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The Future of Contact Centers Lies in AI and Agent Collaboration

Contact centers are seen as a cost center and a source of frustration for both companies and customers. Although companies have used BPOs to reduce their cost of running a contact center, they haven’t solved the fundamental problems. Instead, “We just reduced the cost and moved it farther away and made it someone else’s problem — in this case, the BPO,” said Gadi Shamia, CEO and cofounder of Replicant, during a town hall about the future of contact centers.

In order for contact centers to thrive, organizations need to solve these underlying problems. How can contact centers and customer service leaders do this? The answer lies in AI and the introduction of an autonomous contact center.


Watch the recording above for a preview of the full town hall discussion on the future of contact centers.

Three Fundamental Problems of Contact Centers

Despite outsourcing and attempts at automation, contact centers have historically faced three major problems that still persist today.

Difficulty in accurately forecasting supply and demand

Even with workforce management software, it’s difficult for contact centers to accurately predict call volumes and always have the perfect number of agents on staff to meet demand. Contact centers end up with either too many or too few agents, which leads to higher costs or long hold times and poor customer experiences.

High turnover rates

The problem above is exacerbated by the fact that agents don’t stay at contact centers for very long. Call centers see an average of 30% to 45% turnover rate. Some even have turnover rates in the three digits. Turnover is so high because most agents prefer less mundane work. When agents are fielding repetitive Tier-1 calls, it can lead to burnout.

Poor customer experience

The more repetitive the tasks, the more difficult it is for agents to stay focused and engaged. While they’re working, they may also be checking social media or texting a friend. As a result, their quality of work and the customer’s experience suffers.

With AI, a New Contact Center Model Can Emerge

To solve these problems, companies are looking to AI to help automate repetitive, task-oriented aspects of their customer service. However, not all efforts have succeeded. In fact, most automation efforts have failed to deliver on their promise or have frustrated customers. Phone, in particular, has been difficult to automate because it requires AI to process the context of a customer’s call, accurately understand the request, and respond back quickly.

Companies that have tried to develop voice AI in-house are rarely able to put the technology into production or process thousands of calls with the AI. Companies that don’t build a custom solution have turned to IVRs. Because IVRs use either primitive AI models or phonetic recognition, IVRs require customers to learn their language. Customers have to say numbers, specific phrases, or keywords that the IVR recognizes. When IVRs fail to contain the problem, customers get passed onto an agent and have to repeat their issue. This leads to greater frustration.

Autonomous contact centers provide a more effective way of leveraging AI technology for customer service. Using the power of voice AI, they act as the first line of defense by resolving Tier-1 customer service issues, without burdening agents with repetitive, high-volume calls or keeping customers on hold.

They also provide customers with multi-experience, omnichannel support across voice, SMS, mobile, and other channels. When the AI can’t resolve an issue, it’s escalated to an agent and a summary of the interaction is shared with the agent. Customers don’t have to repeat themselves, and the agent can jump straight into solving the problem.

How Autonomous Contact Centers Solve the Three Fundamental Problems

Using a combination of AI, visual IVR, and seamless integrations with existing contact center software, an autonomous contact center can solve the three fundamental problems that contact centers currently suffer from.

Tier-1 issues are immediately resolved

Machines are great at performing tasks that have a defined beginning and end. For example, looking up the status of a delivery, updating an order, or finding the nearest store location based on the customer’s address. By fully resolving and not deflecting these types of issues, an autonomous contact center takes away tedious tasks from agents. In turn, agents are freed up to handle the emotionally sensitive or complex problems and to build relationships with customers.

Elastic customer service that automatically scales with demand

An autonomous contact center can answer as many phone calls as needed — no matter how much call volume you get. “The system is elastic, which means if you send 10 calls an hour, 100 calls an hour, 1,000 calls an hour, we don’t care. We’ll take as many calls. There’s never going to be a hold time,” said Shamia. When supply shrinks and stretches with demand, you no longer have to worry about having enough agents at all times and spikes in demand are flattened.

Increased customer satisfaction

Customers don’t care whether a human or AI helps them, as long as they don’t have to wait on hold, their issue is resolved as quickly as possible, and they don’t have to repeat themselves when transferred to an agent. Autonomous contact centers increase CSAT by meeting these expectations. Every call is immediately answered by the AI, and calls are quicker and more efficient. When speaking with a machine, there’s no chit-chat. Customers also don’t have to wait while agents are manually entering information or navigating between multiple systems. By plugging into CRMs and contact center software, the AI technology instantly finds and updates information. It also automatically generates summary notes for deeper call insights and less manual data entry on behalf of agents.

Where an Autonomous Contact Center Fits Into Your Tech Stack

Since IVRs are used widely, most people immediately understand an autonomous contact center through the lens of an IVR. However, autonomous contact centers are different from IVRs and have a lot more capabilities. An autonomous contact center can either fit in front of or behind an IVR. It can even replace an IVR.

When an autonomous contact center is in front of an IVR, it’s the first interaction that customers have. The easy issues are automatically resolved without any agent interaction, while the more complex issues are handed off to an agent. When the autonomous contact center sits behind the IVR, it will interact with customers after they have chosen a menu option.

You don’t need to rip and replace existing technology, since an autonomous contact center works alongside your IVR and other systems.

How to Get Started With Autonomous Contact Centers

Identify a use-case for automation

The easiest way to get started with an autonomous contact center is to identify a single use-case where it can be applied. Find a simple and repetitive call driver that could be resolved by a machine. Then, figure out how much volume of that use-case you have, the current cost of having agents handle that issue, and the ROI of automating it.

Determine which systems need to be integrated

You also need to identify the systems that need to be plugged into the autonomous contact center. For companies that are built on a modern system architecture, the AI can easily plug into your systems through APIs. However, companies that are built on older systems may need to first upgrade their infrastructure before they can implement an autonomous contact center.

Ensure your data is up-to-date and accurate

The success of your autonomous contact center depends on the quality of your data. To autonomously solve Tier-1 issues, the contact center technology needs to pull information from other systems and update them. If you have outdated knowledge bases or CRMs, the AI will draw from this bad information. Before you implement this type of technology, make sure your data is up-to-date and accurate.

Implement one use-case to realize business value

Even if your systems and data aren’t in an ideal state, you can still start transforming your contact center into an autonomous one. When choosing your first use-case, find one that’s isolated and touches few systems. “Because if you can reduce 10% of the pressure off the call volume, it doesn’t matter where you reduce it from,” explained Shamia.
Automating even a small percentage of your calls positively impacts your operations and customer experience. You shouldn’t hold off on implementing an autonomous contact center just because you can’t automate all of your call volume immediately. “The full potential might be realized in five years. But the initial potential, we can realize now,” said Shamia.

Bring an Autonomous Contact Center to Your Organization

You can reduce call center costs, increase CSAT, and scale customer service elastically with Replicant, the world’s first autonomous contact center. Replicant brings always-on, elastic capacity to every customer experience with voice AI.

Replicant Voice resolves Tier-1 support issues over the phone, using natural and human-like contextual voice AI. It eliminates hold times, manages unpredictable call volume, and gives agents more time to resolve emotionally-sensitive and complex issues. Unlike many AI solutions, Replicant Voice can be implemented in just a few weeks or months. It’s also been deployed by Fortune 500 companies to resolve over three million calls a month and reduce contact center costs by 50%.

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