The use of artificial intelligence in customer support
Artificial intelligence (AI) is intelligence that is created and demonstrated by machines and computers, not by the human brain. AI comes in many shapes and sizes. There are usually two types of AI: Narrow AI and General AI. We encounter Narrow AI in computers and smartphones in our daily lives. Such intelligent systems perform specific tasks without the need to be programmed. The most common examples of narrow AI are speech and voice recognition systems such as Siri or Alexa, vision recognition systems in self-driving cars, medical AI that recognizes MRI results, etc. General AI is something we see more often in movies, the type of artificial intelligence that may learn on its own to do the different tasks humans do. Narrow AI has broader applications in customer service. It supports clients by guiding them and answering any questions or requests along the way. In addition, it is used in customer support chatbots, customer self-service, machine learning for customer data analysis, natural language processing to provide voice recognition and many other procedures.
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The impact of AI on customer support
AI is an excellent tool for most support teams to deliver the perfect customer experience. Chatbots perform various actions, from reminding shoppers to return to their cart to complete an order to collecting feedback. AI in customer service means being available 24/7 around the world in different languages, attracting new customers, and increasing their satisfaction level. Artificial intelligence also works alongside support agents, replacing them with routine tasks and allowing them to focus on more complex issues. AI-based solutions such as chatbots easily identify voice triggers and provide relevant data and recommendations without human intervention. Another option to introduce AI into customer support is data collection and analysis. When communicating with customers, a vast amount of data is created. It can provide valuable insights into customer behavior, preferences, churn rates, and more. Thanks to AI, you don’t have to analyze data and draw conclusions based on it manually. AI also provides a comprehensive view of customer interaction and conversational intelligence.
Examples of AI in customer service
Advances in artificial intelligence continue to pave the way for greater efficiency throughout the organization, especially in customer service. Different technologies are suitable for disorganization, but in any case, AI plays a central role in the future of customer service. We have collected examples of the future of AI in the field of customer service.- Chatbots: one of the most popular use cases for AI in customer service is chatbots. Companies successfully use bots of varying complexity to solve routine problems, including delivery dates, debts, order status, etc. By relaying these frequently asked questions to a chatbot, customer service agents can help more people and improve the overall experience while cutting operating costs for the company.
- Agent consultation: in many of today’s multichannel contact centers, agent assistance technology uses artificial intelligence to automatically understand what the customer is asking, search for knowledge base material, and display it on the help desk agent’s screen during a call. This process will save agent and client time, reduce the average turnaround time, and cut costs.
- Self-service means that customers can identify and find the support they need without the help of an agent. If given the opportunity, most clients would prefer to solve problems independently if given the proper tools and data. As AI becomes more and more advanced, self-service features will become more common and allow customers to solve problems according to their schedules.
- Machine learning is the key to processing and analyzing large data streams and determining what valuable insights there are. In customer service, machine learning helps agents identify common questions and answers with predictive analytics. This technology can even pick up what the agent may have missed when communicating. In addition, machine learning can be used to help bots and other AI tools adapt to a specific situation based on previous results.
AI customer service best practices
These days, companies that know their customers well enough and understand how to meet their needs and lifestyles are in the lead. As artificial intelligence (AI) is evolving at a phenomenal pace, there are many ways to use it to learn more about their clients and ensure the support they need. If you want to get the most out of modern technologies, there are several essential points to consider when implementing AI-based solutions, which will be discussed below.Don’t forget to research
When it comes to using AI in customer service, research is the most critical step. You need to analyze some questions and use the answers to test any potential platforms:- What channels do your buyers prefer to utilize in customer support? (SMS, Facebook Messenger, or other social networking or phone conversations).
- What are your clients’ main pain points, and how can AI customer support help solve them?
- What are the critical weaknesses of current customer service? Are your agents struggling with specific customer requests, or is your contact center suffering from high turnover?
Don’t ignore customer reviews
Your customers are your main assets. Make sure you always consider customer feedback when making contact center decisions. Customer reviews are a direct representation of the user experience. Perhaps they are interested in self-service? Do they prefer to interact through one channel rather than another? One easy way to start collecting feedback is with a Customer Satisfaction Survey (CSAT).Personalize the experience across different channels
We live in the age of personalization. Personalization is the trump card in customer service. Customers expect their conversations to be automated, and we understand customer needs without having them repeat themselves every time they talk to another agent. It’s not enough to have real-time customer data — you need to be able to use it and make it available to everyone in your contact center.Conduct monthly or quarterly performance reviews
Nothing ever stays the same forever. So make sure you constantly re-evaluate your customer service processes. The best way to do this is to schedule periodic performance reviews. You can keep abreast of what is going well and not and then make the necessary changes based on the available data. Evaluate your business before and after automation. Analyze how your team rated before implementing AI in customer service and how you were rated after using it for some time?Risks of using AI in customer service
Organizations are increasingly looking for ways to use AI customer support to increase productivity and profitability and improve business results. Despite the many business benefits of artificial intelligence, there are also specific barriers and disadvantages to be aware of.- One of the main barriers to AI adoption is the availability of data. Data is often slide or inconsistent and of poor quality, posing challenges for companies seeking to create value with AI at scale. To overcome this, you must have a clear strategy to find data that suits your AI from the beginning.
- Another critical constraint to AI adoption is the lack of skills and the availability of technical staff with the experience and training necessary to operate AI solutions effectively.
- When buying AI technologies, do not forget about their cost. Companies that lack in-house skills or are unfamiliar with AI often turn to outsource, at which point cost and maintenance issues arise.
Automate 84% of user questions
AI Engine can transform your data into knowledge, and answer any question your users asks, complexity automatically