Building the AI Contact Center of the Future with Robust Self-service

Contact centers are ushering in a new era. AI contact center solutions are redefining how customer experience is delivered. CX leaders are dedicating their resources to providing personalized and proactive support to modern, highly engaged customers. The customers expect robust self-service models powered by next-gen AI automation. Besides, innovations such as generative AI and conversational AI leading the charge of CX mass shift, it’s worthwhile to explore what the future of an AI contact center and customer experience will look like.

Deciphering Modern Customers’ Support Needs

The customer behavior is changing drastically. The modern customer is more tech-savvy and engaged, which means they will attempt to sort their issues on their own first. About 83% of customers choose self-service over speaking with a CS rep. Besides, they expect the support to be delivered seamlessly across multiple channels – on average, 8 for customers and 10 for business buyers.

Moreover, 93% of customers build affinity towards a brand that is available on their preferred channel. This all needs to ensure zero-wait convenience, 24/7 availability, and fast response. But that’s not it. Over 71% of customers not only expect a personalized experience, but about 76% even get upset if it’s not there. This means your business needs to have a highly detailed understanding of the customer’s behavior and desires.

Simply put, modern customers want to

• Solve issues on their own
• Use their preferred channels
• Delivered in a personalized way
• And get superfast query resolutions
• Irrespective of time or geographical factors.

It’s beyond the human capability to deliver on these expectations in a fulfilling manner. Modern AI innovations can mitigate this issue at scale, from automating simple and repetitive tasks to equipping CS professionals with insights to resolve issues with ease. An AI-based call center can address these challenges and nurture the creation of the contact centers of the future.

AI is the Cornerstone for Next-Level Customer Experience

Customer support has come a long way. Traditional CS models before AI faced issues with human errors, long wait times, limited scalability, and high operational costs. Moreover, delivering frictionless personalized support across various channels was nearly impossible. AI call centers can operate 24/7, have advanced routing mechanisms for fast resolutions, and have great scope for customer insights. 

AI can analyze vast datasets to create personalized experiences based on individual preferences and histories. AI chatbots provide instant responses to eliminate wait times and improve CSAT. Latest innovations, such as generative AI and conversational AI for contact centers, virtual agents, speech and intent recognition for sentiment analysis, automated ticketing, and semantic search, are expected to further the advantage in favor of AI-powered contact center solutions.

Key Opportunities with AI in Contact Centers

Smart Self-Service

Only 11% of businesses are prioritizing smarter self-service despite 36% of consumers wanting this as a priority.
Source: 2022 Digital-First Customer Experience Report, NICE

AI is taking self-service models to the next level. Customers can now solve more complex queries independently. FAQs, knowledge bases, and video assistance can be enhanced via AI, thereby boosting customer satisfaction and freeing up agents. Video assistance is often overlooked in self-service, but around 96% of people watch an explainer video to learn more about a product or service. On top of that, AI chatbots and smart IVRs go beyond traditional alternatives to help with highly convoluted issues while enabling better routing for the process. Besides, robust self-service empowers customers and is capable of continual self-learning from consumer insights.

Omnichannel Approach

Over 93% of customers build affinity towards a brand that is available on their preferred channel. Source: CX Trends Report 2022, Zendesk

AI can seamlessly enhance your communication channels, including phone calls, emails, social media, IVRs, chatbots, or any other medium. These AI-powered contact center workflows not only deliver unified CX but also create consistency in service quality and enhance customer journeys on their preferred channel. Such comprehensive communication makes way for more personalized experiences across channels. In real life, communication is contextual and can carry over across mediums. Contact center AI can realize this via real-time channel switching to boost flexibility and contextual conversations.

Operational Efficiency

62% of call center managers say they can’t analyze enough calls to evaluate agent performance accurately.
Source: The State of the Contact Center, Invoca

Contact centers have historically struggled with inefficiency at many levels. AI effectively addresses these challenges to boost efficiency at several touchpoints. It automates routine tasks and optimizes resource utilization, allowing agents to focus on complex problem-solving. Conversational intelligence enables intent recognition that facilitates quicker issue resolution. Contact center AI is proving to be highly effective in workflow optimization by using in-depth workflow analytics for adaptive and informed contact center operations. For instance, AI is used by contact centers to employ predictive resource allocation and maintain optimal staffing during high-volume periods.

