Leveraging Artificial Intelligence (AI) in your contact center can help you solve even the most challenging customer experience problems.
And with customers having higher service level expectations than ever, deploying AI solutions into your existing contact center systems is vital for business success.
In this guide, we’ll explore the benefits of implementing AI in contact centers and how you can utilize its capabilities to reach your contact center goals.
What Is Contact Center Artificial Intelligence?
Contact Center AI is the use of Artificial Intelligence (AI) and Machine Learning (ML) in contact centers to increase agent efficiency and boost customer satisfaction throughout all stages of the customer journey.
Some common use cases for AI in the contact center industry include routine task automation, real-time language translation, customer interaction analysis, real-time quality assurance, and agent assistance and coaching.
Contact Center AI can enhance agent performance, provide a more personalized customer support experience, and make customers happier.
What Can Contact Center AI Do?
Contact center AI solutions are capable of automating and simplifying a wide range of contact center operations and tasks. Here’s what a contact center AI tool can do:
Anticipate Customer Needs
Figuring out what your customer needs and identifying intent before they even interact with your contact center is one of the areas where you can improve customer experience with AI.
For example, if an e-commerce store experiences extended downtime, and they decide to reach out to their hosting provider for support on a weekend when the company usually expects the highest sales volume, the AI judges the call to be urgent even before it’s answered.
The AI puts that company’s query at the top of the queue and routes it to the most suitable agent with an Automatic Call Distribution (ACD) system so that they can get support quickly.
As the company’s representative explains the issue to the human agent on the phone, an AI-enabled virtual agent is simultaneously listening to the call and pulling out key terms with Natural Language Processing (NLP) to quickly identify the possible causes of downtime and even propose solutions.
All of this happens before the customer fully explains the problem, which also contributes to a lower Average Handling Time (AHT).
In contact centers, lots of tasks don’t always require a human agent. Contact center AI can easily handle any routine customer requests efficiently without involving a human agent.
One example is when a banking customer wants to deactivate their credit card if they suspect it’s stolen. The AI simply verifies the customer’s phone number and uses a voice print analysis for additional identity verification to process the request.
Benefits of Artificial Intelligence in the Contact Center
There are many perks of integrating AI into your contact center. These include:
Faster Customer Handling
With AI, handling large volumes of customer queries can be more efficient, resulting in a reduced Customer Handling Time (CHT).
And because customers expect their problem gets solved as quickly as possible, this will make them more satisfied with their service delivery experience. Plus, by being able to handle more customers in less time, you won’t have to unnecessarily scale your team to cope with demand.
AI enables cost savings in many areas and operations of a contact center. For example, using AI to provide self-service channels for your customers, such as AI chatbots, can help you significantly cut labor costs.
On top of that, your customers will be able to have their problems solved quickly with no human interaction, saving you the cost of lost customers that can’t afford to wait for a human agent to answer the phone after waiting on hold and being forced to go through the Interactive Voice Response (IVR) system.
Analyzing Big Data
Call centers collect a huge amount of data on their customers and how they interact with their businesses. For major businesses that handle hundreds or thousands of customers per day, putting the collected data to use seems impossible.
With AI, you can analyze and manage big data more efficiently, providing you with useful insights that can influence your decisions and improve the performance of your contact center.
Adapting to Unexpected Scenarios
Adaptability is one of the biggest challenges of modern contact centers. Leveraging AI and machine learning will help your customer service center:
- Spot service gaps quickly
- Predict demand based on data analysis
- Guide contact center agents with useful insights and information based on changing customer behaviors and situations in real-time
- Prioritize tasks based on importance and prevent agent burnout
Enhanced Self-service of Common Requests and Questions
According to recent research by Harvard Business Review, at least 81% of customers prefer to take care of simple problems or technical difficulties by themselves before chatting with live agents. Still, many customers don’t like “talking to a robot”, but with advancements in AI, you can create smart and efficient self-service channels without frustrating them.
Modern AI self-service solutions utilize machine learning and analyze large amounts of data to proactively find ways to meet customers’ needs and effectively respond to common questions.
As a result, the customer won’t feel like they’re talking to a brainless machine, ensuring that the use of technology enhances the overall customer experience instead of deteriorating it.
By personalizing the interactions and making the customer feel like they’re chatting with a human being, contact center AI helps you maximize operational efficiency without damaging your relationship with your customers.
Contact Center Analytics
Customers expect to be able to reach support on any channel the organization has a presence on, such as social media platforms. This has made it harder to consistently collect and analyze customer interaction data, especially with their increasing volumes.
Contact center AI enables you to define and automate KPI tracking, helping you deliver the best possible customer experience.
