Ticketmaster.com Tickets Data Scraping on a Recurring Basis
# | event_url |
event_id |
title |
datetime_utc |
datetime_local |
name |
postal_code |
scrape_date |
ticket_id |
ticket_price |
total_price |
fee |
service_fees |
full_section |
section |
row |
quantity |
deal_score |
in_hand_date |
selection |
||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1 | xxxxxxxxxx | Xxxxxxxxx | xxxxxx | xxxxxxxxxx | Xxxxx | Xxxxxx | Xxxxxxxxxx | Xxxxxx | Xxxxxxxxx | Xxxxxxxxxx | xxxxxxxxx | Xxxxxxxxx | xxxxxxxxx | Xxxxxxx | xxxxxx | Xxxxx | xxxxxxxxxx | xxxxxx | Xxxxxxxxxx | xxxxxx | Xxxxx | Xxxxxx | xxxxx | xxxxxxxx |
2 | xxxxxxx | Xxxxx | Xxxxxxxx | xxxxxxxxxx | xxxxxx | Xxxxxxxxx | xxxxxx | Xxxxxxxxx | Xxxxxxxxx | xxxxxxxxxx | Xxxxxx | Xxxxx | xxxxxx | xxxxxxx | xxxxxxx | Xxxxx | xxxxxx | Xxxxxxxxxx | xxxxxxxx | xxxxxx | Xxxxx | Xxxxxxx | xxxxxx | Xxxxxxxx |
3 | Xxxxxxx | Xxxxx | xxxxxx | xxxxxxxxxx | Xxxxx | xxxxxxxxxx | xxxxxxxxx | Xxxxxxx | xxxxxxxx | xxxxxxxx | Xxxxxxxxxx | Xxxxxxxx | Xxxxxxxx | xxxxxxxxx | Xxxxxxxxxx | Xxxxxx | Xxxxxxxxx | xxxxx | xxxxxxx | xxxxxxxxx | Xxxxxx | Xxxxxxx | Xxxxxxxxx | xxxxxxxxx |
4 | xxxxxxxxx | Xxxxx | xxxxxxxx | Xxxxxxx | xxxxxxxxx | Xxxxxxx | xxxxx | Xxxxxxx | xxxxxxx | Xxxxx | xxxxxxxxxx | Xxxxxxx | Xxxxx | xxxxxxxxxx | Xxxxxx | xxxxxx | Xxxxxxxxx | xxxxx | Xxxxxxxxxx | xxxxxx | xxxxx | xxxxxxxx | Xxxxxx | Xxxxxxxxxx |
5 | xxxxxxxxx | Xxxxxxxxxx | xxxxxxxx | xxxxx | Xxxxxx | xxxxxxxxxx | xxxxxxxxx | xxxxx | xxxxx | xxxxxxxx | xxxxxx | Xxxxxxxxxx | xxxxxxxxxx | Xxxxx | xxxxxxx | Xxxxxxxx | Xxxxxxx | xxxxx | xxxxxxxx | xxxxxxxxxx | Xxxxxx | xxxxxxxxx | Xxxxx | xxxxx |
6 | xxxxxxxxx | xxxxxxx | Xxxxxxxxx | Xxxxxxx | xxxxxxxxxx | Xxxxx | xxxxxxxxx | xxxxxxx | Xxxxxx | xxxxxxxxx | xxxxx | Xxxxxxx | xxxxxxxxx | Xxxxxxxx | xxxxxxxx | Xxxxxxxx | Xxxxxxxx | xxxxxxxx | xxxxxxxxx | Xxxxxxx | Xxxxxxxxx | xxxxxxxx | xxxxx | Xxxxxxxxxx |
7 | xxxxxxxxxx | xxxxxx | Xxxxx | Xxxxxxx | Xxxxx | Xxxxxx | Xxxxx | Xxxxxxxxx | xxxxxx | xxxxxxxx | Xxxxxxxxx | Xxxxxx | Xxxxxxxxxx | Xxxxxx | Xxxxx | Xxxxxxx | xxxxxxxxx | Xxxxx | xxxxx | Xxxxxx | xxxxxxxxx | xxxxxxx | xxxxxxxxx | Xxxxxxxxxx |
8 | xxxxxxxxx | Xxxxx | Xxxxx | Xxxxxxxxx | xxxxxxxxxx | xxxxxx | xxxxxxxxx | xxxxxxx | Xxxxxxx | Xxxxxxxxxx | Xxxxxxxxxx | Xxxxxxxx | Xxxxxxxxx | xxxxx | Xxxxxxx | xxxxxxxxxx | Xxxxxxxxx | Xxxxxxxx | xxxxxxxxxx | xxxxxxx | Xxxxxxxx | xxxxx | Xxxxxx | xxxxxx |
9 | xxxxxxxx | xxxxxxx | Xxxxx | Xxxxxxxxx | Xxxxx | Xxxxxxx | Xxxxxxxx | xxxxxxxxx | xxxxxxxx | xxxxx | Xxxxxxxxxx | Xxxxxxx | xxxxxxxxx | xxxxxxx | xxxxxxxxxx | xxxxxx | xxxxx | Xxxxxxxxxx | Xxxxxxxxx | xxxxxxx | Xxxxxx | Xxxxx | Xxxxxxxx | xxxxxxxxx |
