TicketPickUp is a one-of-a-kind intermediary between online ticket selling platforms and event organizers or bulk ticket sellers. This system functions as an online ticket booking engine, which was created specifically to eliminate the human labor required for this process in the past. Our client has a niche reputation in the field of computer technology and has been a leading ticket aggregator in the United States for many years. They are associated with well known ticket selling platforms who offer online ticket booking solutions for sports, entertainment, cultural and all kinds of events.
They were anticipated in a manual process that consumes a lot of time and human efforts, and the TicketPickUp system was developed to overcome it. The given application was already in the market and had been developed by another group of developers; however, the client was experiencing a number of technological and performance issues with that product. As a result, they turn to the Rlogical team to resolve the issue and improve the characteristics.
We looked at the existing application code and discovered that the architecture of the ticket booking solution was not robust enough to generate some key functionality.
In addition, the developed portion of the application represents only close to 15% of the overall scope. Considering the scalability of the app's functionality and understanding the customer's vision, we recommend developing the app from scratch.
We review the code quality and optimize the existing code
Made system independently sustainable by removing legacy tools
Provided 24*7 tech support with rotational shift of developers for smooth execution
We maintained transparency along with continuous improvement and attention to technical excellence
Assigned PM used to review the process weekly to make sure everything is in line
Existing and legacy application architecture were not scalable, maintainable, secure, and the performance was low. So it was quite difficult for the developers to understand the legacy application. Apart from that below are the problems we have faced.
Integration of multiple markets and scraping the data from their website.
System throw errors when vendor ID and Ticket IDs do not find the match with the location & events details.
Keep the database inventory updated with the latest data available from the third party APIs.
Usage the third party API efficiently to avoid API call limits for large amounts of database inventory.
The server used to hang during the processing and we had to restart the entire process repeatedly.
Data mismatch issues due to continuously changing algorithms of the 3rd Party APIs.
IBM cloudant was not able to handle the load when simultaneous multiple event tickets were being loaded or queries with large data were getting used.
With numerous brainstorming sessions with client and internal technical discussions, we have brought together all the right cutting-edge technologies to deliver top performance and a seamless development process. The entire architecture of the application was redesigned and we built it from the ground up by utilizing mentioned solutions.
The AWS concept for the load balancing mechanism. Assignment of a dedicated server to maintain load.
Created multiple AWS EC2 Instances dynamically to distribute the data processing in thread simultaneously.
Migration of the database to MongoDB to handle ad hoc queries.
Less coding complexity for queries and sorting.
Algorithm to increase genuine buying ratio by buying the most available tickets.
Blacklisting option to prevent unappropriate or mismatched event venue data.
Presale events and ticket management by unlocking the codes.
Ticket reprising algorithms to maintain the top position amongst the competitors.
After all the efforts of the team, we came to the conclusion by adding the appropriate features which can make the whole process hassle-free and easier to understand.
Getting event and venue information from different ticket management solutions with the help of automation. Black list mechanism for sold/flawy tickets, venues or events.
Set a profit margin and the system will automatically suggest a ticket resale price. Competitor analysis algorithm developed which shows comparison of suggested ticket selling price with other resellers, Admin can reprice the ticket selling price accordingly.
Customized dashboard to let users utilize the application as per their business requirement to ensure privacy and to provide easy access to the application.
This feature allows an app to get all the latest events and newly added venues from different sites by applying different mechanisms which are run by the automated scripts. Automated scripts to get events and venues.
This mechanism is used to keep some rows as a buffer which helps to provide a selected or an upgraded ticket to the customers.
Due to the row back mechanism system usually provides upgraded rows which delights the customers and increases repetitive business.
Multiple back office executives simultaneously work on ticket purchasing for the booked tickets.Socket.io used to lock specific ticketing id booking sessions.
System highlights the ongoing ticket booking in real time to avoid multiple purchases. System users have a toaster message for the notification.
Email account credentials can be added into the system so the bot can crawl the email account for booking confirmation details. System Scrap the Gmail account at regular intervals to get the purchased tickets confirmation details.
Boats can find the relevant details the email attachments (i.e. PDF documents) as well and link them to the respective booking record in the system. This feature allows users to save and update their mailing information which helps them maintain the vendor accounts.
System manages different types of tickets. I.e. General Admission TIcket, Group Ticket, VIP Pass etc.
Buyers purchase confirmed tickets from the marketplace and provide the PO to the customers after final purchase. This eliminates the chances of cancellation.