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AI implementations–from emotional AI to conversational automation–are among the most exciting and useful customer service tools available today. With more businesses investing in digital initiatives in the wake of the global pandemic, demand for AI tools is on the rise. However, the best AI implementation is only as good as the strategy behind it. To create a truly effective digital experience, businesses must first identify the customer service AI use cases they want to target.
Let’s get into the top customer service AI use cases and what they can do for your business.
Top Tier AI Use Cases
The following AI implementations tend to have the biggest and fastest returns and are relatively easy to roll out. They cover multiple areas and address overarching customer service for a smoother experience, and they are documented to improve customer satisfaction across industries.
Speech analytics for customer sentiment/intent Speech analytics tools comb customers’ speech for relevant data that can aid in call resolution. Powered by conversational AI, speech analytics can identify friction points, customer intent and opportunities for real-time assistance to deliver exceptional customer experience.
Human-in-the-loop (HITL) intent learning HITL processes allow human confirmation of machine learning in a continuous loop to optimize outcomes. By continually updating machine capabilities with human input, businesses can refine their AI tools for optimal performance.
Workforce scheduling Workforce scheduling tools collect personal scheduling information, drawing on historical data to create optimal schedules, reducing employee workload and eliminating the cumbersome back-and-forth that limits productivity.
Predicting customer lifetime value Among the newer, most promising customer service AI use cases is predicting lifetime value. Artificial intelligence is tasked with calculating the potential of the customer to spend more, targeting those customers who are likely to produce more value for your business.
Identifying customer emotion Identifying customer emotion is another exciting, new customer service AI use case. Advances in emotional AI make it possible to identify and interpret sentiment in real-time and adjust a customer’s journey accordingly, injecting empathy--or escalating to a live agent--as needed.
Identifying Next-Best Actions (Customer Journey Analytics) Predictive analytics, when well implemented, can track customer behavior and journeys. This is a particularly useful AI use case, as machine tracking of customers and their buying strategies can produce highly accurate next-best actions during real-time interactions.
Second Tier AI Use Cases
These customer service AI use cases tend to be more specialized, targeting precision-based gains based on organizational needs. Businesses prioritizing information security and customer-centric personalization in particular can see significant ROI with these AI applications.
Voice biometrics for verifying agents Voice biometrics identify agents through their unique “voiceprint”, ensuring speaker authenticity during calls. This is a particularly compelling AI use case for remote workers and contact centers that handle sensitive or highly personal information.
Visual product search (Customer Sales) An image-based search engine like Pinterest, Google, and Amazon uses visual search results to suggest related options to customers. Artificial Intelligence ensures that each customer is receiving thematically relevant content, drawing them back for further business.
Offer personalization As more organizations adopt a customer-centric business strategy, offer personalization will become an increasingly attractive customer service AI use case. This AI implementation tailors interactions based on a customer’s past behavior and predictive data, allowing for highly targeted cross-selling and creating a unique experience that strengthens customer loyalty and likelihood to spend.
Conversational self-service (AI-powered customer assistants) According to Gartner, 70 percent of customers attempt self-service during their resolution journey; however, only 9 percent solve their issue through self-service alone. Given the appetite for self-service, AI-powered customer assistants--from chatbots to automated callers--are growing in popularity. This is an especially appealing AI use case for contact centers facing higher traffic with fewer agents.
Protecting personally identifiable information (PII) In the era of high-profile data breaches, more companies are doubling down on digital security. AI can help contact centers protect personally identifiable information (PII) during interactions, strengthening compliance and customer confidence.
Post-call summary analytics By automating time-consuming post-call work, employees can continue assisting customers in their call queue. This makes a powerful AI use case for organizations looking to reduce wait times and manual agent errors.
Third Tier AI Use Cases
Customer service AI use cases at this level are much more granular and are designed to focus on areas of business optimization.
Customer segmentation Using AI, organizations can group customers based on related similarities. This AI use case focuses on more effective customer targeting and journey personalization, allowing for greater precision in marketing and sales.
Real-time agent coaching This highly useful AI implementation allows contact center leaders to coach agents when they need assistance the most--during live interactions. This is a particularly valuable AI use case for improving first contact resolution (FCR), average handle time (AHT) and other employee metrics.
Agent onboarding assistance By automating time-consuming onboarding tasks--particularly knowledge base comprehension and retention--contact centers can get new agents up to speed and on the phones faster.
Hyperautomation Hyperautomation involves the rapid automation of as many IT approaches as possible. AI accelerates and streamlines this process, allowing customer service to operate with greater speed and efficiency.
Fourth Tier AI Use Cases
Fourth tier AI use cases are highly detailed and are designed to drive incremental increases in operational efficiency.
Chatbot Knowledge Graphs Chatbots can only be as effective as their information base, and implemented AI knowledge graphs can supplement actionable changes for chatbots, improving customer satisfaction and increasing usability.
Contact Routing Intelligent contact routing uses AI to automatically direct customers to designated representatives based on their queries. This time-saving AI use case is especially beneficial for contact centers with multiple departments and/or customer service options.
Interested in learning more? Reach out to Uniphore today.