AI in customer service: Everything you need to know

Artificial intelligence (AI) in customer service isn’t just a concept on the horizon or a future investment strategy. It is already here and shaping the way many companies work. A recent study conducted by SalesForce found that 83% of businesses are either investing or planning to invest in AI technology to enhance this crucial part of their operations. 

With AI engines, machine learning and Big Data at the forefront, companies are revolutionizing how they connect with customers, but this is only the beginning.

How AI is transforming customer service

Until recently, AI in customer care was mostly limited to handling simple, repetitive automated tasks, such as answering frequently asked questions or providing basic information. This narrow focus meant that its usefulness for businesses was somewhat limited. However, with recent advancements, AI is transforming everything we know about customer service. 

On the one hand, it has stepped up in the analysis of customer behaviors. AI can now analyze complex behavioral patterns, as well as identify trends more quickly, which leads to predicting customer needs or problems more accurately. This enables companies to anticipate any issues and to offer more proactive solutions.

On the one hand, AI has made significant strides in analyzing customer behavior, boosting productivity. Thanks to automation and AI-based support tools, businesses can now process complex patterns and agents can solve problems faster and more accurately, and in consequence have more time to deal with difficult cases. 

These tools can analyze customer previous engagements with the business, suggest solutions based on similar cases, and provide relevant information in real time. As a result, agents can provide more accurate and personalized solutions, improving both customer satisfaction and productivity.

AI Customer Support Tools & Software

Here are some of the most popular AI-driven tools that are transforming customer service:

• Proactive problem management: by integrating with customer data sources, these tools use AI to analyze customer behavior and preferences, enabling companies to address problems before they arise.
• AI agent assistants: these tools provide employees with real-time information and natural language recommendations, suggesting effective solutions quickly and efficiently.
• Ticket automation: AI systems generate virtual tickets to resolve issues without human intervention, executing corrective actions that reduce the workload for front-line agents.
• Real-time monitoring: this tool allows companies to track purchased services and detect issues before they impact the customer experience. For instance, in network services, AI identifies drops in quality or transmission interruptions to apply automatic corrections and notify the support team.

An exemplary tool in this domain is AI Care NOW by Tupl. This solution reduces workload by swiftly identifying and resolving customer issues through integration with network and subscriber data. It determines root causes and provides natural language recommendations to support agents and network engineers. The AI engine automates detection, troubleshooting, and action recommendations by correlating data from multiple sources.

Benefits & Impact of AI in Customer Service

• Knowledge centralization: AI enables the centralization of information and the generation of new insights from dispersed data, supporting better decision-making, consistent responses, and the development of more effective strategies.
• Reduced response time: automation, as well the analysis of real-time data, allows agents to resolve customer queries faster, shortening user waiting times.
• First call or visit resolution: AI provides customer service agents with immediate access to relevant and accurate information, increasing FCR (First Call Resolution) rate.
• Decreased number of tickets: AI's ability to proactively anticipate and resolve issues, as well as provide fast and accurate responses, can reduce the number of customer calls and emails by up to 90%.
• Improved NPS: implementing AI in customer service can significantly improve NPS (Net Promoter Score). By providing faster, more accurate and personalized responses, customer satisfaction improves.

Examples of AI in Real Customer Service Scenarios

AI in customer care can often be the deciding factor between a smooth, satisfying experience and a frustrating one. Here are some real-world examples:

• Network maintenance: a telecommunications company leverages AI to continuously monitor network performance. The system automatically detects issues like traffic congestion or equipment failures and, in many cases, resolves them without the need for human intervention.
• Coverage problems: if a customer reports coverage problems in their area AI can quickly analyze network data, geographic conditions and previous similar incidents. Based on this information, it can suggest solutions to the customer service agent.
• Troubleshooting common issues: AI systems can automatically diagnose and resolve issues like network latency, connection problems, or device configuration errors. These systems can guide users through solutions or, in many cases, apply fixes remotely without human intervention.

In summary, AI in customer care is transforming the industry by improving efficiency, personalization, and response times, all while enhancing customer satisfaction and strengthening brand reputation. As AI systems continue to advance, we can look forward to even greater capabilities and improvements in customer care, leading to smoother interactions, proactive solutions, and increased customer loyalty.