AI in customer service is automating repetitive tasks and freeing agents up to focus on more complex issues. Furthermore, virtual assistants and chatbots offer innovative new solutions for customers.
Next-gen customer service leverages AI, technology, and data to revolutionise customer experiences – with several companies already using it to achieve that end.
Companies are turning to AI tools due to their ability to reduce costs while improving customer service speed and quality. AI-powered tools like facial and voice recognition as well as interactive voice response can answer calls, understand vocal replies and complete tasks such as routing them to the correct agent or department.
Customers expect faster and more convenient support services from businesses, and AI can help businesses meet them. Conversational AI can detect a customer’s native language and automatically translate their question, eliminating the need for human translators while saving both time and money.
Chatbots can respond automatically to simple customer requests while routing more complex ones through to an agent for response. This enhances customer satisfaction while decreasing first responder time.
Predictive analytics is the cornerstone of machine learning techniques such as predictive analytics. This machine learning technique attempts to forecast future events based on historical data and statistics, such as computer vision. Computer vision analyzes video media for patterns that indicate changes in action (for instance, bee swarm detection through accelerometer signals). You can see predictive analytics at work in photo search algorithms, facial recognition apps and smartphones’ ability to group images together based on similar characteristics.
Predictive analytics can create customer loyalty by using customer data to anticipate the next steps in their journey, helping brands meet needs before customers even realize there are any. Target was an early adopter of predictive analytics when they used it to recognize buying patterns of women and market baby products specifically to them.
Predictive analytics can also reduce customer support calls by anticipating peak calling periods and routing them to agents familiar with resolving those issues, so as not to waste both time and resources. By eliminating frustrated customers from making additional attempts at getting help, predictive analytics helps save both time and resources by eliminating wasted calls to support.
Agent Assist Technology
Agent assist technology combines real-time customer conversations with information from previously resolved cases to generate actionable insights for agents to provide better resolutions and save time during conversations. In doing so, it also reduces agent workload significantly and saves them time when discussing matters directly with customers.
AI models use ASR to convert speech into text and analyze its context and identify any major themes being discussed on each call, which enables it to automatically complete tasks such as displaying charts on an agent’s screen to help them better understand customers and suggest solutions.
Information collected is then fed into generative AI, which analyzes customer interactions to provide agents with personalized recommendations for them to make during interactions. Studies have demonstrated this strategy’s ability to shorten agent response times, increase first call resolution rates and decrease escalations rates to supervisors, as well as provide personalized experiences during customer interactions and improve CSAT scores overall. Arming your agents with this intelligence allows them to provide a superior customer experience every time a customer contacts them.
AI tools can create personalized customer experiences by drawing upon data about customers and their behaviors. Furthermore, these AI tools can further optimize and expand this personalization process by using machine learning algorithms to detect patterns within this data.
Consumers and businesses now have access to an array of AI services–from voice assistants like Siri and Alexa, chatbots, virtual assistants on smartphones, and content recommendations found within search engines. In time, these systems may become even more advanced; potentially creating personalized experiences tailored to you as an individual.
While AI offers numerous opportunities to improve customer service, companies must remain mindful of privacy concerns and use technology responsibly and ethically if they want to gain the advantage in today’s competitive marketplace. More than 70% of consumers now expect personalized experiences from brands they engage with.