The customer service stories of the call centers in the past were mostly associated with bad user experiences. These included:
- lengthy wait times for the support agents to answer the phone call,
- numerous call transfers to the right agent, and
- When finally the problem was discussed, it was either not properly resolved or the response was, ‘We will get back to you shortly!’
Isn’t that true?
But today, these experiences have completely changed with the introduction of AI in the call center industry. In a survey by Salesforce, 93% of customer service professionals have reported that AI saves them time on the job. Artificial Intelligence (AI) has revolutionized customer services by enabling companies to use AI models that provide conversational human-like communications to enhance customer experience.
What are AI call centers?
AI call centers are companies that use artificial intelligence technologies like natural language processing (NLP), machine learning, voice recognition and multiple AI algorithms to simplify and automate several customer-service processes.
These services include responding to user queries, handling complaints and feedback from the clients, automated customer conversations, streamlining wrap-up processes and consolidating customer data.
The main difference is, AI-driven call centers offer fast automation, efficiency, and cost savings, while human-operated call centers provide empathy, emotional intelligence, and personalized service.
Benefits of AI in customer service
AI-powered customer service offers multiple advantages, making support more efficient and cost-effective.
- Lower Operational Costs – AI automates repetitive tasks, optimizing workflows and reducing costs by 10% while improving customer satisfaction by 20% (McKinsey).
- Personalized Interactions – AI accesses customer data to provide relevant details like name, account info, and past interactions, ensuring a seamless experience. Using AI for content personalization can go a long way in improving customer experience.
- 24/7 Support – AI-powered chatbots and virtual assistants offer round-the-clock service, reducing wait times and improving customer engagement.
- Proactive Issue Resolution – AI detects sentiment, predicts problems, and helps businesses resolve issues before they escalate.
- Enhanced Performance Management – AI analytics track key metrics like response times and satisfaction rates, helping optimize support strategies.
- Reduced Call Volume – AI-driven self-service options minimize unnecessary calls, allowing agents to focus on complex issues.
- Multi-Language Support – AI facilitates global customer support by translating conversations and responding in multiple languages.
Top 7 Ways to Revamp your Call Center Customer Services using AI
Providing quick, efficient, and customized assistance across each user engagement is becoming increasingly crucial as customer expectations increase. Here are the 7 ways to revamp your call center customer services with the help of AI:
- Chatbots and Virtual Assistants
AI-powered chatbots and virtual assistants improve the customer service experience by offering real-time services and user support. By answering user queries, these virtual assistants guarantee prompt replies and free up human customer support agents to work on more complicated problems.
They make customer service available at all times and anywhere thereby creating a seamless and effective user engagement. Social media chatbots are a perfect example of how technology is revolutionizing communication channels by enabling businesses to connect with customers on platforms they frequently use. A Gartner report predicts that by 2027, chatbots will be the primary customer service channel for almost a quarter of organizations.
Real-life example: H&M Chatbot
H&M’s ‘KiK’ chatbot offers quick answers to frequently asked questions related to order tracking, refunds, and delay in shipments. It also provides fashion advice and recommendations to its users. The chatbot employs natural language processing (NLP) to interpret the user’s requests and deliver customized style suggestions.
- Content Generation
As per a Gartner report, 80% of customer service and support companies will use generative AI to enhance the customer experience. By incorporating generative AI consulting services into customers, businesses can effectively address user questions and produce logical, and contextually relevant answers. They can provide accurate responses to intricate requests from customers that include reasons, solutions to the problem, and even personalized replies.
Real-life example: Agent Assist
Google’s Agent Assist AI solution offers customer service professionals in-the-moment support, automated replies, and real-time coaching that allows them to address user concerns quickly and correctly. Recent improvements include generative knowledge assistance, coaching techniques, summarization, intelligent responses, and live translation.
(1823) Introducing Cloud Contact Center AI’s Agent Assist for Chat – YouTube
- Intelligent routing systems
Intelligent routing is an AI technology that is used by call centers to collect customer queries via company websites, social media, or voice channels and route it to the customer support agent.
In contrast to the typical routing algorithms, which use a basic sequential method, intelligent routing analyses customer information based on call history, user profile, and the context of the communication and then routes the query to the best- fit customer service agent.
NICE claims that AI-driven routing improves customer satisfaction ratings (CSAT) while reducing average handle time (AHT).
Real-life example: Convin’s AI call center software
In Convin’s call center software, the automated call distributors (ACDs), assist in directing to the most appropriate agent or department based on factors like availability, skill level, or IVR (Interactive voice response) choices.
- Self-Service AI tools
As per, 2022 Digital-First Customer Experience Report, 81% of customers prefer self-service options, rather than speaking to support agents. AI-based self-service tools in call centers use conversational AI techniques to provide rapid responses to customers via chat, text, or a voice channel. Customers receive the assistance they require independently through self-service automation cutting down on the wait times.
Real-life example: HelpShift self-service support
HelpShift provides tools for implementing self-service assistance for clients in customer service operations. From AI agents to QuicKSearchbots, their simple technologies help companies rapidly build customer care assistance.