With Contact Center AI, you’ll be able to gain a single pane of glass visibility on analytics dashboards that continuously monitor performance in real-time, allowing you to identify areas of improvement in the quality, workforce, and efficiency compartments.
Real-Time Customer Insights
For contact centers, creating the best customer experience can be achieved by simplifying customer interactions and making the conversations friendly.
This can be achieved by training your agents, but it won’t give you the results you seek no matter how hard you try.
With contact center AI solutions, you’ll be able to utilize data-driven solutions that take into consideration your customer’s non-verbal cues, mutual history, tone of voice, and other factors that could influence the direction of the conversation.
Instead of counting 100% on your agent to gather information about the customer, leveraging AI software provides real-time customer insights to the agent to help them make the conversation natural, friendly, and memorable.
Real-Time Sentiment Analysis
Sentiment analysis is the usage of NLP to identify whether a particular set of data is positive, negative, or neutral. Customer sentiment analysis is crucial for you to capture the way customers interact with your contact center and determine their satisfaction.
Contact center AI makes it easier for you to tell whether an individual call or interaction is going well or not, helping you uncover performance issues and determine which agents need more guidance or training.
This can drastically reduce customer churn rate and result in happier and more loyal customers.
Real-Time Guidance and Coaching
Contact Center AI enables you to advance your agent soft skills coaching and qualify them to handle even the most challenging customer interactions with real-time guidance and coaching.
By providing your agents with real-time workflows and information, such as product/service details, sentiment, and demographics, you give them more time to handle the customer interactions that may require more attention. Plus, they’ll be able to automate redundant tasks and provide a truly personalized experience for each customer.
Real-Time Quality Assurance
AI-powered real-time QA automatically scores all calls, allowing you to identify problems quickly and efficiently and spread awareness about them before they turn into habits.
AI automatically collects scores from all calls and suggests possible reasons for the low scores, such as insufficient knowledge from the agent. This can help you target your coaching and enhance the quality of your customer interactions.
You can also see the scores for individual agents of particular groups of agents in a matter of seconds. In addition, you can effortlessly disaggregate the scores into categories, like compliance, call handling, professional, etc.
AI-powered QA also makes it easier for you to track performance and evaluate whether your coaching efforts and corrective actions are helping drive better performance and higher call quality.
Contact center AI systems allow agents to focus on resolving customer issues while the whole note-taking process is done automatically with AI.
AI software programs use sentiment analysis and Natural Language Processing (NLP) to automatically determine the key parts of the conversation that should be noted for after-call processing and handling.
The Contact Center as a Service (CCaaS) Evolution
Contact Center as a Service (CCaaS) is a deployment model that helps organizations reduce costs by only paying for the tech they need. CCaaS solutions can either be deployed on-premises or in the cloud depending on the company’s requirements and resources.
For many contact centers, launching new support channels or features can be time-consuming and costly. That’s where CCaaS solutions come in; they allow businesses to launch new features without the footprint.
They also enable them to provide more comprehensive omnichannel support for their customers.
Some of the advantages of CCaaS include scalability, flexibility, predictable monthly billing, and fast time to market.
Utilizing CCaaS can help you optimize your CX with the following capabilities:
- Chat and email support
- Call management and routing
- Agent routing
- Workforce automation
- Advanced virtual agents and chatbots
- Intelligent IVR systems
- Assistance automation
- Proactive customer updates and alerts
Will AI Replace Human Call Center Agents?
At the moment of writing this article, the possibility of AI fully replacing human agents is highly unlikely.
Even though we already have advanced AI chatbots, customers are still very likely to seek support from a human agent if the AI agent couldn’t help them with their problem.
In its current and near-future form, the implementation of AI in contact centers focuses on empowering agents to handle customers more efficiently, automate redundant tasks, prioritize tasks, help them with real-time guidance and suggestions, and reduce after-call work.
For instance, if your agent spends a lot of time taking care of post-call work, AI can help them get it done faster with things like automatic note-taking.
Make Your Customers Happier by Using the Balto.ai Real-Time Guidance Platform
Is your contact center struggling in the performance and customer satisfaction compartments?
Balto helps you drive better results and boost sales using Real-Time Guidance and Coaching for empowering agents, and Real-Time QA for automatic call scoring.
Our AI-enabled solution helps you retain your customers and keep them satisfied by making their interactions with your business faster and less frustrating. Access insightful analytics about customer interactions and develop data-driven solutions to improve efficiency. Boost agent productivity by letting your agents focus on more important jobs while Balto handles tedious tasks with its powerful AI capabilities.
For more about our services, check out our free definitive guide here. We’re also happy to offer you a free demo of the Balto platform so you can discover how it works in real-time.