The 2022 Guide to Contact Center AI
Call centers date back to the 1960s, when UK-based Birmingham Press and Mail installed the first customer service telephone line. Today, contact centers are an integral part of most businesses, handling customer inquiries, sales, and support.
While the technology and processes have changed over the years, the basic goal of the contact center remains the same: to provide quality customer service. To do this, contact centers rely on customer service representatives (CSRs) who are trained to handle customer calls.
With the advent of artificial intelligence (AI), contact centers can augment strategic goals, processes, and workflows to improve customer satisfaction, and automate more repetitive tasks. In this article, we'll explore how AI is changing the contact center landscape and what it means for businesses and CSRs.
The basics of contact center AI
At its core, AI is a process of programming computers to perform tasks that would otherwise require human intelligence, such as decision making and pattern recognition. In the context of the contact center, AI can be used to automate customer service tasks, such as handling routine inquiries, or providing recommendations based on past customer behavior.
Some of the most common AI applications in the contact center include chatbots, virtual customer assistants, and intelligent call routing.
Chatbots are computer programs that simulate human conversation. They can be used to handle simple inquiries, such as providing information about a product or service. You've likely used a chatbot yourself, without even realizing it, when you've interacted with an automated customer service agent online.
Virtual customer assistants (VCAs) are similar to chatbots, but they are more sophisticated and can handle more complex tasks. VCAs use natural language processing (NLP) to understand human conversation and respond accordingly. They can also be integrated with other business systems, such as CRM platforms, to provide a more holistic view of the customer.
One of the most well-known VCAs is Amazon's Alexa. Amazon's Echo line of products are powered by Alexa, which allows users to perform tasks such as checking the weather, setting alarms, and adding items to their shopping list.
Intelligent call routing is a contact center AI application that uses caller data, such as location and past interaction history, to route calls to the most appropriate agent. This can help save time for both customers and CSRs by ensuring that calls are routed to the right person the first time.
What is the difference between contact center AI and call center AI?
Telecommunications leader Verizon handles around 800 million wireless calls a day during the week. While this may seem like an enormous volume of interactions, call volume pales in comparison to the 293 billion emails sent each day.
Call centers were once the backbone of customer service, as phone calls were the primary way that customers interacted with businesses. But in the age of email, chat, and social media, call centers are no longer the only way to provide customer service.
Instead, a holistic customer service strategy today must revolve around a contact center, and not just a call center. A contact center is a centralized hub that provides customer service and support via multiple channels, including phone, email, chat, and social media.
The COVID-19 pandemic helped spur the transition from call centers to contact centers, as businesses quickly realized that they needed to be able to support their customers on multiple channels in order to meet their needs.
One of the challenges of a contact center is that it requires significant human resources to staff all of the different channels. This is where AI can help. AI-powered chatbots and virtual customer assistants can provide 24/7 support on multiple channels, freeing up human agents to handle more complex issues.
AI can also help contact centers improve their efficiency and effectiveness. By analyzing customer interactions, AI can help businesses identify issues and trends, and provide recommendations on how to resolve them.
AI is not usually a total replacement for human agents, but it is a powerful tool that can complement and enhance their work. As businesses continue to move from call centers to contact centers, AI will become an increasingly important part of the customer service landscape.
Understanding the contact center AI market
While many businesses have suffered tremendously at the hands of the COVID-19 pandemic, geopolitical upheaval, and market volatility, the contact center AI market has actually been experiencing quite a bit of growth.
In fact, according to Allied Market Research, the global call center AI market was valued at $959 million in 2020 and is projected to reach $9.9B by 2030, registering a CAGR of 26.3%. In other words, the field is expected to grow from around $1 billion to $10 billion this decade.
In contrast, the broader IT services market is only expected to grow at a compound annual growth rate of 7.04%, according to Statista. This means that the contact center AI market is growing almost four times as fast as the broader IT services market.
This tremendous growth represents a unique opportunity for businesses of all sizes to enter the market and capitalize on this trend. However, it is also important to understand the landscape of the market in order to make the most informed decisions.
The contact center AI market can be segmented by product, application, deployment, end-use industry, and geography.
- Product: Offering types include solutions and services. Solutions can be further classified into interactive voice response (IVR), automatic call distribution (ACD), computer telephony integration (CTI), workforce optimization (WFO), customer relationship management (CRM), and knowledge management (KM). Services are categorized into professional services, managed services, and support & maintenance services.
- Application: The applications include call routing, quality management & monitoring, fraud detection & prevention, customer engagement & experience management, text analytics, sales acceleration & lead management, performance management & reporting, workforce management (WFM), and others (includes desktop analytics, chatbots, and text-to-speech).
- Deployment: On-premises and cloud are the typical deployment modes.
