Chatbots have the potential to be a game changing technology that can revolutionize customer interactions, offering a host of benefits that traditional support systems struggle to match. Chatbots operate 24/7, handling multiple inquiries simultaneously while delivering instant and accurate responses. This not only streamlines operations but also significantly reduces costs, making large support teams and infrastructure a thing of the past. By embracing chatbots, businesses can modernize their customer service, boost customer satisfaction, and foster stronger customer loyalty. This leads to improved operational efficiency, reduced costs, and building a competitive edge in the digital age.

Common Challenges Faced by the Customers

For organizations with a global footprint, the traditional approach of relying on a single customer support center, often located in the U.S., can present significant challenges. The impracticality of expanding customer support centers globally and hiring multilingual staff is a clear limitation. This setup can lead to difficulties for users in different time zones and frustration when the available staff is overwhelmed by the volume of queries.

Other significant challenges include:

• High training costs for executives and the need for continuous learning whenever policies or processes change.
• Inconsistent responses to the same query, depending on which executive handles it.
• Difficulty in implementing a reliable feedback mechanism.
• Scalability issues as costs tend to proportionately increase with an increase in query volume.
• Longer conversation times.
• Extremely high operational costs.

However, these challenges can be effectively addressed by building an automated chatbot that provides a seamless customer service experience across different time zones and languages, ensuring security and scalability.

Intelligent Chatbots with Microsoft Azure

The standard Chatbot solution handles two types of information:

• Static Information: This includes fixed details like company policies and processes, such as the standard process for filing a claim or return policies.
• User-Specific Information: This involves specific details for each user, like their individual claim status and payment status. Chatbot uses this data to provide accurate responses based on the user’s questions.

Let us look at the Azure Components that can be used to make the chatbot intelligent:

• Conversational Language Understanding (CLU) to enable users to build custom natural language understanding models to predict the overall intention of an incoming utterance (User Input) and extract meaningful information from it. CLU only provides the intelligence to understand the input text for the client application and doesn’t perform any actions
• QnA Maker, a cloud-based Natural Language Processing (NLP) service, that facilitates the creation of a natural conversational interface over static data.
• WebChat, which is a customizable chatbot interface that makes creating and managing conversations easy.

How it Works:

• User Query: The user asks a question or makes a request.
• Intent Recognition: CLU figures out what the user wants.
• Response Creation: Depending on the intent, the system either –
  • Uses a template and the user’s data to create a response.
  • Looks up an answer in the QnA maker database.
• Response Delivery: The system sends the appropriate response back to the user.

Another key feature of the chatbots is the ability to transfer the conversation to a live chat agent, if available. However, when the user is dissatisfied, the system cannot identify the intent, or the intent is set up to trigger a transfer. The decision flow for this process is outlined below.

Key Features & Benefits of an Intelligent Chatbot

To sum it up, let us look at the key features and distinctive benefits that businesses can reap from deploying intelligent chatbots –

• Plug & Play: The solution is a flexible platform, not a standalone application. It operates based on database configurations and can be integrated with other applications. It is already connected with three different systems.
• Language Agnostic: Detects the language of the user’s question and responds in the same language.
• Automated Actions: Identifies user intent and performs tasks such as creating tickets and transferring calls to live chat agents. It responds intelligently based on the recognized intent.
• Feedback Mechanism: This mechanism analyses user sentiments and logs satisfaction levels with responses. These logs help refine intent and improve response accuracy over time.
• Integration: Compatible with live chat agents and ticketing systems.

As a result, these are the benefits realized by businesses –

• Streamlines processes by automatically managing tasks and user queries, such as ticket creation and call transfers, reducing manual effort and response times.
• Delivers consistent and relevant information to users, enhancing their overall experience.
• Continuously improves response accuracy through user feedback and sentiment analysis.
• Reduces the need for extensive human resources, cuts operational costs, and efficiently handles high query volumes while providing 24/7 support.
• Detects and responds in the user’s language, improving communication.
• Integrates seamlessly with existing systems and adapts to various applications, offering a versatile platform.

 

 

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