AI in Action: Use Cases for Faster, Smarter Contact Centers

Communications and media customer service: Process intelligence provides a fresh playbook

According to a recent market study on CX trends, challenges, and opportunities, 55% of consumers feel experiences have worsened over the past year. The overwhelming majority say experiences remain devoid of convenience, personalization, empathy, and simplicity. Also, in a sobering commentary on the state of AI, customers identify the inability to access a human agent and unhelpful automation platforms as ChatGPT the two most significant pain points in customer service. However, savvy business leaders will not let these statistics shake their faith in AI’s potential. Instead, they will treat them as a call to adopt a more customer- and employee-centric approach to AI. Companies will stop focusing on what AI theoretically could do and prioritize what it should and must do within the customer contact operation.

Without first remedying internal frustration points, brands are setting agents up for catastrophic failure. Using advanced computer vision and voice analysis, AI systems have the capability to detect and analyze human emotions in real time. These systems can interpret facial expressions, tone of voice and even subtle gestures to gauge a person’s emotional state. The insights gained from this analysis can provide valuable context and help create more personalized and empathetic interactions during customer engagements. Traditional in-person onboarding methods, such as shadowing, can lead to inconsistencies in training quality depending on the mentor assigned to the new hire.

CRM for Customer Service: AI Trends

Traditional approaches often treat these two aspects in isolation, resulting in a disjointed customer experience. Customers dissatisfied with issues like poor connectivity or unexpected charges are less responsive to marketing promotions. This highlights the need for a more integrated approach to customer service and marketing. But, brands should also consider a change of mentality in how they handle customer complaints. Some leverage VoC tools to do so, allowing them to prioritize issues; track complaint trends; democratize this insight; and take invaluable, cross-functional actions to improve customer experience. EWeek has the latest technology news and analysis, buying guides, and product reviews for IT professionals and technology buyers.

Innovations in artificial intelligence have made today’s technologies more powerful and valuable than ever. NICE is also leveraging AI to support supervisors and CX leaders, providing real-time and historical insights into CX operations along with actionable steps to optimize employee and customer experiences. When an AI is unable to adequately resolve a customer question, the program must be able to route the call to customer support teams. This collaborative approach between AI and human agents ensures that customer engagement is efficient and empathetic. These conversational AI applications can efficiently handle customer inquiries and provide support around the clock, thereby freeing up human support agents to handle more complex customer issues. With AR in customer support, customers can use their smartphones or AR glasses to overlay digital information onto the real world.

• Companies also use machine learning for customer segmentation, a business practice in which companies categorize customers into specific segments based on common characteristics such as similar ages, incomes or education levels.
• Conversational IVR systems can interact with callers in a natural format, responding to their spoken queries instantly, and helping to guide them towards the right solutions.
• These conversational AI applications can efficiently handle customer inquiries and provide support around the clock, thereby freeing up human support agents to handle more complex customer issues.
• It can transcribe calls in real-time, aiding customer service representatives in more effectively understanding and addressing customer needs.
• When using AI in customer facing use cases – such as voice and chat bots – organizations should build, train and test their models on real, business-specific customer data before deployment.
• Focus on automation opportunities that will improve the experiences of your customers, agents, and team managers.

Microsoft’s widespread implementation and continuous expansion of generative AI functionalities position it at the forefront of AI innovation. Netflix relies on generative AI to enhance user engagement by creating personalized content previews and thumbnails tailored to individual viewing preferences. This technology analyzes user data, including past viewing habits and ratings, to make visuals that highlight aspects of the shows or movies predicted to resonate with certain viewers. By automatically producing these personalized previews, Netflix not only increases the likelihood of users clicking the suggested content, but also elevates the overall platform experience.

Generative AI Tools Transforming Customer Service

That’s why evaluagent has launched a GenAI-powered solution that analyzes a customer’s contact center conversation before predicting what score they would have left if asked the NPS survey. Indeed, the GenAI-powered solution first ingests various sources of such feedback – including surveys, conversation transcripts, and online reviews. That will impact many aspects of customer service, and chatbot development offers an excellent early example.

Benefits include effective self-service, enhanced remote work and improved contact center metrics. To keep up with consumer expectations, customer service managers should know what KM is, how it can improve contact center operations and how GenAI can help. Launched in early 2024, Arc Search is a standalone mobile search app created by The Browser Company, which also owns the Arc browser. Its app can “browse” for users based on queries and generates unique results pages that act like original articles about the topic, linking to all of the sources it uses to generate the result. Like Perplexity, the service does not include ads, and the Arc browser connected to it even blocks web trackers and on-page ads by default.

Sidekick is your AI-enabled ecommerce adviser that provides you with reports, information about shipping, and setting up your business so it can grow. Although rule-based chatbots are more limited than AI bots, they can still handle initial customer service conversations and funnel customers to the proper human agents. A rule-based chatbot can also walk a customer through a routine task, like initiating a return. That automation can improve a business’s customer experience by delivering immediate responses to common questions. So I think there’s a clear distinction then between artificial intelligence, really those machines taking on the human capabilities 100% versus augmented, not replacing humans, but lifting them up, allowing them to do more.

Advanced analytics can predict support volumes and resource needs, while in-depth analysis uncovers hidden customer needs and pain points. Robust reporting and analytics transform your support team from firefighters to fire preventers, predicting and solving issues before they escalate. For example, when a VIP reports an issue, the system can automatically flag it as high-priority and route it to top agents without human intervention. Before you decide, scrutinize these must-have features to support smooth case handling and happy customers. Hippocratic AI trained its models on evidence-based medicine and completed rigorous testing with a large group of certified nurses and doctors. The constellation architecture of the solution comprises 20 models, one of which communicates with patients while the other 19 supervise its output.