Actionable Business Insights

37% of CS reps state that AI tools that can collect and analyze customer feedback are the most popular/in demand.
Source: The State of AI in Customer Service, Hubspot

Leveraging AI in contact centers provides access to valuable data analytics, generating actionable insights from customer interactions. These insights empower businesses to make informed decisions, identify trends, and adapt strategies to meet evolving customer needs. Brands are investing in tools that help with sentiment analysis, customer challenge identification, brand perception monitoring, and creating personalized engagement strategies. CX is the key, but creating an effective system for that requires an in-depth understanding of the customer mindset, to the point of predicting why they are contacting before they do so. AI insights make it possible to achieve that.

Improve CX and CSAT

Companies that excel at personalization generate 40% more revenue from those activities than industry stakeholders that don’t.
Source: The Value of Getting Personalization Right—or Wrong—is Multiplying, McKinsey

The modern business landscape demands highly agile customer centricity. CX and CSAT can directly impact business growth and success by fostering customer loyalty and brand affinity. Contact center AI helps understand customer intent and journey at a granular level. With precision routing, customers can be connected to the best agents for the query. Moreover, detailed customer profiles and real-time prompts enable the agents to understand the issue and deliver the correct solution in a timely manner. In addition, AI is proving to be highly effective at enhancing self-service and decreasing wait times, and customers can resolve simpler queries on their own.

Deliver Proactive and Frictionless Support

54% of CS leaders consider proactive customer service as a priority.
Source: Reactive to Proactive: How to Shift Your Support Strategy, Hiver

AI enables contact centers to shift from reactive to proactive customer support. By anticipating customer needs and issues, An AI powered contact center can empower agents to address concerns before they escalate. CX leaders are deploying automated systems that send reminders for payments and renewals. Issue prediction is used by analyzing patterns and minimizing disruptions. This can be personalized at scale, helping customers interact with your support in a smooth and frictionless manner. This translates into business benefits in terms of contact center cost reduction and optimization.

Enhance Resource Management

65% of CS leaders state that AI has had a positive impact on their customer service costs.
While 68% reported positive outcomes on resolution times.
Source: Customer Service Excellence 2023, Deloitte

AI optimizes resource allocation in contact centers by predicting peak times, staffing requirements, and skill-based matching. If the right agents are available whenever they’re needed, idle time and resolution times drop significantly. Accurate insights about the workforce requirements during different times of the year allow the AI contact centers never to overstaff or understaff. Agent training can also be optimized in a precise and personalized manner. The impact of AI on resource optimization is highly layered, positively impacting several touchpoints, including costs, resolution times, and ROI.

Improve Support Routing

87% of organizations are interested in implementing AI to provide real-time assistance to customer service agents.
Source: State of Conversational AI in the Contact Center, 8×8

AI-driven systems significantly improve support routing by analyzing customer queries and directing them to the most suitable agents or channels. This significantly speeds up issue resolution while ensuring customers are connected to the most qualified support personnel. This can enhance the overall quality and effectiveness of customer interactions. Advanced channel optimization ensures that CX remains consistent and effective across channels. Improved support routing translates to quicker resolutions and higher CSAT. Besides, AI is enabling intent-based routing algorithms and dynamic routing strategies.

Zero-wait and 24/7

AI contact centers use real-time agent assistance and specialized tools to automate over 80% of customer support tickets.
Source: AI in the Contact Center: An Essential Tool, CMSWire

Modern customers expect their support to be zero wait and available 24/7. Chatbots, smart IVRs, and virtual assistants in an AI-powered contact center can handle such demands effortlessly. This around-the-clock accessibility ensures that customers receive support whenever they need it, contributing to higher satisfaction and loyalty. While chatbots can instantly provide responses and resolutions for simpler queries, virtual assistants are built to mimic human agents with conversational AI, thereby delivering support to complex issues. In case of escalation, automated ticketing helps customers feel heard and minimizes wait times.

