Let’s take a little trip back in time, back to 1750 BC. Even though this was way before Yelp Reviews or Twitter rants, people still had opinions, and they definitely weren’t afraid to voice them.
In fact, during this time, the earliest documented customer complaint was written. A clay tablet from the ancient city of Babylon showed someone named Nanni complaining about a bad deal he got from a trader.
Fast forward to today and we can see that customer service has really changed a lot since then. Now, businesses use AI with machine learning to talk to customers like a real person would. Even though we’re far from those ancient clay “tickets,” keeping customers happy is still a big deal.
Luckily, using call center AI software makes it easy to provide great customer service. Our guide covers the perks, best practices, trends, and tips for using AI tools in call centers.
What is an AI call center?
An AI-powered call center is like your regular customer service center, but with a technological twist. AI call center services make use of artificial intelligence (AI) to help out with customer requests.
This means that AI is integrated into the system to manage a larger number of customer interactions across various communication channels.
Instead of just humans handling all customer inquiries, call center AI technology tackles the routine and mundane stuff like answering basic questions, managing simple tasks, and even helping with more complex customer issues.
Now, these abilities come from some key technologies:
- Large Language Models (LLMs): These are super-smart algorithms that understand and create human-like text, perfect for making chatbots that talk to customers like a real person.
- Natural Language Processing (NLP): This helps computers understand what you’re saying (Yes, even when you’re not making much sense) so AI can answer all sorts of customer questions.
- Natural Language Understanding (NLU): This is a special part of NLP that really “gets” what you mean so the AI can give you spot-on answers.
- Machine Learning (ML): ML lets AI learn from experience and get better over time, making call centers more efficient the more they interact with customers.
- Speech recognition and synthesis: Both of these can convert spoken words to text and back again, making it easy for customers and AI agents to talk to each other seamlessly.
How has AI transformed call centers?
AI has dramatically transformed the way call centers operate, bringing about once unimaginable improvements. And the best part is, we’re probably only just getting started!
Here’s a closer look at how AI has already made its mark on the industry:
From manual to automated call routing
In the old days, getting a call to the right agent often involved a lot of manual work, leading to delays and some pretty annoyed customers. But thanks to AI call center solutions, that’s all in the past.
Nowadays, an AI call center solution can apply technologies like Interactive Voice Response (IVR) and Automatic Call Distribution (ACD) to figure out which agent is best suited to handle each query.
This automation eliminates the need for manual call transfers and significantly reduces both wait time for customers and handle time. Customers are instantly connected to the best agent for their needs, making the experience smoother and more efficient.
Plus, it makes the customers happier because who doesn’t love skipping the hold music?
From human-handled queries to virtual agent-handled queries
Another major shift has been the rise of virtual agents. Remember the AI call center technology we mentioned above? These virtual agents are examples of both conversational AI and generative AI, leveraging NLP and NLU to understand and respond to customer queries in real time, and in a human way.
What does this mean for customers, though? Well, it means instant answers, no more waiting on hold for ages, and a lot less frustration.
These intelligent virtual agents can handle a wide range of questions and tasks, allowing human agents to focus on more complex issues that require a human touch.
From manual quality assurance to AI-powered reviews and speech analytics
Call center quality assurance used to be a labor-intensive process, with supervisors listening to call recordings from start to finish to evaluate agent performance. But AI-driven QA changes the game here as well.
AI-powered speech analytics tools can now analyze call recordings and transcripts from customer service calls with your customers in a fraction of the time, automatically assessing whether the agent met the criteria on the QA scorecard.
What’s even better is that AI can do this for all of an agent’s calls, not just a random sample. So, no more inaccurate reviews because a supervisor happened to pick a particularly rough call to assess.
AI ensures a more accurate and fair evaluation process so every agent gets the feedback they deserve, and true actionable insights into how they can improve.
AI for a call center: How can AI be used in your call center?