10 | xxxxxxxx | Xxxxxx | xxxxxxxxxx | xxxxxxxxx | xxxxx | Xxxxx | xxxxxxx | xxxxxxxxxx | Xxxxxx | Xxxxxxxxx | xxxxxxx | Xxxxxxxx | xxxxx | xxxxx | Xxxxxxxxxx | Xxxxxxx | Xxxxxxxx | Xxxxxxx | xxxxx | xxxxxxx | Xxxxx | xxxxxxxxxx | Xxxxxxxxxx | xxxxxxx |
... | Xxxxx | xxxxxxxxx | xxxxxxxx | Xxxxxxxx | xxxxxxxx | Xxxxxxx | Xxxxxx | Xxxxxxxxx | Xxxxxxxx | Xxxxxxxxxx | Xxxxxxx | Xxxxxx | Xxxxxxxxxx | xxxxxxxxxx | xxxxxxxxxx | Xxxxxxx | Xxxxx | Xxxxx | Xxxxx | Xxxxxxx | xxxxx | xxxxxxxxx | xxxxxxx | Xxxxxxx |
Data Dictionary
Attribute | Type | Example | Mapping |
---|---|---|---|
event_url
|
String | https://www.ticketmaster.com/madonna-the-celebration-tour... | |
event_id
|
String | 09005E39EB887DA2 | |
title
|
String | Madonna - The Celebration Tour | |
datetime_utc
|
String | 1/8/2024 4:30 | |
datetime_local
|
String | 1/7/2024 20:30 | |
name
|
String | Kia Forum | |
String | Address | ||
String | Inglewood | City Name | |
String | CA | State Name | |
String | US | Country Name | |
postal_code
|
Integer | 90305 | |
scrape_date
|
String | 2/25/2023 11:42 | |
ticket_id
|
String | GN6DIOJZGU3DQNJYHB6DSMRVHA3GEMTGGU | |
ticket_price
|
Integer | 102 | |
total_price
|
Float | 121.64 | |
fee
|
Float | 19.64 | |
service_fees
|
String | service:19.64 | |
full_section
|
Integer | 208 | |
section
|
Integer | 208 | |
row
|
Integer | 26 | |
quantity
|
Integer | 4 | |
deal_score
|
Float | 0.051111 | |
in_hand_date
|
|||
selection
|
String | resale |
Attribute | Type | Example | Mapping |
---|---|---|---|
event_url
|
String | ||
event_id
|
String | ||
event_title
|
String | ||
event_datetime_utc
|
DateTime | ||
event_datetime_local
|
DateTime | ||
venue_name
|
String | ||
venue_address
|
String | ||
venue_city
|
String | ||
venue_state
|
String | ||
venue_country
|
String | ||
venue_postal_code
|
String | ||
ticket_id
|
String | ||
ticket_price
|
Float | ||
total_price
|
Float | ||
fee
|
Float | ||
service_fees
|
String | ||
full_section
|
String | ||
section
|
String | ||
row
|
String | ||
quantity
|
Integer | ||
selection
|
String |
Description
Country Coverage
History
Volume
150 million | rows |
Pricing
License | Starts at |
---|---|
One-off purchase |
$10,000 / purchase |
Monthly License |
$10,000 / month |
Yearly License |
$100,000 / year |
Usage-based | Not available |
Suitable Company Sizes
Quality
Delivery
Use Cases
Categories
Related Products
Frequently asked questions
What is Ticketmaster.com Tickets Data Scraping on a Recurring Basis?
