Artificial Intelligence (AI) in the contact center is growing at a rapid rate. End-user spending, which was on track to reach nearly $2 billion in 2022, is expected to more than double by 2026. By that time, Gartner predicts that 10% of agent interactions will be automated – nearly 10 times as many are today.
This growth is already bringing transformational benefits to many customer service organizations looking for savings, added efficiency, and support against unpredictable demand. But it has also created confusion for others as the market becomes filled with more noise and greater saturation. Whether you’re an early adopter of Contact Center Automation – the leading customer service application of AI – or a leader just digging into your options, chances are you’ve run into one or more of these common misconceptions:
- Automation, IVRs, and chatbots are all the same
- Automation is more expensive than it is beneficial
- Customers don’t want to talk to a machine
- Automation can’t resolve customer issues
- Customer-facing bots hurt CSAT
- Automation aims to replace agents
Despite the confusion, however, thousands of customer experience innovators are already reaping the benefits of Contact Center Automation. But for those still gathering information for their own organizations’ automation plans, a clear understanding of the solution is imperative.
Read on for 10 of the most common misconceptions about Contact Center Automation as well as the data and firsthand accounts that have proven them false.
Misconception #1: No one wants to talk to a machine
Fact: Nearly 80% of consumers would converse with a machine to avoid long hold times.
Rigid IVRs and keyword-driven chatbots have conditioned many contact center leaders to think customers have lost faith in machines altogether. But Contact Center Automation is neither an IVR nor a chatbot. And the results speak for themselves. Customers are often surprised by the capabilities of conversational AI, the engine that powers automated conversations.
Contact Center Automation allows customers to speak naturally, ask multiple questions at once, and be understood in scenarios where legacy technologies fail. This includes seamless conversations even when there’s background noise, multiple languages, and unique accents or dialects present. “You solved my problem and that’s all that I cared about,” is a common response to Thinking Machine. Additionally, a recent customer survey found that nearly 80% of consumers would rather speak to a machine than wait on hold, and 44% of people report being annoyed, irritated or angry with a 5-15 minute wait time.
Misconception #2: Automation can’t resolve customer issues
Fact: Replicant’s Thinking Machine achieves a 90% first call resolution without agent escalation.
Unlike traditional automation solutions that aim to deflect or reroute customers to self-service channels, Contact Center Automation is all about resolution. Replicant’s Thinking Machine has automated millions of conversations to achieve a 90% first call resolution rate without agent escalation. This is driven in part by Natural Language Understanding trained specifically for customer service scenarios, as well as expertly designed conversations that focus on pushing conversations toward resolution, not searching for ways to send customers to a webpage or app. Automation can connect with platforms like CRMs, scheduling systems, and even partner platforms to offer end-to-end resolutions for call drivers like appointments, orders and returns, dispatching, and much more.
Misconception #3: Customer-facing bots hurt CSAT
“For us, the value of automation has gone far beyond containment. It’s about actually improving the customer experience and cost savings. It’s so much more than we could have imagined.” – Rob Dunning, Operations Leader at The General
It’s no secret that faster resolutions and eliminated hold times increase customer satisfaction. But with Contact Center Automation, improved satisfaction comes to life in many more ways. Error rates in automated conversations are flattened, handle times are cut in half, omnichannel experiences are made easy, and agents are more available to focus on complex issues. Customers who need a quick resolution to a request like a medical appointment or a flat tire are able to get instant service without waiting for an agent. Meanwhile, those with complex or urgent requests can be connected with an agent faster, without having to wait in the same queue as a customer with a simple account question.
Misconception #4: Deploying automation is too risky
Fact: 91% of contact center leaders report that Contact Center Automation is a critical or important priority in the next year.
Many organizations believe that automation comes with inherent risks. These perceived risks may be monetary, time or resource-related, or the simple risk of deprioritizing other projects. But when you zoom out, it’s clear that the risk of not beginning to automate, even in an initial testbed project, is far greater. According to the 2022 Benchmark Report, almost all contact center leaders (91%) report that Contact Center Automation is a critical or important priority in the next year. 80% are planning or evaluating automation and intend to invest in it within the next 12 months. Given the fact that automation can be deployed in weeks, combined with the knowledge that your competitors have likely already started, it’s easy to see why prioritizing automation is not only strategic for most, but imperative.
Misconception #5: Building a solution yourself is cheaper
“Implementing conversational AI requires expensive professional resources in areas such as data analytics, knowledge graphs and natural language understanding” – Gartner
While it may be tempting to go at an automation project alone, the “build” approach can get off the rails quickly. “Implementing conversational AI requires expensive professional resources in areas such as data analytics, knowledge graphs and natural language understanding,” says Gartner. “Once built, the conversational AI capabilities must be continuously supported, updated and maintained, resulting in additional costs.” Many contact centers who attempt to build automation from scratch end up committing magnitudes more time, money and resources than they anticipated to the project. Even in these cases, it’s not uncommon for an in-house automation project to never reach deployment and set digital transformation roadmaps back years.