Revolutionize Customer Service with AI-Driven Support

Table of Contents

1. Introduction
2. The Importance of AI-Driven Support
3. The Role of NIST in AI Support Tickets
4. The Organizational Part of AI Support
5. The Partnership between Jishong and David Jay
6. The Impact of Customer Support on Efficacy
7. The Progress of Marvis in Answering Support Tickets
8. The Addition of Graph Database Framework
9. Solving the Misconfiguration Use Case
10. The Future Arc of AI Support Tickets
11. The Growth of Mist Cloud Users
12. The Relationship between Support Tickets and Timing
13. Categorization of Support Tickets

AI-Driven Support: Revolutionizing Customer Service

In today's technology-driven world, customer support plays a crucial role in ensuring customer satisfaction. However, traditional support models often fall short in providing Timely and effective solutions. This is where AI-driven support comes into play, with its ability to leverage artificial intelligence and machine learning algorithms to optimize the support process. Leading the charge in this field is NIST, the vendor that is revolutionizing customer support through its advanced AI support ticket system.

The Importance of AI-Driven Support

AI-driven support is an innovative approach that aims to enhance Customer Service by automating support ticket resolutions. By utilizing AI technology, companies can ensure faster response times, improved accuracy, and a more consistent support experience. The key to successful AI-driven support lies in the combination of powerful algorithms and effective organizational processes.

The Role of NIST in AI Support Tickets

NIST has emerged as a frontrunner in the field of AI-driven support. Their aiml engine is designed to tackle every support ticket that enters their system. What sets NIST apart is their dedication to continuous improvement. Jishong and David Jay, the leaders of NIST's customer support team, review every support ticket that Marvis (NIST's AI system) couldn't answer. This feedback loop allows NIST to constantly enhance Marvis' efficacy and ensure customer satisfaction.

The Organizational Part of AI Support

While algorithms play a vital role in AI-driven support, the organizational aspect is equally important. NIST recognizes this and has tightly integrated their customer support and data science teams. This collaboration ensures that customer support feedback directly influences the development of Marvis. David Jay, as the proxy for NIST's customers, acts as the liaision between the support team and the data science team. This synergy is the backbone of NIST's commitment to continually driving improvement.

The Partnership between Jishong and David Jay

Jishong and David Jay's joint efforts have proven instrumental in the success of NIST's AI-driven support system. Their weekly meetings to review support tickets that Marvis couldn't handle allow them to identify Patterns and areas of improvement. By aligning the support team's insights with the capabilities of the AI algorithms, NIST continuously refines Marvis to deliver optimal solutions.

The Impact of Customer Support on Efficacy

Customer support plays a critical role in AI-driven support systems. David Jay and the customer support team at NIST represent the largest pool of customers, allowing them to Gather valuable insights. By prioritizing customer support satisfaction, NIST ensures that Marvis is equipped with the necessary data to handle a wide range of support tickets. Making David Jay and the support team happy directly translates to customer satisfaction.

The Progress of Marvis in Answering Support Tickets

NIST's commitment to improving Marvis' efficacy is clearly visible in the progress Chart. Over time, Marvis has become increasingly capable of answering support tickets. While there are occasional dips, representing unanswered tickets, NIST's data-driven approach ensures that ongoing improvements are made. Currently, Marvis successfully handles over 65% of support tickets, either by providing the correct answer or supplying Relevant data for quicker resolution.

The Addition of Graph Database Framework

To further enhance Marvis' capabilities, NIST is integrating a graph database framework. This powerful tool will enable NIST to identify the root causes of complex issues, specifically focusing on the misconfiguration use case. By leveraging the graph database, NIST can quickly connect the dots between user problems and misconfigurations on the network, streamlining troubleshooting and reducing resolution time.

Solving the Misconfiguration Use Case

Misconfigurations often lead to user experience issues, making them challenging to identify and resolve. However, with the graph database framework, NIST can effectively pinpoint misconfigurations caused by routers or switches on the network. This improvement allows NIST's support team to address the underlying problems promptly, thereby ensuring a seamless user experience.

The Future Arc of AI Support Tickets

NIST's continuous dedication to improvement means that the efficacy of AI support tickets will continue to evolve. While already impressive, NIST aims to surpass the 80-90% success rate in the near future. As with self-driving cars and Watson, the addition of the graph database framework will unlock a whole new level of problem-solving capabilities, bridging the gap between user problems and their root causes.

The Growth of Mist Cloud Users

The exponential growth in the number of users and managed devices on the Mist Cloud showcases NIST's success in the market. Despite this significant growth, the average number of support tickets remains predominantly flat. This indicates that both NIST and its customers are experiencing fewer support issues, emphasizing the effectiveness of their AI-driven support system.

The Relationship between Support Tickets and Timing

Support tickets not only vary in quantity but also in timing. Some tickets are quick and easy to resolve, while others require more time and effort. NIST acknowledges this aspect and tracks different types of tickets, such as problem tickets, question tickets, internal tickets, and new customer tickets. By categorizing and analyzing these tickets, NIST can identify areas that need improvement and optimize their support process accordingly.

Categorization of Support Tickets

Within the realm of support tickets, NIST further categorizes them based on complexity and rarity. While the specifics are not revealed, NIST recognizes that certain issues are harder to troubleshoot and require more resources. By identifying these challenging problems, NIST can allocate the appropriate efforts to address them effectively, resulting in better support outcomes for their customers.

As technology continues to advance, AI-driven support will play an increasingly vital role in meeting customer expectations. NIST's commitment to excellence and continuous improvement ensures that their AI support system remains at the forefront of the industry, enabling them to provide exceptional customer service.

🔍 Resources:

• NIST Website
• Mist Cloud