Ticketmaster is a popular online platform for buying and selling tickets to various events such as concerts, sports games, theater shows, and more. Scraping Ticketmaster events and tickets involves automatically extracting data from the website’s pages using custom built web scraping software.
What is Ticketmaster.com Tickets Data Scraping on a Recurring Basis used for?
This product has 3 key use cases. Datamam recommends using the data for Market Research, Marketing Intelligence, and Competitive Intelligence. Global businesses and organizations buy Event Data from Datamam to fuel their analytics and enrichment.
Who can use Ticketmaster.com Tickets Data Scraping on a Recurring Basis?
This product is best suited if you’re a Small Business, Medium-sized Business, or Enterprise looking for Event Data. Get in touch with Datamam to see what their data can do for your business and find out which integrations they provide.
How far back does the data in Ticketmaster.com Tickets Data Scraping on a Recurring Basis go?
This product has 1 days of historical coverage. It can be delivered on a secondly, minutely, hourly, daily, weekly, monthly, quarterly, yearly, real-time, and on-demand basis.
Which countries does Ticketmaster.com Tickets Data Scraping on a Recurring Basis cover?
This product includes data covering 249 countries like USA, China, Japan, Germany, and India. Datamam is headquartered in United States of America.
How much does Ticketmaster.com Tickets Data Scraping on a Recurring Basis cost?
Pricing for Ticketmaster.com Tickets Data Scraping on a Recurring Basis starts at USD10,000 per purchase. Connect with Datamam to get a quote and arrange custom pricing models based on your data requirements.
How can I get Ticketmaster.com Tickets Data Scraping on a Recurring Basis?
Businesses can buy Event Data from Datamam and get the data via S3 Bucket, SFTP, Email, and REST API. Depending on your data requirements and subscription budget, Datamam can deliver this product in .json, .xml, .csv, .xls, .sql, .txt, and .bin format.
What is the data quality of Ticketmaster.com Tickets Data Scraping on a Recurring Basis?
Datamam has reported that this product has the following quality and accuracy assurances: 99.9% Quality Rate. You can compare and assess the data quality of Datamam using Datarade’s data marketplace. Datamam has received 5 reviews from clients. Datamam appears on selected Datarade top lists ranking the best data providers, including Best +8 Web Scraping APIs to use in 2023 and Best +8 Amazon Review APIs to use in 2023.
What are similar products to Ticketmaster.com Tickets Data Scraping on a Recurring Basis?
This product has 3 related products. These alternatives include Ticketmaster.com Events Information Scraping on a Recurring Basis, Dappier Breaking News Data RAG API, LLM Compatible Real-Time Updates Unlimited Data, and OpenWeb Ninja Public Event Data, Local & Online Events, Shows, Concerts, Sport Events, Workshops + More Google Events Global Real-Time API. You can compare the best Event Data providers and products via Datarade’s data marketplace and get the right data for your use case.