So, you get the gist of what AI-based call centers are all about and how they’ve totally transformed the way we communicate with customers.
But now you’re probably wondering, “how can I actually use AI in my call center?”. Let’s get into the nuts and bolts of how you can leverage AI in call center operations.
1. Improve call routing
Not too long ago, skills-based routing systems were the new thing, matching customer calls with agents who had the right skills to help them out.
But now, AI and automation have kicked that up a notch, making it way faster and smarter to figure out which agent should handle a call.
Today’s contact center software uses intelligent call-routing systems with self-learning algorithms. These algorithms analyze everything from customer personality types (Yep, AI can guess if someone’s a “chatty Cathy” or a “straight-to-the-point Steve.”) and past call history to behavioral data.
Based on all that info, the system decides the best way to handle calls. Those simple requests can go straight to bots or directed to self-service resources. However, if the issue is more complex and needs a human touch, the system will route the call to a live agent.
In those cases, AI makes sure the call goes to the agent best suited to handle that specific customer or query. This means issues get resolved faster, tickets get closed more efficiently, and everyone’s time is freed up.
The best part is that the more the system is used, the better it gets at making those perfect matches. Over time, this means you’ll be able to respond to customers even more effectively and keep improving their overall experience.
2. See call analytics instantly
Every customer interaction is packed with useful data, and with the power of AI in contact centers, it’s easier than ever to tap into that wealth of information.
One way to do this is through live customer sentiment analysis. It can give you extremely important insights into how your customers feel about your brand, service, or products just by analyzing the words they use.
Say you’ve carried out 60 customer service calls one morning. With AI, you don’t have to sift through each call manually. Instead, AI can instantly scan all those interactions and highlight patterns.
Maybe it detects that a lot of customers are using words like “frustrated” or “confused” about a particular issue. It’ll then flag those calls for further review so you know exactly where to focus your attention.
If AI identifies that several customers had negative feelings about a recent product update, you’ll get a complete summary showing these trends and the specific issues raised.
This data-driven approach allows you to address the problem promptly, improving the customer experience, boosting customer satisfaction, and potentially saving you from more complaints down the line.
3. Understand your customers better
AI can really help you understand your customers and make your interactions with them more effective.
The first way it can do this is by spotting trends in customer behavior that might not be obvious at first. For example, AI may discover that more customers are calling about a particular issue (like to tell you that their account has been locked), it can alert you early on so you can start preparing for it.
This early insight helps call centers predict what customers might need in the future and come up with new best practices to handle those needs.
But that’s not all.
AI can also gather detailed information about each customer and their behavior and then share it with all your agents. This means your customer service team can see useful details about each person they’re talking to (We’re talking about their past interactions and preferences).
With this kind of info, agents can get a better sense of what customers might need or want. For example, if an agent knows a customer has shown interest in certain products before, they might suggest related items or services.
It’s all about tailoring the conversation to fit the customer’s needs and interests, making every interaction more relevant and personal.
4. Help agents with real-time tips
How do you handle an increase in the volume of customer interactions? Well, while AI might not come up with the perfect answer for every situation, it can definitely help agents respond better in lots of different scenarios.
For example, AI tools can give live feedback during a call and even search for answers in real time.
RingCentral RingCX has an AI Assist feature for precisely this purpose. It constantly evaluates and contributes to live calls, pulling from existing content to give accurate responses, instantly.
This is super handy for new agents or those who are still getting up to speed. They can get quick suggestions and answers without having to guess or scramble for information.
Plus, AI can help make sure conversations follow your company’s standards. It can alert managers if a call starts going off track and might need some extra attention or follow-up.
Over time, this helps improve call quality and agent efficiency, fine-tune your best practices, and cut down on customer frustration and churn.
5. Make self-service and call reflection easier
AI might not be able to do everything a human agent can, but it’s great for handling simple requests.
You can let AI take care of routine tasks of contact center operations like placing an order, checking a balance, or paying a bill. This way, your human agents can focus on more complex issues.
