How to Build a Chat Based Employee Self Service Platform
We want to cover and provide tips for creating a chat system that can handle most employee questions on its own, reducing the need to involve live agents. The goal is to design a platform that solves issues effectively and keeps more cases from needing human help.
Using Your FAQs and Content to Enhance Employee Self Service
Our chat platform includes a full CMS and FAQ content creation module. Use your FAQs and KB content to help employees quickly find answers to common questions, streamlining their support process. By tracking which questions frequently arise and comparing them to your existing FAQs, you can identify gaps and update the FAQ section with new information to better support both employees and customers.
Displaying FAQ content in a user-friendly and visually appealing format can significantly enhance the experience for employees, making it easier for them to quickly find the information they need. When FAQs are well-organized and attractively presented, employees are more likely to engage with and rely on the resource, leading to improved efficiency and satisfaction. An intuitive design not only reduces frustration but also encourages more frequent use, ultimately streamlining their workflow.
The clean, organized presentation of FAQs within Teams also ensures a visually appealing and user-friendly experience, enhancing overall usability and engagement.
Using Microsoft Teams to display FAQs is efficient because it integrates seamlessly into the platform employees already use, making information easily accessible without disrupting their workflow.
AI Chat: Embed Custom FAQs into a Conversational Chat Model
Integrating custom FAQs into an AI chat model enhances its ability to provide precise and relevant answers based on common inquiries. This setup allows the chat system to leverage predefined information, improving response accuracy and efficiency. By embedding tailored FAQs, the AI can engage in more natural and helpful conversations, ultimately enhancing user satisfaction and reducing the need for live agent intervention.
Customize results with your own data. Choose from existing data sources or link new ones through Azure Blob storage, databases, or local files. This data forms the base of your personalized results, while remaining securely stored in your chosen location.
AI chat systems equipped with real-time translation capabilities break down language barriers, enabling users to communicate seamlessly in their preferred languages. This feature translates messages instantly, ensuring that users from diverse linguistic backgrounds receive clear and accurate responses. By supporting multiple languages, AI chat systems make it easier to provide consistent and effective support across global teams and customer bases.
AI chat systems with conversation summary features automatically capture and distill key details from interactions. These summaries provide a concise overview of the chat, highlighting important points, decisions, and action items. This functionality helps streamline follow-ups, improve record-keeping, and enhance overall support efficiency by making it easier to review and address previous conversations.
Effective Ticketing Management: Streamlining Support and Tracking
With a chat-based self-service platform, you can monitor and manage open tickets directly through the chat interface, making it easy to add or update information as needed. If a ticket requires more detailed assistance, the platform can connect users to a live agent who can provide targeted help for the selected issue.
Reporting on Chat Session Deflection Rates: Optimizing Service Desk Efficiency
Monitoring deflection rates of chat sessions for a service desk involves analyzing how often customers are directed to self-service options instead of requiring live agent assistance. By using reporting tools effectively, you can gain valuable insights into these deflection rates and identify areas for improvement.
Track Deflection Rates: Use reporting tools to measure the percentage of chat sessions where customers successfully resolve their issues through automated responses or self-service options without engaging with a live agent.
Analyze Trends: Look for patterns in the deflection rates across different times, topics, or types of issues to understand when and where deflection is most or least effective.
Identify Improvement Areas: Use reports to pinpoint specific topics or service areas where deflection rates are low, indicating potential weaknesses in self-service content or automated responses.
Optimize Resources: Adjust and enhance self-service options and automation scripts based on insights from the reports to improve deflection rates and reduce the burden on live agents