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Artificial Intelligence (AI) is no longer just a buzzword; today, it's a promising solution that can make real contributions to your business processes. In this article, we're going to give you 12 practical ways to incorporate AI into your customer service strategy. Each of these strategies can be tailored to your unique business needs, especially if you're operating a SaaS (Software as a Service) company. Lay the foundation for AI integration using these practical steps, and you're certain to see a notable transformation in your customer service experience.
Contemplating the use of an AI chatbot for your customer support? The best way to begin is by setting it up as an internal tool. This will give you firsthand experience of how well your AI chatbot is able to field a variety of questions, and you'll be able to understand your solution's strengths better. The operational workflow here is pretty straightforward: when a new message or ticket comes in, it is checked against your knowledge base using vector search. From there, the AI chatbot crafts an appropriate response. To ensure your system's robustness, you can add multiple layers of AI logic into your workflow to tackle edge cases.
After the successful internal application of your AI chatbot, you can confidently extend its services to dealing with customer inquiries. To make this transition smoother, you should have a clear grasp of its capabilities, strengths, and the subject areas where it delivers the best responses. With this knowledge, you can even specify use cases where the chatbot is most effective and steer other inquiries, such as those related to refunds, to human agents.
An AI model can be used to distill long-drawn tickets or emails from customers into concise, easy-to-understand sentences. This is especially useful when customers pack multiple questions into one ticket. The AI can sift through these queries and break them down into simpler components.
Getting your data into an easily interpretable format requires efficient labeling. AI comes in handy for this purpose as it can make sense of words and their underlying connections, thereby labeling your data appropriately.
For more precise data categorization, you can employ a predefined list of categories. This makes your data more organized and consequently more useful when conducting data analytics.
Traditional sentiment solutions typically detect the overall sentiment of a message. However, with AI, you can better understand subtle emotional clues within customer messages—a feature standard tools often overlook.
AI can convert whole phrases into vectors, enabling you to search for content that has a similar meaning to what you're interested in. This simplifies the otherwise tedious task of searching for specific terms or synonyms in your content.
With AI, your closed tickets are a treasure trove of information, waiting to be leveraged. By identifying which cases repeat most often, you can get AI to generate new insightful support articles based on the closed tickets.
AI proves to be a valuable tool when jargon needs to be simplified for customers. Regardless of how technical a language may be, AI can convert it into elementary terms, helping customers and support team members understand complicated support tickets better.
AI can ensure that every customer communication maintains a consistent brand voice. With AI, you can create a messaging standard that aligns with your brand's personality and tone of voice.
AI's translation capabilities mean you can assist customers in their native language. Although the quality of translation might vary across different languages, AI's performance in core languages is quite reliable.
AI can also be used to transcribe phone support calls. This not only simplifies the review process, but also opens an avenue for further LLM tasks like sentiment analysis.
The benefits of infusing AI in your customer support processes are enormous, and these 12 use cases of AI provide excellent starting points for any SaaS company looking to enhance its customer support system. Whether it’s implementing an internal AI chatbot or transcribing support calls, these strategies will help streamline your operations and positively impact your customer service delivery.
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