From conversational automation to emotional AI, these are the most commonly available customer care service tools available today. With businesses going digital at the onset of the pandemic situation, the nature of the customer experience has been changing along with the sudden increase in customer expectations towards it.
Hence, the use of AI, along with machine learning and robotic process automation, has been prevalent among call center service providers to stay ahead of the competition by fulfilling customer expectations. A truly effective digital experience can only be created whenever a business can identify the AI use cases in customer service. In this blog, we are going to point out the most popular AI use cases in customer service and how businesses are going to implement them.
Use Cases of AI in Customer Service
Below are the most trending AI implementations that tend to have the fastest and biggest returns and are quite easy to roll out. It covers multiple facets of customer service and addresses most customer issues, while also being known for offering a richer customer experience.
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Speech Analytics
Speech analytics is intended to understand customer sentiment and intent. The tools comb the customers’ speech to collect relevant data that aids in call resolution. Enabled by AI, speech analytics are used for identifying customer intent, and friction points, and delivering an excellent customer experience while providing real-time assistance.
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Human in the Loop Learning
Human-in-the-loop intent learning (HITL) in AI allows the human confirmation of machine learning for optimizing outcomes in a continuous loop. By continually updating the capabilities of machines along with human input, companies can refine AI-enabled systems for optimal performance.
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Predicting Customer Lifetime Value
One of the most promising use cases of AI in the realm of customer service is predicting customer lifetime value, which helps increase sales and customer experience. In this case, AI is tasked with calculating the purchasing behavior of the customers. It identifies the consumers who are willing to pay more for your products and the customer experience provided by your company.
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Finding Customer Journey Analytics
One of the most popular use cases of AI in customer service is the use of predictive analytics for identifying the next-best actions of customers. When predictive analytics is implemented properly, it can easily track customer journeys and their behavior. It is done very accurately by AI because the systems are highly accurate in tracking buying strategies and next best actions based on real-time interactions.
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Visual Product Search
Visual product search is a use case of AI that is used by most image-based search engines like Google, Interest, Amazon, etc. that use visual search results to suggest related product recommendations and opinions to consumers. Artificial intelligence (AI) also ensures that customers are getting relevant content from the company so that it draws them towards the company.
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Personalized Customer Service
Most call center agencies are adopting customer-centric business strategies to fulfill their expectations. And offering personalized customer service will be a great way to attract customers, which is becoming the most trending use case of AI in the world of customer service. AI-enabled systems can tailor the interactions based on their predictive data and past behaviors while allowing highly targeted cross-selling by creating unique experiences that nurture customers’ likelihood to spend more and their loyalty toward the brand.
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Conversational Self-Service
More than 70% of the customers prefer self-service during their issue-resolution period; however, 9% tend to solve their issues completely through self-service. Given the need for self-service, AI-enabled customer assistants, starting from automated callers to chatbots, are growing immensely popular for serving faster customer service. It is helpful for call center agencies when they face higher traffic in customer support services and have very few agents to handle the situation.
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Hyper Automation
Hyper automation is the byproduct of using machine learning, robotic process automation, and Artificial Intelligence. The process of hyper-automation involves the rapid automation of many business processes, including customer service. AI helps in streamlining and accelerating the process that allows customer service to operate with higher efficiency and speed. Hyper automation in customer support helps in the faster resolution of customer issues.
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Real-Time Agent Assistance
Agent assistance is very important in terms of onboarding them, as it requires a lot of time to complete the whole process. AI helps automate the process of agent onboarding. It automates the retention of the call center agencies and the knowledge base comprehension that gets new customer support agents, speeding up their operating procedures with higher efficiency.
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Contact Routing
Intelligent contact routing is one of the best use cases of AI in customer service. It is used to direct customers to the designated support agents automatically based on the nature of the queries. This saves time and is beneficial for call center agencies with multiple customer support departments or a plethora of customer experience options.
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Chatbot Knowledge Graphs
Chatbot’s knowledge graph is the most important aspect of live chat support services. The information and data present in the chatbots and the AI integration can supplement the actionable insights for the chatbots. It not only leads to a faster response to customers’ queries but also improves customer satisfaction while increasing usability.
CONCLUSION
If you are looking to provide next-level customer service, AI can be integrated to get more precise, targeted, and specific results based on customer needs. Call center service providers that are focused on prioritizing information security and personalized customer experiences can easily witness a significant increase in ROI. Trupp Global is a reliable customer care services company known for using next-gen technologies to provide exemplary customer service. Omnichannel platforms, along with chatbots, are used to offer a faster response to customers, which turns into customer delight in the long run.
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