fettes said. “We’re starting right at the agents. Instead of being a management tool, Laivly is a performance tool.”

Self-service 3.0 adds people

The Winnipeg, Manitoba-based Laivly has “quietly built” its contact center technology since its founding in July 2017. This involved careful selection of its initial customers. According to Fettes, these have included top Fortune 500 companies in -commerce, technology and consumer goods. 

Early adopters are already achieving 50% to 300% return on investment (ROI), he said, and are seeing dramatic gains when it comes to agent job longevity and job satisfaction. In a recent survey, 88.5% of agents using Laivly said it was “helpful” or “very helpful” in delivering a better customer experience. Furthermore, 78% of agents said they would be “disappointed” or “very disappointed” if they had to do their jobs without the tool. 

The company is led by a team of data scientists, developers and researchers well versed in customer service. Fettes himself was a contact center agent and manager for more than 20 years, and in fact had his first exposure to the industry as a kid – his mother owned a telephone answering service and he and his brother sometimes helped answer those calls. He most recently cofounded 24-7 Intouch. The global business process outsourcing company partners with brands on contact center strategy, recruiting, IT, HR and workforce planning. 

“Laivly is born of [a] group of people who managed call centers and were agents ourselves,” Fettes said. “I know what I would want to use if I was answering a call or a direct message. We know what (agents) need. We built a tool to be popular with the superuser.”

Such technologies are filling spaces where fully automated tools have often failed, he said, describing an initial “huge rush” to self-service once such tools first became available, then an era of “self-service 2.0” with the arrival of chatbots and messenger platforms. 

Now, technology is “coming together with people again,” Fettes said, “to create this self-service 3.0.”

“This technology is really starting to emerge, and it’s a game changer,” he said. Within the next five to 10 years, companies like Laivly at the forefront will “coalesce into something that’s an industry standard.” 

Ultimately, Fettes predicted: “Every single contact center program, or a vast majority, will be using a tool like this.”

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Taryn Plumb