Automation in contact centers is already essential to making customer service customer-centric. AI, machine learning, and advanced analytics can improve many processes, including handling routine inquiries, reducing wait times, and improving overall service quality.
The shift towards automation in contact centers has made customer support available 24/7 to customers and helped companies meet demand for seamless omnichannel customer service.
Powerful analytics also enable contact centers to identify common issues and other trends, allowing them to solve problems proactively.
The shift to automation is already happening, but here, we'll see what this is and how companies use it to their advantage in contact centers.
What is contact center automation?
Contact center automation is simply using technology, particularly AI-powered solutions, to improve and streamline contact center operations without the need for direct input from human agents.
Examples include automated call routing, which lets AI and other types of automation direct calls to the right departments and human agents. Interactive voice response solutions can also help customers find the right department and agent without speaking to a human customer service agent first.
Chatbots allow customers to interact on websites, apps, and social media to solve problems, answer FAQs, provide information, or complete transactions and other tasks.
Much like chatbots, callbots offer many benefits for contact centers by allowing customers to resolve issues over the phone, speaking to an AI just as they would a human agent.
Contact center automation is also particularly useful for self-service. It allows customers to find solutions to their issues using knowledge bases, FAQs, and AI-guided assistants without speaking with a human agent via chat or phone.
AI is driving call center innovations
With the recent advances in AI, there's been much innovation in how companies use it.
The applications for AI are particularly useful in improving call center efficiency. By automating specific processes, particularly repetitive ones, using AI, call and contact centers are improving and more efficient.
AI solutions aren't replacing human agents but instead automating monotonous and repetitive tasks, allowing human agents to provide more value to customers by dealing with more complicated issues and inquiries.
AI also improves the quality of customers' interactions with call centers. From guiding calls to suitable agents and departments to answering FAQs and other quickly resolved issues, AI means that customers get faster and more effective solutions.
Let's dive deeper and see the ten most significant trends in contact center automation.
1. Omnichannel Integration for Seamless Customer Experience Across All Channels
Automation and AI-driven contact center solutions provide consistent customer-centric service across every channel. With around 73% of customers using multiple channels during their shopping journey and 54% preferring messaging apps to contact businesses (Wisernotify), omnichannel customer service is essential.
Thanks to knowledge bases, customer information can be centralized so that AI-powered solutions and other kinds of automation can access customer information from other channels, including records of previous interactions with customer service.
AI and automation can help make the brand experience more consistent, encouraging customers to use the channels of their choice, which can help spread incoming call or query volume across multiple channels.
Thanks to the consistent omnichannel customer and brand experience, customers can seamlessly switch across channels, going from calls to chats to emails or any channel they like, knowing that a human or AI customer service agent can pick up the query from where they left it.
2. AI-Powered Hyper-Personalization Leveraging Data Analytics
AI can leverage data analytics to understand customer preferences, improve customer engagement, and make real-time adjustments during customer interactions on any customer service channel.
Personalization is key for customer retention and cross-channel consistency. According to McKinsey, it can provide five to eight times the ROI on marketing spend and boost sales by 10% or more.
These analytics and AI-driven hyper-personalization are changing how businesses interact with customers, making marketing campaigns more effective and creating better customer loyalty.
As AI continues to improve, the levels of personalization available to businesses and, ultimately, customers will only continue to grow.
3. Self-Service Revolution Empowering Customers with AI Tools
AI and automation are changing how customers deal with issues and inquiries. Customers now have the agency to solve problems using AI tools like chatbots and virtual agents.
Thanks to natural language processing (NLP) technology, customers can ask a chatbot or virtual assistant about their issue or query and get instant support. Examples include getting account information, payment processing, and troubleshooting.
Customers no longer have to wait on the phone for a live agent to resolve any issues, and many common problems can be solved quickly and efficiently using AI tools.
For example, Bank of America's Erica AI assistant offers customers guided support to navigate banking services, complete transactions, and handle millions of weekly requests.
According to Renascence.io, 85% of customer interactions are expected to be solved without human intervention by 2024.
4. Evolved IVR Systems Transitioning to AI Callbots
Previously, contact centers typically relied on Interactive Voice Response (IVR) systems to direct customers' calls and provide basic self-service through menus.
Now, thanks to AI callbots, which use Natural Language Processing (NLP), customers can interact more naturally, speaking in a similar way as they would to a human agent.
As with other aspects of contact center automation, AI callbots provide more personalization and integration with existing CRM systems, offering conversations based on the customer's history and preferences.
