How to Monitor Event Data Using Web Scraping

What is Event Data Aggregation?

Event Data Aggregation is when data is collected from various sources about an event to power a web application, mobile app or similar.

Web scraping event data is the standard way of doing this unless companies have access to multiple API's which contain the required data.

Many apps including Google search and loads of other websites that allow you to book an event or find out more information about an event use web scraping to power their backend API.

Many data points can be collected depending on the requirements. Event sites, event times, ticket prices, amount of tickets left are just some of the possible field names.

This data is then shown via a GUI to an end user. This could be for a search functionality, to sell tickets, to help engage users on a website and more.

What types of Apps Aggregate Event Data?

Generally event data is used for applications that allow users to search for upcoming events from near to their current location.

For example, if you love a musician you may wish to lookup when they will be on tour near you, often you'll find an event aggregation website which will help solve your query and enable you to make a booking.

Many booking websites will also scrape event data to show how many tickets are left and to offer the best prices.

What are the other Use Cases for Event Data?

Event data is used in many other cases including quant trading (such as in the gambling industry), analytics and competitive research and more.

How can I collect Event Data?

You can collect event data with web scraping or data as a service. You can write your own web scraper or use the services provided by a web scraping company.

How can I write a Web Scraper to Collect Event Data?

To write your own web scraper to gather event data you will need to follow a few steps.

  • First, you'll need to identify target websites. The more websites you wish to aggregate data from, the more complex your program will be.
  • Secondly, you'll need to create required data structures. This could be as simple as 'name', 'date', 'total tickets' or you could include any fields available on your target websites.
  • Now, you'll have to write the scraper. This will include a database for storage, html or json parsing, as well as the ability for your program to send and receive http requests and responses and efficiently navigate the target websites.
  • Once you've written the scraper, you'll need a server and ideally some proxies or other anti blocking technology so your bot doesn't get banned.
  • Now, if all goes well you can export your data and update it when required.

Can the data be updated regularly, and more often closer to the event?

Yes, there are many use cases for this.

For example, advantage gamblers will want to monitor event related information more frequently right before an event goes in-play.

Also, many analytics purposes require that data be updated close to the start of an event. For example, if the event is over a week away data might be updated daily, however if the event is in an hour, data might be updated every 5 minutes.

If you create your own web scraper or use a web scraping service, these options can be fine tuned depending on your requirements.