- End Use: Verticals include BFSI, healthcare, retail & ecommerce, telecom & IT, manufacturing, energy & utilities, media & entertainment, travel & hospitality, and others (including government & defense and education).
- Geography: North America (NA), Europe (EU), and Asia Pacific (APAC) are key regions seeing growth.
As the contact center AI market continues to grow at an incredible pace, it is important for businesses to stay up-to-date on the latest trends and developments. Those who do so will be best positioned to capitalize on this game-changing technology.
What is driving this growth? Businesses are realizing that they need to modernize their contact centers in order to keep up with the competition and meet the needs of their customers. The old model of customer service--a human agent on the phone taking care of customer inquiries--is no longer enough. Customers now expect a more personalized, efficient, and convenient experience, and they are increasingly turning to chatbots and other AI-powered solutions to get it.
Of course, this is not to say that human agents are going away completely. In fact, most businesses are using a hybrid approach, with both human and artificial agents working together to provide the best possible service. However, as AI technology continues to evolve and become more sophisticated, it is expected that the role of human agents will diminish over time.
So what does this mean for businesses? If you're running a contact center, it's time to start thinking about how you can incorporate AI into your operation. Not only will this help you keep up with the competition, but it will also allow you to offer your customers the kind of modern experience they now expect.
Key Contact Center AI Players
Businesses seeking to implement or enhance their contact center AI should consider the following key players:
- Commerce.AI
- Amazon Connect
- Google Contact Centre AI
Each of these platforms has distinct advantages that can benefit businesses of all sizes.
Commerce.AI
Commerce.AI's data platform has scanned over 1 billion products and services across 56,000 categories, allowing businesses to glean insights about customer behavior and trends. The platform is available on Genesys AppFoundry, which gives businesses access to a broad range of customer experience solutions.
Genesys AppFoundry is the largest marketplace focused on CX solutions, and it allows businesses to deploy solutions quickly and easily. Commerce.AI supports over 100 data integrations, both inside and outside of organizations. This makes it easy for businesses to unify their data sources and get insights across all stages of the customer experience - from consumer to customer to client.
Further, Commerce.AI's speech-based voice survey capability provides real-time feedback and deep insights at scale. This can help businesses deliver an exceptional customer experience.
Commerce.AI is used by leading brands like Coca Cola, Unilever, Suzuki, and Cisco.
Amazon Connect
Amazon Connect is Amazon's omni-channel contact center environment, which is designed to support a flexible and ever-changing business landscape. Amazon Connect makes it easy to set up and manage a contact center.
Built-in machine learning capabilities allow businesses to automate customer interactions, understand customer sentiment, authenticate callers, and route calls to the best-suited agent. Amazon Connect also offers analytics so businesses can monitor contact center performance and make improvements accordingly.
Google Contact Centre AI
Google Contact Centre AI is a contact center enhancement that builds on the benefits of your existing contact center. It uses Google's cutting-edge machine learning technology to automate customer interactions and deliver insights in real time.
10 Benefits of Contact Center AI
There’s no question that artificial intelligence is rapidly transforming the customer experience landscape. Indeed, AI is expected to add up to $15.7 trillion to global GDP by 2030, according to PwC research.
As such, it’s no wonder that an increasing number of businesses are turning to AI to power their operations. But what exactly are the benefits of contact center AI? Here are the top 10.
1. Product and Service Innovation
In many industries, customer expectations are constantly changing and evolving. To stay ahead of the competition, companies must continuously innovate their products and services. However, innovation can be a challenge, particularly when it comes to understanding what customers want and need.
This is where contact center AI can play a critical role. By analyzing interaction data (including feature requests, complaints, trends, competitive mentions, and more), contact center AI can provide valuable insights that can help organizations make more informed decisions about product and service innovation.
For example, suppose a company is considering adding a new feature to its product. Using contact center AI, the company could analyze past customer interactions to identify any patterns or trends related to that proposed feature. This analysis could reveal whether there is customer demand for the proposed feature, what potential obstacles there might be to its successful implementation, and so on.
In addition to helping organizations make better decisions about product and service innovation, contact center AI can also improve the quality of those innovations by ensuring that they are more closely aligned with customer needs and expectations. In other words, by using contact center AI to “listen” to customers on a regular basis, companies can ensure that their innovation efforts are better targeted and more likely to succeed.
2. Improved Customer Satisfaction
Customer churn has been called the "silent killer" of SaaS businesses, as it costs up to 25 times more to acquire a new customer than it does to retain an existing one. And since customer service plays a critical role in the customer lifecycle, it’s crucial that contact centers be as efficient and effective as possible.
Enter AI. By automating repetitive tasks and surfacing insights that agents may not have otherwise had access to, AI can help contact centers improve customer satisfaction scores. Further, customers won't have to wait nearly as long to speak to an agent, since AI can handle a large volume of low-level inquiries.