AI-powered solutions make this available 24/7, and AI callbots continuously learn and improve, which wasn't possible with older IVR systems.
For example, Vodafone's TOBi AI callbot has helped reduce customer response times by 30%.
Just remember that while AI callbots have many advantages over IVR systems, you have to carefully consider the challenges of integrating these new technologies, especially in terms of data privacy.
5. Robust Security Measures Protecting Customer Data in Contact Centers
While automation and AI solutions allow contact centers and other customer service channels to use massive amounts of data to offer personalized customer service, security remains a crucial consideration.
Luckily, companies can use AI technologies for threat detection, including data breaches, given role-based access control (RBAC), operate in line with data protection regulations like the GDPR, and use multi-factor authentication (MFA) for customer interactions.
Depending on the industry, AI solutions can also ensure compliance with certain industry standards, particularly regarding payment data, health information, or standards dependent on a customer's geographic location following local, national, or international law.
6. Agent Empowerment Enhancing Well-Being and Performance with AI Tools
Businesses use AI tools and automation to empower their human agents with real-time information and guidance during customer service interactions.
AI agents, for example, can give human agents suggestions and information during calls, improving average handling times and providing better customer interactions.
Companies use AI tools to help manage human agents' workload. Automating monotonous, repetitive tasks allows human agents to focus more on complex customer queries, ultimately reducing their workload and improving their overall health and well-being.
Companies aren't using AI to replace human customer service agents. Instead, they're using a hybrid solution of human and AI agents, allowing each to work to the best of their abilities. H&M, for example, has implemented AI chatbots to handle general customer inquiries and provide personalized shopping advice while human agents offer deeper customer support.
7. Predictive Analytics Proactively Addressing Customer Issues
Thanks to historical data, AI, and machine learning, companies use predictive analytics to forecast customer behavior and identify customer preferences.
Companies use AI solutions to provide customers with personalized offers and solutions before customers reach out to a contact center or any other customer service channel.
This can be used to resolve issues before they occur or to de-escalate issues before they even reach a human customer service agent.
For example, American Express uses predictive analytics to identify potential offers and services to customers based on their spending patterns.
Thanks to this knowledge, customer interactions are optimized, choosing the right timing and channel. AI-powered systems, for example, could predict that a customer prefers to be contacted by a certain channel at a certain time and schedule a call, email, or message in accordance with these analytics.
This also allows companies to allocate resources better, limit the number of customer service inquiries, and reduce the workload of human customer service agents.
8. Virtual Assistants and Voice Commands Enhancing Customer Interactions with AI
Interactions with AI-powered customer service solutions are improving, and AI is now more capable of handling more complex and nuanced customer queries.
While the most detailed and complicated issues are still best left in the hands of a human customer service agent, AI-driven solutions offer round-the-clock solutions when human agents aren't available.
Not only does 24/7 customer support improve customer satisfaction, but modern AI solutions offer better and more natural interactions than earlier AI technologies.
Since current AI solutions can also be trained, contact center operations for specific industries can be automated to deal with far more specific queries over the phone using voice recognition in real time.
Domino's Pizza streamlines the ordering process by using the Dom pizza ordering bot to handle orders via voice command over the phone and through an app.
9. Automated Routing Directing Customers to the Right Agent Instantly
Recent developments in AI have allowed contact centers to use AI to automate call and query routing in a way that wasn't possible with older IVR systems that used menu-based interactions.
Automated routing and AI allow customers to be routed to agents and departments based on specific skills. This is a great way to ensure each customer speaks to the best-suited human agent to deal with their query.
Analytics can be used to offer predictive behavioral routing where calls are redirected to departments and agents based on predicted interaction dynamics. For example, an AI callbot or chatbot could route calls from customers with a history of complicated issues to experienced agents. In contrast, more straightforward issues can be routed to trainees and less experienced agents.
While not specifically call routing, Uber's AI algorithms use routing to quickly and efficiently connect ride requests with available drivers while optimizing wait times and trip durations.
10. Enhanced Customer Feedback Systems Providing Real-Time Insights for Continuous Improvement
AI is being used in contact center automation to analyze customer sentiment during and after interactions, collecting data across multiple channels, such as calls, chats, emails, and any other interactions with the company.
Many companies are using AI algorithms to analyze feedback data and identify trends, patterns, and specific issues. From this data, machine learning can be used to predict customer behavior, allowing companies to proactively make changes to improve the customer experience.
The Ritz-Carlton hotel chain leverages real-time insights from guests to constantly improve customer service.