As such, customers can choose the channel that works best for them, which increases satisfaction. These interactions are personalized, consistent, and continuous regardless of which touchpoints customer service use cases the customer chooses, such as in-person, online, mobile app, email, or phone. In these models, multiple stakeholders interact with the customer across different branded channels.

This speeds up customer response time and frees up customer service teams, who can be deployed to higher-complexity cases referred by the chatbot if it doesn’t have the necessary information. In addition to facilitating simple, consistent, and smooth implementations, advanced chatbots support a variety of languages and communication channels, enabling customer support personnel to provide quicker and more individualized services. Telcos face a major challenge in balancing marketing efforts with service-related customer interactions.

Instead of forcing customers into chatbots before they are ready, brands should identify the specific use cases for which bots are superior and then educate customers on this opportunity. By helping customers see the value (whether in terms of resolution quality or time savings) they can get from bots, brands will change the narrative. Customer service teams need tools that overcome/eliminate these challenges and drive changes that impact their customers’ experience. We needed a place to sit that volume of customer service requests in one spot so our agents could handle email and chat tickets. Up to half of companies surveyed saw an average 20% reduction in escalation with AI-powered chatbot conversation flows, and a 10% improved cross-and upsell rate after adopting real-time transcriptions to identify opportunities for sales.

AI integration offers investment returns by scaling customer and employee capabilities, automating tedious and redundant tasks, and offering consistent experiences based on collected and specialized data. In addition, predictive analytics, powered by machine learning and process AI capabilities, can be used to create proactive customer service practices. These AI tools can predict customer needs and behaviors by analyzing past interactions and resolving issues even before they arise. AI-driven customer service is reshaping telecom, offering personalized experiences with seamless connectivity and swift issue resolution. Integrating service with marketing, telecom companies are overcoming traditional challenges, enhancing customer satisfaction, and reducing churn.

Aptly named, these software programs use machine learning and natural language processing (NLP) to mimic human conversation. They work off preprogrammed scripts to engage individuals and respond to their questions by accessing company databases to provide answers to those queries. Tomi Behm is a senior security professional with 24 years of experience in cyber security. He has worked with customers ranging from small businesses to large enterprises across multiple industries.

Lighthouse use cases are specific scenarios where AI-enabled personalization can make a significant impact, providing a starting point for implementation. AI decisioning can personalize interactions with customers, ensuring that each communication is relevant and tailored to the individual. This not only enhances the customer experience but also increases the effectiveness of marketing campaigns.

NVIDIA NIM microservices, part of the NVIDIA AI Enterprise software platform, accelerate generative AI deployment and support various optimized AI models for seamless, scalable inference. NVIDIA NIM Agent Blueprints provide developers with packaged reference examples to build innovative solutions for customer service applications. According to McKinsey, over 80% of customer care executives are already investing in AI or planning to do so soon. In nearly every industry, AI systems can help improve service delivery and customer satisfaction.

The AI powered chatbots can also provide a summary of the order and request confirmation from the customer. It can also provide real-time updates on the order status and location by integrating with the business’s order tracking system. This includes customer profile, related accounts, billing status, buying history, browsing history, past issues and social media conversations, along with the emotional context of the current interaction. “While we’ve observed an increasing number of customers turning to GenAI tools to try and self-resolve their customer service issues, often this is happening before they interact with a company-owned channel,” Sladdin said. Brian Cantor is the Managing Director of Customer Management Practice’s Digital division. Reaching a community of almost 200,000, these digital properties offer industry-leading commentary, research reports, and virtual event sessions.

It is system-agnostic, allowing teams to capture data from any customer service system, including homegrown and legacy systems. It can also connect to multiple CX channels like CRMs, contact-centers, chatbots, web portals and messengers to get an end-to-end view of the customer journey. The integration of AR and VR into customer support signifies a shift toward more engaging, efficient and effective support experiences. AI plays a pivotal role in self-service options within customer support, fundamentally transforming how customers access and receive support. By integrating AI, businesses can offer sophisticated self-service platforms that not only enhance the customer experience but also improve operational efficiency. Customer support teams, across any industry, will use information from multiple systems to understand customer behavior and resolve customer issues.

It can also provide tools for resolving common customer issues like easily returning items based on previous purchases. By measuring the time saved in each customer contact, you can quantify the agent’s impact. They can handle a wide range of tasks, from customer service inquiries and booking reservations to providing personalized recommendations and assisting with sales processes. They are used across websites, messaging apps, and social media channels and include breakout, standalone chatbots like OpenAI’s ChatGPT, Microsoft’s Copilot, Google’s Gemini, and more. Rule-based chatbots do not use AI, but AI-powered chatbots use conversational AI technology. Conversational AI systems use natural language processing (NLP), deep learning, and machine learning to understand human inputs and provide human-like responses.

Chatbots are AI systems that simulate conversations with humans, enabling customer engagement through text or even speech. These AI chatbots leverage NLP and ML algorithms to understand and process user queries. You can foun additiona information about ai customer service and artificial intelligence and NLP. Since AI chatbots can answer more elaborate user questions ChatGPT App and execute more complex tasks than a basic chatbot,  ecommerce businesses can use these types of chatbots to support a wider range of sophisticated customer support functions. The time is right for organizations to embark on a journey of experimentation with GenAI.

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