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Cloud-Based Tier 1 Support That Keeps Aviation eLearning Platforms Running Smoothly
eSparkBiz delivers 24/7 L1 support for a global aviation training platform that serves 250+ clients. We have set up omnichannel support systems to resolve tickets quickly and provide a seamless experience.
What We Did
Our teams are built for scalability, and they have defined escalation metrics that are met under pre-defined SLAs, which helps us in maintaining uptime and providing a better user experience.
24/7 L1 Support
Omnichannel Support Structure
This architecture centralizes omnichannel inputs through Amazon Connect, enabling streamlined support, AI self-service, and real-time analytics:
Key L1 Support Responsibilities
SLA Adherence & Consistent Service Quality
Improved Collaboration and Reporting
Strategic Roadmap for Growth & Scalability
✈️ Did You Know?
In 2024, global air cargo demand increased by 11.3% compared to 2023, surpassing the previous record set in 2021.
Our client struggled with unclear workflows, overworked support teams, and delayed responses to users, which often resulted in frustration and dissatisfaction with the platform. Moreover, the lack of coordination between L1 and L2 support teams made more impact on the service and also brought down the platform experience.
Our client consistently faced delays in responses to user queries and tickets on the platform. Even the simple tickets, like login issues, course access, etc, could get delayed for a long time and result in frustrated users. This has impacted the client’s service reputation in the domain.
The client's support tools were not set up correctly, and they killed productivity instead of uplifting it. Moreover, it made it harder for teams to manage tickets across email, chat, phone, and portals. Due to this incorrect setup, tracking tickets became much harder, and it started causing visibility issues, as well as delayed servicing to users.
The client's service setup was not scalable, due to which their teams would struggle to service even 400 tickets a month during peak times. This caused extended wait times for each user.
Though the client offered support across different platforms like email, chat, portal, etc, the lack of a centralized tracking solution made ticket handling harder for teams across platforms. Users often suffered due to delayed responses and had to reshare the same information across platforms to get solutions.
Even with highly-trained support teams at the L1 and L2 levels, the client did not have a correct handoff process between their teams, which affected response times even after escalations. The lack of coordination between these teams meant frequent yet unclear escalations and tickets that would stay unresolved for longer periods.
Teams lacked centralized dashboards to identify recurring support issues quickly, impacting decision-making and service reliability. By implementing advanced data analytics and real-time reporting, the support team gained actionable insights, improved forecasting, and reduced repeat tickets, ensuring smoother operations for aviation training platforms.
Users relied on live agents even for routine queries, leading to higher ticket volume and slower resolutions. Deploying an AI-driven knowledge base and self-service portal empowered users to resolve common issues independently, reduced support load, and boosted customer satisfaction across aviation training platforms.
eSparkBiz leveraged its knowledge of AWS Development and service domains to come up with a scalable solution. We built the solution with Amazon Connect and Jira service desk to streamline ticket management across different platforms like voice, chat, email, etc. The new setup improved service times, and L1-L2 collaboration, and helped the client achieve higher user satisfaction.
We implemented a 24/7 support system that can serve users across time zones and provide seamless assistance. Our solution also includes a real-time monitoring tool to help track and improve the performance of your teams through workflow adjustments based on ticket loads and ensure faster resolution. This approach brought down resolution time by 30% and increased customer satisfaction.
eSparkBiz leveraged its AWS integration capabilities to set up an integrated Amazon Connect and Jira service desk for teams and centralized ticket tracking, as well as management options across different channels.
This visual streamlines omnichannel inputs into AWS-powered automation, delivering faster resolutions, smarter routing, and real-time support efficiency gains:
We created an efficient routing and rules policy for managing high ticket volumes with precision at all times. This approach helped teams to address critical cases first, reduce delays, and meet SLAs at all times.
We used Amazon Connect to unify email, chat, and phone support into a single support system. This integration helped in improving response times and a smoother transition between different platforms.
We helped the client by defining escalation workflows to enable better coordination and collaboration between L1 and L2 support teams. Our team also set up ongoing training and feedback-sharing between teams to help them stay aligned with servicing customers better and quickly.
We introduced real-time dashboards and trend reports, giving teams actionable insights into recurring issues. This data-driven approach improved forecasting, reduced repeat tickets, and strengthened decision-making, helping keep aviation training platforms stable and responsive.
We built a dynamic, searchable portal with AI-driven consulting, enabling users to handle FAQs and routine tasks themselves. This streamlined user journeys, cut ticket volume, and ensured Tier 1 teams focused on complex issues, improving efficiency and satisfaction.
eSparkBiz’s business-aligned support solution helped in achieving faster resolutions to problems, better satisfaction, coordination, and scalable service delivery across the organization. The client now operates with much better efficiency, and highly productive teams, and has unlocked accelerated growth.
Key Outcomes: