How Can Using AI in Customer Service Help Your Brand?
AI (Artificial Intelligence) in customer service is making a fundamental difference to businesses. It’s saving companies time and money by improving engagement and the customer relationship, which in turn enhances customer loyalty and brand reputation. An added benefit is that staff retention can also be impacted because the AI can reduce burden, help them manage tickets more efficiently and allow them to focus on the customers that really need them. Sixty-five percent of employees reported feeling optimistic, excited and grateful about having AI bot “co-workers”.
Strategic AI can support your CS teams by customising interactions, intelligently routing conversations, reducing wait times, and improving customer self-service. While the technology is still evolving almost daily, there is already endless potential for improving customer engagement with AI, whatever your industry.
What Does AI in Customer Service Look Like in 2021?
The best AI customer service is omnipresent 24/7 across multiple channels. It handles more customer queries in less time and offers an ultra-personalised experience. Each time you interact with a chatbot, that’s AI. Recommending products based on a customer’s purchase history is also AI customer service. In fact, the very best AI is now evolving to be less bot like and more humanoid so its possible that many customers are not even aware that they are interacting with a bot in a number of instances.
AI technology instantly responds to customer requests in real-time, often rendering human involvement unnecessary and so reducing burden and demand on service teams. Context-aware AI sifts through complex data and knowledge-base articles, analyses the customer’s association with the brand, and interprets their query. All of this takes place within seconds. These low turnaround times result in high Customer Satisfaction (CSAT) scores. CSAT is the most straightforward way of measuring how satisfied a customer is with a particular interaction or overall experience. Fast resolutions also give a better perception of the brand’s ability to handle future issues and reduce churn. For example, 90% of customers claim an “immediate” response is important.
AI customer service allows you to be both reactive and proactive. By harnessing the power of machine learning, you can recognise patterns. There’s no need to wait for your customers to come to you. Instead, data analytics gauge which customers are likely to contact you. They can also mine large volumes of data to determine when and why they will need to contact customer support. In this way, AI can help you accurately predict potential interactions to prepare adequate self-service resources or create guidelines for the customer support team.
AI provides a good overview of a customer’s behaviour and helps direct them to the best channel (usually digital for simple enquiries). Human agents are then able to focus on helping customers with more complex problems. What is more, AI can be used to more efficiently route tickets to the most qualified agents for specific enquiries, further enhancing their customer experience as well as making the CS team more efficient.
The Benefits of AI in Customer Service
Integrating AI into customer service can dramatically improve CX (Customer Experience). It helps identify customer pain points, automates processes, speeds up decision-making, and optimises service delivery. An AI-powered customer relationship platform (CRM) will transform your customer experience in the following ways.
AI Saves Time
At its most basic level, AI assists with workload management. It saves customer service agents time by automating internal workflows and repetitive tasks. Pattern recognition provides agents with canned responses to various questions. Manually building mailing lists and updating Excel spreadsheets is time-consuming and presents security risks and best practice use of AI can alleviate the need for them.
Automated responses also save customers’ time. According to McKinsey, three-quarters of online customers expect support within five minutes of requesting help, though in reality, few people want to wait even that long for a response. According to HubSpot, two-thirds of customers find waiting on hold or having to repeat themselves is the most frustrating thing about customer service. Chatbots can save, track and transfer entire chat histories, so can prevent the frustration of customers having to repeat their query to different CS reps.
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AI Identifies Customer Concerns
AI empowers customers to help themselves via self-service options, which is a huge advantage. Gartner reported that by 2022, nearly 85% of support interactions will start with self-service. It can use context in searches and conversations to detect intent and predict responses. Well-constructed AI systems are programmed to suggest the next best actions for both customers and agents. Conversational AI capabilities enable either text or voice-based chatbots and virtual assistants. These can either assist an employee using knowledge or automation, or capture demand for human-based help or service provision. Amazon Lex is an example of a sophisticated bot that uses advanced functunality to recognise the intent in speech and text. It only hands over to a human after it has engaged with the customer, established the issue and tried to resolve it using responses, knowledge content, and other resources.
AI tracks and processes large volumes of data which help identify and solve complicated issues. Data analysis helps your CRM system to continuously learn the most common issues your customers face and find solutions to help them. For example, AI notices if customers are inactive on a page for a while, prompting chatbots to start a conversation. At call centres, AI listens to the content and tone of real-time conversations to gauge the customer’s potential emotional state. The health insurance company Humana reported a 28% increase in customer satisfaction when using voice analytics tracking. The AI only needs a few phrases to keep learning and evolving so the responses get better over time.
AI Customises Experiences and Products
Companies are always looking for more ways to personalise customer experience. Giving customers more of what they want, on time, is the key to customer retention. Well-constructed data and AI sytems allow companies to build unique profiles of their users to create tailored content based on preferences, geo-localisation, previous purchases, and other insights. This allows companies to suggest relevant products/services or offer targeted discounts. AI can recognise if it’s a customer’s first time on the website and offer a more detailed explanation of its services. On the other hand, repeat visitors can expect to see images for previously purchased or recommended products, be recognised and greeted by the bot and potentially see smart content on the site delivered to them based on their history.
AI Makes Data and Feedback More Accessible
Although companies have always been able to collect data on customers, AI makes it easier. Before automation, data collection was laborious and unreliable. Now CRMs manage multiple brands and products. They can quickly convert data into segmented reports without the risk of human error. AI lets you seamlessly integrate multiple channels – phone, web, chat, social media – in a single interface, to deliver a single point of truth and a single reference that supports the delivery of best practice customer service regardless of the source. Companies can use feedback from internal touchpoints and external social channels to gain a 360-degree view of the customer journey. This helps them intervene for service recovery, retain customers and promote loyalty.
AI also makes the customer feedback process more actionable. Machine learning tools assess and categorise the feedback as positive, negative, or neutral. It can analyse texts to pull out recurring feedback and keywords to get to the root of the customers’ pain points. It provides real-time insights to compare your feedback with competitors’ product reviews. It helps achieve a better Net Promoter Score (NPS) – NPS is a single question survey used to measure the loyalty of customers. It’s worth noting that a superior experience increases customer loyalty and that a customer that is a brand promoter has a customer lifetime value that’s 6-14 times higher than that of a brand detractor. It can also be used to effectively address the negative experiences of unhappy customers and turn around how they feel about a product.
The Challenges of AI in Customer Service
Security and privacy are the biggest concerns with AI. While many customers are willing to share a certain amount of personal data in exchange for the convenience of tailored customer support, the customer is also more aware than ever of how data is used and how they can protect themselves by withholding it. As a result, companies need to be clear about why they collect data, what it is used for and also ensure an ethical data policy is not only developed but implemented and lived. Building trust and transparency around all guidelines and policies on privacy and data ownership is key, especially as AI can be viewed with mistrust.
Automation Is the Future of Customer Service
Customer service excellence is a long-term business strategy. AI in customer service will soon be essential for all successful businesses because customers’ expections have been set by companies already using these capabilities. Improving self-service functionality is the current priority for most companies. This is reflected in ‘The Service Desk: 2021 and Beyond’ report where almost half of all respondents reported that chatbots and virtual agents would grow in demand and a further 42% cited self-service as a significant priority for the next few years.
Customers want to solve their issues via updated knowledge bases, chatbots and other self-service tools. When they can’t, they resort to customer service calls, which significantly increases operational costs. When they can’t solve their problem with self-service, they resort to customer service calls. Gartner reported that using live channels such as chat, phone and email, significantly increases operational costs by up to 80 times the amount of self-service costs.
So, it seems that the correct blend of sensitive and nuanced AI and human contact is the key to delivering a seamless customer experience. While one blend may work for one audience, it may not be transferable to a different audience. Companies need to work with their customers, using data and other insight to deliver the CS solution that meets their needs most effectively.
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