AI can also handle bigger self-service tasks, but accurate data is needed to do this well. If the information AI has is incomplete, it won’t be able to manage more complicated interactions effectively.
So, making sure you have good data and analytics is really important if you want AI to handle more tasks and provide more self-service options.
Types of AI call center software to implement in 2024
Here are some of the best call center AI solutions that we highly recommend you look out for in 2024 and beyond:
Intelligent Virtual Agents or Assistants (IVAs)
AI virtual agents and assistants are getting smarter all the time. They learn from past customer interactions and get better at helping out. These virtual assistants work alongside human agents in real time.
They can give feedback on conversations and dig up info from knowledge bases or CRMs, helping agents tackle tricky questions. This lets human agents focus more on the conversation and connect with customers better.
Now, just like your favorite customer service agents, before they’re ready to help, these chatbots and virtual assistants go through a lot of training. They study a lot of data from past conversations, emails, and calls.
This training helps them understand what customers need and provide quick, helpful responses.
Fortunately, it’s easy and intuitive to configure an IVA with RingCX. You can deploy it in minutes, with the help of a visual drag-and-drop interface and pre-built templates.
Predictive analytics tools
We all like to be prepared. Have a heads up. Know what’s coming. Why? Because it helps us get ready and handle things better. Think about it. Knowing in advance how something might go gives us the chance to plan our responses and avoid any surprises.
That’s exactly what predictive analytics do for AI customer service. They give you a peek into what customers might need or want before they even ask for it.
These tools pull together all sorts of data (like past interactions, financial details, relevant metrics, and customer preferences) to make predictions. For example, if a customer has called multiple times about billing issues, the system can flag this and predict that they might need help again soon.
By piecing together this info, predictive analytics can forecast what customers might do next. This lets your agents get a head start on what might come up during a call.
So, if the tool suggests a customer might be interested in a new service based on their past activity, the agent can be ready to bring it up during the conversation.
Companies that use predictive analytics often see a real boost—sometimes up to 20% more—in customer retention. That’s because staying ahead of customers’ needs and fixing issues before they become big problems helps keep customers happy and coming back.
Speech analytics
Ever feel like you’re drowning in call recordings, trying to figure out if agents are doing a good job? As a manager, you probably spend hours sifting through these calls to assess performance. It’s time-consuming and often feels like searching for a needle in a haystack.
Speech analytics tools listen to every call and assess whether agents are meeting quality standards. Instead of manually picking and reviewing random calls, the system provides a comprehensive analysis of all interactions.
What’s particularly useful is that these tools use NLP to convert long conversations into clear, concise summaries. This means supervisors can quickly understand the key points of each call without having to listen to every second of it. Think of it as getting the important Cliff notes that only have the essential information.
For instance, if an agent consistently struggles with handling complaints, the system will flag these issues and provide their opinion on what went wrong. It’s a practical way to improve call quality and agent performance while saving you a lot of time and effort.
Automated customer feedback analysis
42% of customer service agents who use AI tools say these systems for analyzing customer feedback seriously improve the customer experience. That’s a big deal, so let’s take a look at why that would be.
When AI tools gather all the feedback you get and dig through it for you, you no longer have to manually wade through endless comments.
For example, imagine you’re getting a lot of people giving you feedback about how long it’s taking to get support.
Instead of reading through every comment, AI tools can spot this pattern right away. They sort the feedback into categories like “complaints,” “praises,” or “suggestions” so you can quickly understand what’s hot and what’s not.
This helps you catch issues before they become big problems. If customers keep mentioning that your website is hard to navigate, you’ll see it immediately and be able to take action to fix it.
It also means you can highlight what people love about your service, like fast response times or friendly support so you can keep doing more of the same thing.
What impact does AI in call centers have on CX?
AI is shaking things up in call centers, and it’s changing the way customers experience service.
It’s making the customer journey both faster and more personal, but what does this really mean for how people feel about your service?
