Leveraging AI in Customer Service: Maximizing Potential and Overcoming Challenges
Overall, the technology is extremely useful and can strategically align a business to become more competitive within its industry. However, the challenge lies in the implementation. Many use cases do not fully utilize the benefits of AI, resulting in a negative user experience for end customers who need support.
Our primary role is to adopt new tech and develop Proof of Concept (POC) projects for the community to visualize and build use cases from. I've personally experienced AI in the customer service area. Where it should be an awesome experience, it often is not. This is due to the platform's implementation, which follows outdated structures.
Take customer support, for instance. When a customer needs help, they are taken to a chat window where a chatbot pops up and asks, "How may I help you?" The user describes their issue, but then they are prompted to select a category and sub-category. Most users struggle to find the appropriate category, leading to frustration. Often, they abandon the chat or select any option just to reach a live agent. This inefficient process stems from basing AI implementation on traditional telephone support structures, which are not suited for AI.
Current AI Limitations:
For example, "press 2 for billing enquiry" and similar prompts were useful for reporting and incident management, but these methods are ineffective when adopting AI. AI should categorize issues automatically, eliminating the need for rigid categories.
When customers can't find the right category, they either give up or choose a random one just to reach a human agent. This approach not only frustrates customers but also defeats the purpose of implementing AI in the first place. The ultimate goal should be to enhance the customer experience, not hinder it.
The Potential of AI:
AI has immense potential and capabilities. It can learn from interactions, identify patterns, and provide solutions without human intervention. With the right implementation, AI can drastically reduce response times and improve customer satisfaction.
Proposed Solutions:
1. Intelligent Categorization: Instead of forcing customers to choose categories, AI should analyze their queries and categorize issues automatically. This not only streamlines the process but also ensures that customers are directed to the right resource quickly.
2. Personalization: AI can use past interactions to personalize responses and anticipate customer needs, creating a more seamless experience.
3. Feedback Loops: Regularly gather and analyze customer feedback to continuously improve the AI system. This ensures that the AI evolves and becomes more accurate over time.
4. Human Oversight: While AI can handle many tasks, having human agents oversee and step in when necessary can prevent frustrations and provide a safety net.
Conclusion:
By building POCs and visualizing AI's capabilities, we can help businesses create better use cases and improve the overall customer experience. The rush to implement AI without a thorough strategy often leads to negative customer experiences. It’s crucial to understand how to optimize AI's potential and ensure it aligns with customer needs.