The Keys to Improving Your IT Chatbot Success

As interest in AI in IT grows, there’s still a lot of skepticism around the use of chatbots. And this skepticism is well deserved. A recent market study from CIO.com found that nearly 76 percent of chatbot customers report user frustration with existing solutions. That’s a HUGE number.

So how can the chat experience be improved? Conversational AI, different from traditional chat, is a great way to improve the chat experience for customers.

In fact, when conversational AI is used more than 61 percent of those surveyed said users were able to resolve their problems versus just 35 percent when traditional chat is used.

Conversational AI vs. Traditional Chat – What’s the Difference?

The problem with traditional chatbots is that they aren’t smart – they lack the “brain” or natural language processing (NLP) that conversational AI chatbots have.

Instead of understanding a person’s intent when a question is asked – a traditional chatbot is programmed to follow a very linear path and any deviation from that path (usually due to the inputs from an end-user or customer) can cause that chatbot to fail. And when a chatbot fails it’s often a frustrating experience and adds to the ticket volume of your IT service desk.

Conversational AI chatbots, on the other hand, have several advantages a traditional chatbot lacks including:

1. Human-like Interactions: One of the most significant advantages is their ability to replicate human interactions. This leads to an improved user experience and higher satisfaction levels.
2. Understanding Intent: Unlike traditional chatbots, conversational AI chatbots can understand the intent behind a user's query, not just the literal meaning. This makes them much more effective when it comes to assisting customers and end-users.
3. Greater Engagement and Accuracy: Conversational AI chatbots offer much higher levels of engagement and accuracy in understanding human language compared to traditional chatbots.
4. Adaptive Learning: Conversational AI chatbots leverage machine learning to adapt and improve over time. They can answer questions that are not identical to what they have in their knowledge base.
5. Natural and Engaging Conversations: AI-based chatbots can have more natural and engaging conversations than rule-based chatbots.

The Benefits of Conversational AI Chat

When you combine automation, self-service and conversational AI – you can positively impact IT resource drain and improve the experience of your customers and end-users.

Conversational AI chatbots are intelligent software applications that can simulate human conversations and perform tasks such as answering questions, providing information and performing transactions.

Conversational AI leverages natural language processing and understands intent. While they do need to be trained, with conversational AI you can facilitate more complex conversations and resolve issues through actions vs. the traditional chatbot's question/answer limited dialog path.

Because conversational AI chatbots understand intent, they are much more effective when it comes to assisting customers and end-users. For example, when using traditional chat if you say “My password broke” it would likely respond with something like “I’m sorry, I don’t understand that. Please type your issue again,” and continue down that path with a final response that might give you links to 3-5 FAQ articles that it thinks might help resolve the issue – leaving it to the customer to further seek out a solution to the password problem.

When you have conversational AI, if you were to say “My password is broken” it can inform your intent and know that what you mean is your password isn’t working and needs to be reset. The response from the chatbot is then something like, “I can see you’re having issues with your password. I’ve sent a reset password link to the email on file.”

On the backend, the chatbot can pull the email address needed from the system where it’s stored and automatically send a password reset email – resolving the issue within the conversation in seconds versus sending the customer links and having them do the work to request the link.

Implementing conversational AI chatbots as part of your IT Service Management (ITSM) strategy can provide a myriad of advantages. Here are some key benefits:

1. 24/7 Availability: Chatbots are available round the clock, ensuring continuous service for customers and employees alike. This means that even outside of standard business hours, users can still have their queries addressed in real time.
2. Reduced Waiting Times: Conversational AI chatbots can respond to queries instantly, significantly reducing customer waiting times. This leads to a more satisfying user experience.
3. Enhanced Productivity: By automating routine tasks, conversational AI allows your IT team to focus on more complex issues. This can increase overall productivity.
4. Improved Customer Experience: With the ability to handle multiple inquiries simultaneously and provide instant responses, chatbots can enhance the customer experience.
5. Cost Efficiency: Chatbots can handle a high volume of queries without any additional cost per interaction, making them a cost-efficient solution.
6. Increased Self-Service Engagement: The ability of chatbots to provide personalized interaction based on user data can lead to higher engagement. The more successful the interaction, the more likely that user is to come back and use self-service in the future vs. submitting a ticket or calling your IT help desk.
7. Seamless Solutions Between Tech and People: Chatbots serve as a bridge between technical solutions and human interaction, providing a more intuitive and user-friendly self-service experience.

By adopting conversational AI chatbots as part of your ITSM strategy, you can significantly improve self-service adoption, customer satisfaction and problem-resolution time – all while cutting costs and reducing the drain on overburdened IT resources.

Making Good on the Promise of Chat

Of course, having a strong conversational AI chatbot platform with a standardized NLP engine isn’t the only necessary ingredient for self-service chat success.

In a market study conducted by InformationWeek and TeamDynamix, respondents listed four key elements for successful conversational AI chat. The top element (75 percent) is a strong knowledge base with content to feed and train the chatbot.

That was closely followed by the ability to personalize the conversation with details about the customer, named by 63 percent. The third and fourth places were ranked equally, named by 62 percent, who equally weighted the ability to present questions to the employee that drive 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.

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.

However, 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 be, “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.

Want to learn more about conversational AI and all it can offer versus traditional chat? Check out our market study: State of Chatbots and Conversational AI.