Let’s take a closer look at how AI affects customer experience—both the good stuff and any bumps along the way.
Benefits of using AI in a call center
By this point in our guide, you probably have a pretty good sense of what AI can do in a call center. But what’s in it for you and your team?
Let’s talk about some of the perks of using call and contact center AI:
Faster responses
AI helps you keep up with the speed of today’s customer demands. Customers want quick replies.
AI can handle the simple stuff almost instantly so customers get answers right away. This lets your team tackle the more complicated questions and keeps everyone happy.
24/7 customer support
AI doesn’t need to sleep or take coffee breaks. It’s always on, so it can help customers anytime, day or night. This is great for people in different time zones or those who need help outside regular hours.
Plus, it lets businesses handle tons of customer questions without dropping the ball on operational efficiency, quality, or speed.
Optimized support costs
Using AI can cut down on the size of your support team because AI can handle a lot of questions at once. It can answer similar questions and FAQs, help customers navigate your website or app, and update records for both new and existing customers.
This means you save money on staffing while still keeping up with high service standards. Plus, it cuts down on human mistakes, making it a smart choice for keeping support costs down.
Improved agent productivity
Customer service agents juggle a lot of different questions daily, which can be pretty overwhelming. AI can help by summarizing chats and emails so agents don’t have to re-read everything, tweaking messages to match the brand’s style, grouping similar tickets together to spot patterns, and suggesting the next best steps to take.
Plus, there’s even more it can do! Basically, it helps agents stay organized and work more smoothly.
Less agent burnout
A recent study published in Forbes shows that a lot of call center workers are feeling pretty burned out. It’s no surprise—handling endless repetitive tasks can really wear you down.
AI steps in to take care of the boring stuff, which eases the load and helps keep your team from getting too stressed out. Happier agents mean superior service for everyone.
Challenges of using AI in a call center
Even though it can do a lot of amazing things for call centers, implementing AI isn’t all sunshine and rainbows. There are some bumps along the road when integrating AI into your customer service operations.
It’s important to be aware of these challenges so you can tackle them head-on and make the most of what AI has to offer:
Data privacy concerns
AI handles a lot of customer data, so keeping that info safe is super important. There’s always a chance of data breaches, so you need to make sure you have strong security measures in place.
Quality of AI responses
Sometimes, AI can get confused with complex questions or tricky language. This might lead to answers that aren’t quite right or leave customers frustrated.
Dependency on quality of data
Now, AI works best with clean and complete data. If your data is all over the place, it might not perform as well, which can mess up your results.
Real-life examples of AI being used in call centers
Example #1: MedCare
MedCare Equipment Company supplies medical gear like wheelchairs and glucose monitors in Western Pennsylvania. They used to struggle with their old phone system, which was always breaking down and was generally hard to manage. Making changes or adding new features took forever.
Switching to RingCentral was a big win for MedCare. Their average call wait times dropped by 40%. With RingCentral, they could set up call queues and get new numbers in under an hour. Plus, their phone menus became more user-friendly, making it easier for customers to get help quickly.
MedCare also started using RingSense for Sales, which uses AI to review and summarize calls. This saved managers 92% of the time they used to spend on call reviews. They went from spending 25 minutes to just two minutes to review a call. This made coaching agents a lot faster and more effective.
Example #2: InsuranceHub
InsuranceHub, a major insurance provider, needed better tools for managing sales conversations and customer interactions. Their old system didn’t cut it, especially after merging with the Leavitt Group.
When InsuranceHub switched to RingCentral and RingSense for Sales, they saw a big change. RingSense helped them to transform their approach to managing customer interactions.
They stated that the stand-out feature was that the system enabled managers to actively listen to their teams’ customer conversations, and they used the coaching tab as a way to gauge performance.
RingSense’s keyword search feature allowed managers to quickly find and review specific types of calls. This streamlined their sales training and quality control. Overall, RingCentral and RingSense helped InsuranceHub improve their sales efficiency, customer service, and data management.
