In today's fast-paced world, conversational AI has emerged as a game-changer. By combining the power of natural language processing (NLP) and machine learning, conversational AI enables intelligent chatbots to understand, interpret and respond to human language.
As businesses strive to enhance their IT Service Management (ITSM) strategies, incorporating an AI-powered chatbot can unlock a plethora of benefits – especially when it comes to relieving the strain on overwhelmed IT service desks.
In this blog, we'll explore the advantages of using a chatbot within your ITSM practices and how it can improve user experience by enabling better self-service support.
Top Benefits of Integrating a Chatbot in Your ITSM Strategy
- Improved User Experience: Conversational AI chatbots offer instant support 24/7, providing users with quick, accurate and consistent responses. This leads to higher user satisfaction and increased customer loyalty.
- Streamlined Incident Management: Chatbots can handle a wide range of queries and tasks, including password resets, incident management and service request routing. By automating these tasks, chatbots free up valuable resources and enable IT teams to focus on higher-level tasks that require human intervention.
- Enhanced Self-Service Support: With conversational AI chatbots, users can resolve their issues without relying on IT personnel. In addition, by using a chatbot on your self-service portal you can save customers time – they no longer need to search for answers and can, instead, initiate a conversation with the chatbot to resolve their problem.
- Reduced Resolution Time: Chatbots can significantly reduce the time it takes to resolve issues by providing accurate information and guiding users through troubleshooting steps. This saves customers from having to put a ticket into support and wait for a response.
- Cost Savings: By automating routine tasks and streamlining support processes, chatbots can help businesses save on operational costs.
The Power of Conversational AI: NLP and Machine Learning
Conversational AI leverages NLP and machine learning to understand and process human language, enabling chatbots to provide a more natural and engaging user experience. Here's how these technologies contribute to a chatbot's effectiveness:
- Natural Language Processing (NLP): NLP enables chatbots to comprehend and interpret user inputs, allowing them to respond accurately and contextually. This technology helps chatbots understand complex language structures, slang, and even typos.
- Machine Learning: Machine learning allows chatbots to learn from past interactions and improve their responses over time. As a result, chatbots become more efficient and effective in handling user queries, leading to continuous improvement in user experience.
Using conversational AI chatbots vs traditional chatbots (that follow a simple question/answer dialog path) is key to success. When you add a conversational AI chatbot to existing self-service options, you can increase the self-service adoption rate by 50 percent vs. standard chatbots.
How to Have a Successful Chat for Self-Service
According to a recent survey, there are four key elements for a successful chat experience when it comes to using conversational AI for self-service. The top cited element was a strong knowledge base for content to feed the chat, which was named by 75 percent of respondents. That was closely followed by the ability to personalize the conversation with details about the customer, named by 63 percent. Third and fourth place were ranked equally, named by 62 percent, who equally weighted the ability to present questions to the employee that drives dynamic content with the ability to automate the fulfillment of requests from the chat interaction.
Conversational AI especially benefits service management teams when paired with enterprise integration and automation (using iPaaS). This combination can elevate chat from a glorified knowledge base search engine into an automated, action-centered channel to field requests.
No matter how good the knowledge base, personalized user information can only be uncovered through the inherent ability to connect to business systems via APIs and integrations. This capability is what makes it possible to automatically provide dynamic content and fulfill simple, repetitive requests for action.
One example of this in action would be an employee asking the chatbot how much paid time off (PTO) they have left for the year. A first-generation chatbot may not be able to answer that, instead offering a link to the employee knowledge base article about how much PTO each employee gets annually.
A conversational AI chatbot tied to a well-connected integration and automation layer could personalize the response leveraging Single Sign-On, and then access the employee’s data from another application to deliver an accurate, fast response. In this case, the response may say, “Currently, you have 12 days of PTO left this year.” It might even follow up with a question like, “Do you want to know how many of these days will roll over next year?” or, “Would you like to request time off?” If the end-user response is to request time off, the solution would present a form for the request to be entered and then pass that data back to the PTO tracking platform.
In conclusion, incorporating an AI-powered chatbot as part of your ITSM strategy can significantly enhance your user experience, streamline processes and unlock cost savings. By leveraging the power of conversational AI, businesses can stay ahead of the curve and deliver top-notch IT support services. Want to learn more about chat vs. conversational AI? Read the full market study: State of Chatbots and Conversational AI.