How AI Enhances Self-Service: Revolutionizing Customer Support

Self-service is a cornerstone of modern customer support. The support domain has been mired with high attrition rates, around 19% for service professionals. While CX leaders are deploying employee satisfaction strategies to bring it down, at the customer end, such factors cannot be pardoned for subpar CX. Self-service holds high strategic value as it enables delivery of satisfactory support and CX irrespective of the situation at the end of workforce availability. About 59% of customers prefer self-service tools for simple questions/issues. In a recent survey involving generative AI early adaptors in the sales and support domain, 48% said the technology would help transform self-service options. Here are a few other ways through which AI innovations can improve self-service in contact centers:

Predictive Analytics for Personalized Support

Predictive analytics involves the forecast of future trends and behaviors to enable businesses to anticipate customer needs. Data algorithms can process vast amounts of data to offer highly personalized recommendations and solutions. By understanding a customer’s history and preferences, businesses can proactively provide them with relevant information or support. This not only improves customer satisfaction but also reduces the workload on human support agents.

Conversational AI: Human-like Connections

Conversational AI is a key element of the next-gen AI-powered contact center self-service. Chatbots and virtual assistants equipped with conversational AI can engage customers in human-like interactions. It collates the efficiency and automation of AI with a level of experience and connection like a human agent. These capabilities are at the forefront of making self-service more efficient and user-friendly in AI-powered contact centers.

Smart IVR: Streamlining Customer Interactions

Interactive Voice Response (IVR) systems have been part of self-service for years, and AI is taking them to the next level. Smart IVR for customer support can understand and interpret customer responses more accurately. This allows customers to navigate through the IVR system using natural language and have their queries resolved without speaking to a live agent. AI-powered contact center IVRs go beyond streamlining customer interactions to deliver a more powerful self-service experience.

Automated Reminders: Keeping Customers Informed

AI is adept at automating routine tasks, including sending notifications and automated reminders for customer support. For example, it can send order updates, appointment reminders, or important alerts to customers. This keeps customers informed and engaged without the need for manual intervention, ensuring they have all the necessary information at their disposal. This reduces the number of inquiries and enhances the self-service experience.

Intent Recognition: Understanding Customer Needs

AI can recognize customer intent from their queries. Natural language processing (NLP) models can determine the underlying purpose of a customer’s inquiry, enabling AI-driven systems to provide relevant information or actions. This is a significant advancement in self-service, ensuring that customers receive precisely what they are looking for, quickly and accurately. Even in the case of escalation, intent recognition helps by creating detailed customer journey maps and profiles to help the agents. 

AI FAQs: Intelligent Self-Service Content

Frequently Asked Questions (FAQs) are a fundamental aspect of self-service. With AI, FAQs can become more intelligent and dynamic. AI-powered FAQ systems can continuously learn and adapt to customer queries, updating content based on the questions customers ask most. This ensures that the FAQs remain relevant and helpful, serving as a valuable resource for customers seeking answers on their own.

Conclusion

AI-powered contact center innovations signify a transformative era for customer support. With modern customers increasingly favoring self-service and expecting seamless, personalized assistance across multiple channels, AI is the missing piece in the jigsaw puzzle of CX. It addresses longstanding challenges of traditional customer service models, offering 24/7 accessibility, advanced routing, and rich customer insights for personalized support at scale. AI’s profound impact extends to operational efficiency, with task automation and workflow optimization enhancing resource allocation and reducing costs.

The power of AI lies in its ability to generate actionable business insights from customer interactions, informing data-driven decisions and tailored engagement strategies. The major benefactor is CX, which can be deployed at scale with precise personalization, routing, and real-time prompts for agents. AI’s role in delivering proactive and frictionless support positions it as the driving force shaping the future of customer support. With automation set to automate one in ten agent interactions in contact centers by 2026, AI-powered self-service and automation are well-positioned to lead this mass shift.