Best practices for using AI in a call center
Adding AI to your call center doesn’t have to be daunting. You can either go with an AI service provider that handles everything for a monthly fee or set it up yourself.
Here are some top tips to make it easier:
Know what you want
Start by figuring out what you want to achieve with AI. Are you looking to make customers happier, cut costs, or help your agents with more efficient workflows? Make sure your AI goals match your business needs.
Try before you buy
Use free trials or take demos of AI software to see if it fits with what you’re doing. Test out the features and see how well it works with your current setup before committing.
Train your team
Not everyone on your team is going to be aware of how to use these AI call center solutions. Make sure your agents get proper training on how any new AI tools work. Let them know AI isn’t here to replace them but to make their jobs easier. It helps everyone get on board with the change.
Keep data safe
Follow privacy rules and put strong security measures in place to protect customer data. AI will be handling a lot of it, so keeping it safe is crucial.
Check and improve
Keep an eye on how well your AI is performing. Gather feedback and make tweaks as needed. Regular updates and adjustments will help keep everything running smoothly and effectively.
What does the future hold for AI in call centers?
As we look into the future of AI and call centers, several amazing trends are set to change how businesses connect with customers.
Here’s what to keep an eye on:
Advanced natural language processing
NLP is getting a major upgrade. It’s not just about understanding words anymore. Future AI will get better at picking up on the emotions and deeper meanings behind what customers say.
This means your AI will be able to handle conversations in a more human-like and empathetic way, making for superior interactions.
Mixing AI with other tech
AI isn’t working alone. It’s teaming up with other tech like blockchain for secure transactions, IoT for improved data collection, and AR/VR for cool, immersive customer support.
Imagine using these tools together to give your customers an even better experience and more insights into their needs.
Focus on ethics and privacy
With AI becoming more common, keeping things ethical and respecting privacy will be a big deal. Call centers will need to use AI wisely, making sure they’re protecting customer data and being transparent about how it’s used.
AI with emotional intelligence
AI is learning to get emotional. Soon, it’ll be able to pick up on the mood and feelings in a customer’s voice or words. This means AI can adjust its responses to match the emotional tone of the conversation, making interactions feel more personal and understanding.
Real-time language translation
As businesses go global, real-time language translation will continue to develop and become more readily available. AI will break down language barriers, letting call centers provide seamless support to customers no matter what language they speak.
Boosting your CX couldn’t be simpler with the help of AI
So, there you have it. Our complete guide on how AI is transforming call centers everywhere.
AI is here to make everything smoother and more efficient for both agents and customers. It handles repetitive tasks, provides quick insights, and helps improve every customer interaction.
With AI, you can:
- Automate routine tasks
- Enhance agent productivity
- Reduce agent stress
- Make smarter decisions
- And more!
If this sounds good to you, check out RingCX. It’s powered by AI and can streamline your contact center operations.
Plus, with brilliant features like sentiment analysis, integrated note-taking, and post-call highlights, it’s a game changer for making your workday easier and your customer interactions stellar.
FAQs about AI in call centers
What is AI used for in call centers?
AI in contact centers helps with a variety of use cases, such as answering common questions, routing calls to the right agents, and even providing 24/7 support. It can also analyze customer interactions to help agents perform better.
Will AI replace human call center agents?
No way! AI isn’t here to replace human agents. Instead, it’s a tool to make their jobs easier. Research shows that AI helps grow careers and is expected to create 97 million new jobs by 2025. In call centers, AI takes over repetitive tasks so agents can focus on more meaningful work.
How is customer experience improved by using AI in call centers?
AI makes customer experience better by speeding up responses and offering help to callers around the clock. It personalizes interactions by remembering past behavior and preferences, making customers feel valued. Plus, it supports agents with useful info and suggestions so they can handle issues more efficiently.
Originally published Aug 30, 2024
