AI-powered virtual assistants can be equipped to handle customer queries independently to ensure instant responses and an option for users to get their queries answered without having to connect with and/or wait for a support professional. With the ability to train the bot, it can make the interactions intuitive and user-friendly, further enhancing the user experience. By handling routine queries, the AI frees up your support operations team to focus on more complex, emotional, and demanding issues, thereby enhancing overall support operations.

AI-powered chatbots can be programmed to assist customers in troubleshooting common issues. They can guide users through a series of steps to identify and resolve problems, offering a self-service solution that is both efficient and empowering for the customer.

In Dan Sahar’s session titled ‘Chatbots are only as good as their training’ at the SD Expo, he talks about how chatbots can be dangerous when they don’t know what they don’t know. In such cases, the answers can be inaccurate and lead to bad customer experiences. As a rule of thumb, he mentions how support teams can approach this concern by providing more accurate data to the bot, and to do so, they can begin with the following approach

FIFO - First in first out is an approach where we focus on older content that is not exactly wrong but is outdated knowledge. Update the content for the bot to be more accurate.

‍Ticket Review - Look at the history of tickets and see which questions have been most commonly asked. Refine the answer to ensure accuracy.

‍Downvotes - All the downvoted answers represent dissatisfaction by the customers. Use this to improve the answers before the bot is trained on it.

‍Chatbot replay - If you’ve already implemented a chatbot, go through its answers from the past few months and correct all the answers that might be inaccurate or even incomplete.

Conversational AI is an extension of intelligent bots that can enhance customer services through cross-channel experiences. An intelligent bot can conduct entire conversations using auto-suggestions and the best part is that it can learn through these iterations and improve itself over time.

Tools like Threado AI can be installed across multiple channels like being embedded as a chatbot within the product or on the website. It can also be installed on channels in your Slack or Discord support community so customers can get support across different platforms. This equates to an immersive support experience that’s not restricted to humans, platforms, or places.

By constantly monitoring customer conversations with intelligent bots or through the concerns raised - you can improve the knowledge bases that become the basis for complete self-help. Analyze user interactions to identify gaps for improvement and improve the answers to make them more accurate. Enrich the knowledge bases and update them regularly to keep them up-to-date resources for customers.

A reliable way to identify gaps is by monitoring which questions is the bot not able to answer or which answers are incorrect or dissatisfactory for the customers. This is an opportunity that can be leveraged to add more questions that the bot can be trained on. Eventually, the entire knowledge base gets optimized.

AI leverages predictive text and auto-suggestions to facilitate quicker and more efficient self-service. By analyzing previous customer interactions and queries, it can suggest potential solutions even before a customer completes typing a query, fostering a seamless self-service experience.

A lot of bots tend to offer suggestions to make it easier for customers to interact and resolve their problems.

As an extension of the previous point, you can leverage auto-suggestions to create workflows that a user can follow. By giving pre-defined options, you’re not just saving time for the user but also making it easier to navigate through questions and resolve queries faster.

AI can also recommend FAQs, articles, and references that the user can explore on their own. These workflows can be some of the best ways to offer self-serve support to customers.

AI tools can analyze customer queries in real-time to suggest potential responses to support agents. This not only speeds up the response time but also aids in providing accurate and consistent responses, enhancing the overall efficiency of the support process.

Intelligent AI bots can be trained on extensive knowledge bases and become more proficient in how your product or service works. The more extensive your knowledge base is, the more easily it can be integrated with the AI bot and leveraged to answer support queries accurately. A tool like Threado AI also adds the links from where the reference has been taken which can help the support professionals retrieve relevant articles and solutions faster, making them more efficient as well.

AI tools can aid in the continuous training and skill development of support agents. Through AI-powered training modules, agents can receive personalized training that enhances their skills and knowledge, fostering a team of highly skilled and efficient support agents.

Before you can improve, you need to measure. Assessing your current operations will help you identify inefficiencies, bottlenecks, and areas ripe for AI intervention. Good customer service already boosts customer interest in purchasing; imagine what you can achieve with AI-enhanced support!