- AI-based Predictive analytics tools
AI-powered predictive analytics systems in customer services enable companies to predict client requests and provide individualized solutions before customers even ask for them. These tools, often developed and fine-tuned by an AI machine learning engineer, analyze customer data, demographics, behavior patterns, and past purchases or requests to forecast future queries.
Real-life example: Netflix uses AI-based predictive analytics tools for personalized recommendations
Netflix is an entirely data-driven company, from the programs it creates to the movies and shows it promotes. It collects massive amounts of data from each user, which it then feeds into AI-powered systems to forecast what the users might want to see next based on their previous watchlist, likes, ratings, and trending patterns.
- Sentiment Analysis tools
Call centers utilize sentiment analysis to interpret human voice or text and identify it as neutral, positive, or negative. Modern AI techniques like ML (Machine Learning), and NLP (Natural Language Processing) are used for this purpose.
Sentiment analysis gives call center companies the ability to learn how consumers feel about their current range of products, solutions, and services, what enhancements they want to see, and how to best provide them.
Here’s an example of the AI-based sentiment analysis,
Real-life example: Amazon
Amazon, one of the biggest online merchants, analyzes product evaluations using AI sentiment analysis known as ‘Amazon Comprehend’. To improve the purchasing experience of the customers and boost users’ trust, Amazon classifies reviews and suggestions ad positive, negative, or neutral and further prioritizes them to improve its services.
- Interactive Voice Response (IVR) services
The typical menu-driven call interactions may be transformed into conversational interactions with interactive voice response (IVR) solutions, which can effectively route and handle customer issues.
By using natural language processing, IVR tools can comprehend unstructured human language, enabling callers to express their requests without having to go through inflexible menus. In addition to leveraging speech biometrics for user authentication, these conversational technologies may immediately fix customer issues without the need for a customer support agent.
Here’s a case study to show how an IVR system of a bank responds
Real-life example: Delta Airlines
From making travel arrangements to getting on the plane, Delta wants every passenger to feel comfortable and cared for. The IVR at Delta Airlines recognizes the phone numbers of the callers and addresses Skymiles members by their first names. The technology offers customized details about future itineraries and proactively notifies users of flight cancellations, delays in flights, and upgrades.
Best practices to know while implementing AI in customer service call centers
88% of marketers believe that businesses need to improve the usage of automation and AI to satisfy client expectations and remain competitive. Thus, implementing AI successfully necessitates meticulous planning and application.
The following five recommended practices promise a seamless transition and optimize AI’s advantage in call centers.
- Train your workforce
As you integrate AI into your call center company, explaining and training the existing and new employees about the new skill like generative AI is a must. Encourage your staff to learn these advanced AI skills and help them understand how new technologies can enable them to do more while emphasizing their human talents.
- Identify KPIs
Clearly defining your call center’s key performance indicators (KPIs) is crucial before investing in any advanced AI technology. Identify and define your objectives, whether you want to enhance first-call customer service response rates, minimize wait times, or personalize customer interactions.
- Manage privacy and reliability concerns
Concerns may exist over how accurately AI systems can comprehend and respond to complex and sensitive customer queries or handle private data. Before implementing any AI technology for your call center, understand in detail about the data usage and security policies of advanced AI techniques.
- Integrate with the existing platform
Implementing AI successfully requires a smooth and seamless integration with your existing call center platform. Make sure the LLM (Large language model) you choose aligns perfectly with your requirements and AI strategies. For example, use Machine Language (ML) to extract insights from massive databases and use Natural Language Processing (NLP) to analyze text data such as in surveys. Additionally, leveraging an email list integrated with AI tools can help personalize customer interactions, automate responses, and provide targeted follow-ups, enhancing engagement and driving higher conversion rates.
Will AI replace Customer Support Human Agents?
No, Absolutely not!
“ AI agents are set to revolutionize the workforce, blending human creativity with machine efficiency to unlock unprecedented levels of productivity and innovation”
-Anthony Abbatiello [PwC workforce Transformation Practice Leader]
Artificial Intelligence (AI) is here to improve and revolutionize the customer services of the call center. Speed and efficiency are important to customers, but they also want someone who understands and connects with them empathetically, which AI can’t always provide.
Thus, a transformed AI call center may enhance human agents’ capabilities in the future and alter the requirements of customer service jobs, but human interaction will always be crucial to building long-term customer relationships.
So, are you planning to upgrade customer services at your call center with the latest AI and other trending technologies? Contact us.
At Payline, we provide solutions and technologies that lead the industry to enable incredible payment experiences. Businesses of all sizes and in all industries may choose from our omnichannel solutions, which can be customized to meet your specific requirements.
About the Author:
Joy D’Cruz is a content marketing specialist currently working with SaSHunt. Joy has a keen interest in researching topics related to B2B and SaaS. He has created copy for a wide range of marketing and business topics including social media, email marketing, and career development. During weekends, he likes spending time watching YouTube.