A poor contact center becomes a cost center, and can even turn customers into "detractors." But with AI-powered contact centers, businesses can take a major step towards becoming a customer experience powerhouse, turning customers into "promoters."
3. Increased Agent Productivity
It’s no secret that contact center agents have one of the most demanding jobs in customer service. They’re constantly balancing multiple tasks and responsibilities, and are expected to provide an exceptional experience to every customer, every time.
This is where AI can help. By taking on some of the more repetitive or simple tasks (such as data entry or account lookup), AI can free up agents to focus on more complex issues. Additionally, AI-powered chatbots can handle low-level inquiries 24/7, meaning agents won't have to field these types of calls outside of normal business hours.
This not only increases agent productivity, but also reduces agent burnout and turnover. In fact, a study by the APA found that American workers are now more stressed than ever before. By using AI to lighten the load on agents, businesses can help improve both employee satisfaction and retention.
4. Reduced Costs
Contact centers are notoriously expensive to run. They require a significant investment in both people and technology, and the costs only increase as businesses scale.
Fortunately, AI can help businesses reduce these costs in a number of ways. First, as mentioned above, AI can help increase agent productivity, which can lead to fewer agents being needed overall. Additionally, AI-powered chatbots can handle an increasing volume of customer inquiries without the need for additional human support. And finally, since AI never takes vacation or sick days, businesses can avoid the costly downtime that comes with traditional contact center operations.
In short, by using AI to power their contact centers, businesses can achieve major cost savings without sacrificing quality or service levels.
5. Improved Self-Service
More and more customers are now expecting businesses to offer some form of self-service option (such as a chatbot or online FAQ). This is particularly true for millennials, who have been found to prefer self-service over speaking to an agent.
With AI-powered chatbots, businesses can offer 24/7 self-service that is both efficient and effective. Chatbots can quickly handle simple customer inquiries, freeing up agents to focus on more complex issues. And since chatbots never get tired or take breaks, they can provide a consistently excellent customer experience at all times.
6. Increased Sales and ROI
In addition to the direct cost savings that AI can provide, businesses can also expect to see an increase in sales and ROI. This is due to the fact that AI-powered contact centers are able to provide a much higher level of service than traditional call centers.
Customers today expect more than just efficient problem solving from their contact center experiences. They also want a personal touch, and they want to feel like they’re part of a human relationship. Thanks to advances in natural language processing and machine learning, AI-powered chatbots are now able to replicate these human interactions, leading to more satisfied customers and more sales.
7. Ability to Rapidly Scale Operations
As businesses grow, so too do their contact center needs. This can be a major challenge for traditional call centers, which often have difficulty meeting the increased demand without incurring significant costs.
AI-powered contact centers, on the other hand, are much more scalable. Chatbots can be quickly deployed to handle increased customer volume, and they can be just as easily taken down when demand decreases. Additionally, since AI doesn’t require breaks or vacation days, businesses can operate at full capacity at all times without incurring additional costs.
8. Improved Insight into Customer Behavior
Contact centers generate a wealth of data that can be used to improve the customer experience. However, most businesses lack the resources or expertise needed to effectively mine this data for insights.
This is where AI comes in. Using cutting-edge machine learning algorithms, AI can help businesses automatically identify patterns in customer behavior. This information can then be used to improve self-service options, customize agent scripts, or even develop new products and services. In short, AI gives businesses the ability to take a data-driven approach to the customer experience - something that was previously not possible.
9. Ability to Preemptively Resolve issues
In addition to providing insights into past customer behavior, AI can also be used to predict future behavior patterns. This allows businesses to preemptively resolve issues before they even occur.
For example, if an AI system detects that a customer is likely to cancel their subscription within the next month, it could automatically trigger a series of targeted interventions (such as discounts or special offers) in an attempt to retain the customer. Or if an agent is handling a complex issue that is taking longer than usual to resolve, the AI system could proactively offer assistance or escalate the issue accordingly.
By using AI in this way, businesses can not only avoid potential problems but also create opportunities for upsells and cross-sells.
10. Smarter Omni-Channel Support
Customers today interact with businesses through a variety of channels (e-mail, phone calls, social media messages, etc.), each of which generates its own data sets. Businesses must then consolidate this data into a single view in order to make informed decisions about the best way forward.
Unfortunately, most businesses struggle with this task. This is where AI comes in. By integrating with different systems and data sources AI can help businesses get a complete view of the customer journey – no matter how many channels they’re using.
What to Consider When Choosing a Contact Center AI Tool
The customer experience can make-or-break a company. So it's no surprise that businesses are turning to contact center AI tools to help improve the customer experience. But with so many different AI tools on the market, it can be difficult to choose the right one for your business.
Here are some key aspects to consider when choosing a contact center AI tool.
What team will use it?
Bygone are the days when only Customer Service Representatives used contact center AI tools. Now, more and more businesses are using them to support a variety of teams, including sales, marketing, and even product development. So it's important to think about which team will be using the AI tool and what their specific needs are.
For example, Commerce.AI can be used by both technical and non-technical teams, because it offers an easy-to-use interface and a broad range of integrations. Product teams can scan customer interaction data for sentiment across topics, trends, mentions of various products, and more, while marketing teams could, for instance, send out voice surveys after customer interactions to get customer feedback in real-time.
Integrations
Another important consideration is what kind of integrations the AI tool offers. Does it integrate with your existing CRM or contact center platform? If not, you may have to invest in new software or go through a lengthy and disruptive implementation process.
Commerce.AI's integration is now available with Genesys Cloud, an all-in-one solution and the world's leading public cloud contact center platform that helps organizations provide better experiences to their customers and employees. With this integration, businesses can quickly and easily get up and running with Commerce.AI, without having to invest in new infrastructure or disrupt their existing processes.
Breadth and depth of underlying data
When it comes to customer experience, data is key. The more data you have about your customers, the better you'll be able to understand their needs and resolve their issues. So it's important to make sure that the AI tool you choose has access to a broad range of data sources, including social media, email, chat, phone calls, and more.
It's also important to consider the depth of the data. Does the AI tool just surface basic information like customer name and purchase history? Or does it give you deeper insights, like customer sentiment across topics or product mentions? The more data you have access to, the better equipped you'll be to improve the customer experience.
Code vs no-code
One of the biggest decisions you'll have to make when choosing a contact center AI tool is whether you want a tool that requires coding skills or one that doesn't. There are pros and cons to both options.
On one hand, coding skills can be helpful if you want to customize the AI tool to fit your specific needs. On the other hand, non-coding tools tend to be easier to use and don't require any specialized skills. Ultimately, it's up to you to decide which option is best for your business.
Ease-of-use
Another important consideration is how easy the AI tool is to use. After all, if it's difficult to use, your team will likely never use it - no matter how good it is. Look for a tool that offers an intuitive interface and straightforward features that can be easily learned by anyone on your team.
Post-sales experience
After you've chosen an AI tool and gone through the implementation process, it's important to think about post-sales support. What kind of training and support does the vendor offer? Do they have a dedicated support system that can help you troubleshoot any issues? The last thing you want is to be left in the dark after implementation - so make sure post-sales support is included in your decision making process.
Future needs
It's also important to think about future needs when choosing an AI tool. In particular, you'll want to consider machine learning capabilities.
As artificial intelligence evolves, so too will customer expectations. To stay ahead of the curve, look for an AI tool that offers advanced machine learning capabilities, like predictive analytics and sentiment analysis.
Building a contact center AI strategy
In the past few years, there has been an explosion of interest in artificial intelligence, and its potential to transform businesses across industries. In particular, AI is seen as a key enabler of digital transformation initiatives, which aim to help organizations become more agile, customer-centric, and data-driven.
For contact centers, AI can be leveraged in a number of ways to improve operations and the customer experience. Here are some best practices for building an AI strategy for your contact center.
1. Define your business goals and objectives: The first step is to clearly define what you want to achieve with AI. Do you want to improve customer satisfaction scores? Reduce operating costs? Increase sales conversion rates? Once you have clarity on your goals, you can start mapping out a plan to achieve them.
2. Identify relevant use cases: There are many different ways AI can be used in a contact center setting. Some common use cases include automatic call distribution, natural language processing for chatbots, voice biometrics for authentication, and predictive analytics for workforce optimization. Think about which specific areas of your business would benefit from AI and prioritize those use cases.
3. Build a data-driven foundation: AI is only as good as the data it is based on. To ensure that your AI applications are effective, you need to have high-quality data sets to train them on. This means having clean and accurately labeled data, which can be a challenge for many organizations. If you don't have the internal resources to build a robust data set, there are now many companies that offer AI-as-a-service and can provide you with the necessary training data.
4. Implement slowly and incrementally: Introducing AI into your contact center should be done gradually, starting with smaller pilots or trial programs before rolling out across the entire organization. This will help you avoid any disruptions to your operations and give you time to fine-tune your AI applications.
5. Continuously monitor and evaluate results: Once you've implemented AI in your contact center, it's important to continuously monitor its performance and make adjustments as needed. This includes tracking key metrics such as customer satisfaction scores, first call resolution rates, average handle times, and abandoned call rates. By constantly monitoring these performance indicators, you can ensure that your AI strategy is on track and making a positive impact on your business.
Building an AI strategy for your contact center doesn't have to be complicated or time-consuming. By following these best practices, you can get started on leveraging AI to improve your operations and deliver a better customer experience.