Entradas.com is a Spanish company specializing in ticketing sales, and is part of CTS EVENTIM, one of the world’s leading international ticketing and live entertainment providers. Approximately 250 million tickets per year are sold using EVENTIM systems, and this is done through box offices, online, or via phone. Their online portals operate under brands such as eventim.de, oeticket.com, ticketcorner.ch, ticketone.it, and Entradas.com.
Their sales process can be split into two parts: cinemas, theatres, and concerts (managed by EVENTIM) and sports (managed by AVET, a company providing the tools, APIs and team servers for Spanish sports clubs).
Each Monday, Entradas.com had the task of configuring a number of queries within their database and sending their partners a CSV document containing their latest sales figures. Although this task didn’t require much time at the beginning of the season, towards the end it could take between 2 to 3 hours to complete.
As part of a plan to improve operational efficiency and the quality of service to our client, we automated this regular manual task using Process Automation to help save time, which could then be spent focusing on other areas of the business, such as product development and evolution.
In this example, Process Automation was able to increase efficiency by reducing the time spent on a task, and it also prevented the database from getting stuck during the process as the queries requested high amounts of data.
So, we studied the process, mapped the data, reworked the query, and developed a process that, by taking advantage of one of the partners’ APIs, sends the required information every 5 minutes. This is the minimum amount of time necessary to complete the query while there is a big sales process running.
From a technical point of view, the aim of our design was to build a process that, using data returned by the improved query and reworking the information, allowed us to send it correctly to the partner’s API.
Entradas.com spent approximately 130 hours each year carrying out this single task, and now. it has been reduced to zero within just 70 hours of development time. As a result, the task has now been completely automated, and partners can access the information in near real-time. Additionally, we were able to completely remove the need for human interaction, resulting in significant time and cost-savings for the customer and their partners.
With this in mind, we are able to build a similar automated process in about 40-70 hours, depending on the problem.
From a technical point of view, the aim of our design was to build a process that, using the data returned by the improved query and reworking the information, allowed us to send it correctly to the partners’ API. Investing more time into adding improvements to the API will allow for more automation in the future, and adding some updates to the initial code will further improve the management of their data.
HOURS OF DEVELOPMENT TIME
HOURS PER YEAR REDUCED TO 0
These two steps below provide a highlight the potential of Intelligent Process Automation.
Step 1 – Creating a purchase prediction system in which, based on user visits and previous purchases, suggests tickets that may be of interest to the user, or events that are in high-demand. This would be created using the data stored by Entradas.com on the details of user behaviors being incorporated into a Machine Learning process.
Step 2 – Creating a self-scaling system machine based on the opening of high demand events to anticipate possible consumption peaks. This would then supply the necessary infrastructure to meet said demand at all times. Entradas.com already has an infrastructure with the ability to scale in function of demand, but here the objective is to proactively – rather than reactively – respond to this demand thanks to a Machine Learning process.
Another Process Automation solution involves an external API that EVENTIM provides to its partners through Entradas.com.
To use the API, partners must develop a process where they take all the necessary information from the database each day and use it to complete the ticketing sales process by sending different requests to the API, such as the seating chart, seat bookings, booking confirmations, etc.
Analyzing the process, we developed an API that would implement the nightly update and store the information in a local database. This would allow their partners to work with our own API, instead of the EVENTIM API, which as a result improved their service quality and saved time.
At Intelygenz, we analyze our Process Automation projects using a 3-wins pattern: