What is Contact Center AI?
Artificial Intelligence (AI) can be integrated into your contact center to deliver a better experience, providing agents with actionable insights to optimize and guide their interactions with customers. Contact center AI can be seen as a subset of customer service artificial intelligence, focusing on internal AI solutions that can support agents.
How Does Contact Center AI Work?
Contact center AI works by integrating AI into various contact center processes, such as AI analytics. But what is AI analytics, and how does it work in contact centers? AI analytics can analyze customer behavior and previous interactions to establish thorough customer profiles. This enhances automatic call distribution (ACD), matching customers to the agent best suited to solve their query. During customer service interactions, AI can assist agents by recognizing keywords during interactions, interpreting requests, and suggesting solutions.
Why are Businesses Implementing AI in the Contact Center?
Businesses integrate AI into their contact centers for several reasons.
Anticipate Customer Needs
AI can evaluate previous interactions across multiple channels, thereby creating a customer profile. AI can then finds other customers with similar profiles, and by comparison, anticipate their needs. This helps create personalized messaging. AI analytics can also better prepare human agents for customer interactions by giving them a complete picture of each customer and their needs and preferences.
Virtual assistants and chatbots
Virtual assistants offer the best of both worlds, with both a human and AI touch to deliver the best customer service experience. AI can work alongside the agent in customer interactions, detecting relevant keywords, and steering the conversation to optimal outcomes. From this, AI can work to collect relevant information the agent may need and suggest how to solves a customer’s challenge. Agents are then able to interact with customers directly, providing a human touch while making the most of AI-powered data and insight.
Predictive call routing
Traditional systems will route customers to the next available agent – at the most, they will consider simple preferences if the customer has previously register them, such as routing a Spanish-speaking customer to a Spanish-speaking agent. AI can improve this process dramatically.
AI can analyze all existing information about a customer, including complex factors like past behavior, the products they own and their personality type. This way, the customer can be matched to an agent who is not only knowledgeable about their problem, but one who suits their personality and sets the customer at ease.
Assisting agents, assessing interactions
Today’s AI technologies used in customer care & support environments help human service agents solve customer, employee and other end-user problems in real-time with greater effectiveness, efficiency, accuracy and certainty.
In fact, a patent-pending technology that digital transformation leader Sutherland uses can — on a turn-by-turn basis within a conversation — actually predict the eventual CSAT or NPS rating associated with each customer interaction as it’s taking place.
Every conversation that runs through a customer support team also runs through the technology’s semantic deep learning engine. The conversation is labeled with insight and predictive KPIs while still underway. That means management teams can step in to proactively support agents at the right moment before a conversation goes south (which some inevitably do) and the customer decides to vent on social media.
Brands can use agent assist AI to look into every conversation of every agent to discover the key moments behind each and every rise or drop in customer satisfaction. Plus, they can understand which events and conversational behaviors have the biggest impact on service performance — even going to far as to predict the number of CSAT and NPS points to be gained (or lost) while estimating savings in time and money.
Pros of Contact Center AI
Contact Center AI speeds up customer service processes in both virtual and human interactions. This has benefits for both a customer and the contact center.
Improves the Agent Experience
74% of contact center employees are at risk of burnout, since regularly engaging with unhappy customers can negatively impact mental health. AI steps in to assist agents. By guiding conversations, AI can suggest the best course of action and improve the success rate of calls, keeping customers happy. This also helps agents improve by letting them know how to best reach positive solutions in their calls and improve their performance.
AI can also take on the burden of being the first line of customer service, allowing agents to only deal with the cases that require their personal touch. Automation can free agents from repetitive and time-consuming tasks like searching for customer information.
Improves the Customer Experience
AI improves the customer experience by using analytics to anticipate their needs. Customers can be presented with solutions or products for their problems before they know they would want or need it. AI also helps to shorten interactions by providing agents with customer information rather than them searching for it.
Customers issues can be solved quickly, reducing frustration and building trust in your business. Customers are also more trusting when you have a higher first call resolution (FCR) rate, which is aided by AI assistance to human agents in calls.
Cons of Contact Center AI
There are some downsides to using AI in the contact center if you use it wrong.
Risk of Lack of Human Touch
Virtual assistance in interactions can sometimes lead human agents away from following their own instincts, making it less likely that right ‘personal touch’ gets delivered. And while AI can shorten customer service interactions, sometimes replacing human interactions without those of a machine can turn customers away – particularly in those circumstances where a warm, personal, human interaction is most needed. Customers appreciate a human touch, and don’t want to feel like they had an automated experience even when they’re talking to a live human agent. It’s important to train agents on how to get the most out of AI without becoming overreliant of it.
AI requires ongoing health checks and maintenance to ensure it is running correctly and meeting requirements. Ongoing maintenance is an important cost to factor in when considering the investment in Contact Center AI.
What’s Next for Contact Center AI?
The Contact Center is likely to see a greater unity (even synchronicity) between AI and AI-assisted human agents. AI will continue to support agents and increasingly automate repetitive tasks. There will be an increase in self-service options, as machines can anticipate and preempt problems – offering solutions proactively, even before a customer reaches out for help.
And yet, it’s unlikely that AI will ever fully replace human agents, since businesses will recognize the value to be delivered in human-to-human interactions, and customers will appreciate being heard and responded to as a uniquely individual human persons.
About Sutherland Conversational AI
By integrating with your CRM and enterprise systems, Sutherland can design, develop, monitor and maintain an advanced AI chatbot custom-built for your business needs. Sutherland Conversational AI helps ensure consistent, satisfactory interactions for your sales, support and other enterprise processes.
An evolving service that adapts to the needs of your customer lifecycle, Sutherland’s enterprise-grade conversational AI applications can help:
- Automate customer self-service interactions and business processes.
- Convert website traffic and generate more qualified leads.
- Improve customer service and user experience.
- Expand after-hours support.
Sutherland Conversational AI features:
- A dynamic, interactive user interface.
- Machine Learning and Natural Language Processing technologies.
- Customized conversational design.
- Integration with common CRM and enterprise chat platforms.
- Conversational analytics.
- GDPR-certified program.