AWS Media and Entertainment Australia

Ticketek

Marketing Personalization

Ticketek has been operating for 40 years, selling 30 million tickets annually. In 2020, Ticketek worked with Snowflake , an AWS Partner , to build a new data warehouse in the cloud for centralized access to customer data.

250% conversion rate uplift
49% boost in purchases for each email opened
5.2x diversity boost for featured products
And sales per email opened have jumped 49 percent with the new solution.

Reported impact

Business outcome

Now that Ticketek is recommending more events that people want to see, the company has increased the value of its newsletter for millions of people. Ticketek intends to keep finding ways to improve the customer experience by personalizing its website, mobile app, and text messages.

  • Customer Experience
  • Revenue Growth

Solution

Because Amazon Personalize targets customers more accurately, Ticketek is now giving a greater spotlight to smaller events. With the previous solution, the company primarily highlighted major events in its newsletters because they were more likely to sell out. However, more niche performances were often overlooked. Personalization changes that by matching fans with the events that excite them, no matter how small the events might be. Using Amazon Personalize, Ticketek has increased the diversity of its featured events by 5.2 times, creating opportunities for lesser-known artists to reach new audiences. And sales per email opened have jumped 49 percent with the new solution. After building out the solution, Ticketek ran A/B tests to assess the performance of the previous newsletter against the personalized newsletter.

Data flow

At the end of each day, its Snowflake data warehouse uploads data into the cloud on Amazon Simple Storage Service (Amazon S3)—an object storage solution.

Solution architecture

2 components · 2 layers
  1. Storage
    • Amazon S3 Stores source data, documents, or generated artifacts used by the personalization and recommendation workflows.
  2. Serving
    • Amazon Personalize Generates individualized recommendations for the personalization and recommendation workflows.

Architecture clues

  • At the end of each day, its Snowflake data warehouse uploads data into the cloud on Amazon Simple Storage Service (Amazon S3)—an object storage solution.

Evidence from the source

In 2020, Ticketek worked with Snowflake , an AWS Partner , to build a new data warehouse in the cloud for centralized access to customer data.
Three months later, Ticketek had a complete personalization solution that takes data from the Snowflake data warehouse and uses Amazon Personalize to generate batch recommendations showing the events that individual subscribers would most...
Ticketek has been operating for 40 years, selling 30 million tickets annually.
To deliver this project, Ticketek teams met with AWS to move from strategy to implementation.
To implement recommendations in newsletters, AWS integrated Amazon Personalize with intuitive customer engagement solution capabilities from Braze , also an .
Within 2 days, the company had a complete pipeline that preps and transforms Ticketek's data and makes it available for use by the Amazon Personalize service.
Transparency Evidence & methodology 100/100 reference value · 87% confidence · 1 source

Review how this reference was scored and trace each normalized claim back to its documented source.

01

Scoring methodology

How scores are calculated

Customer Reference Value measures usefulness as a customer reference. Evidence Confidence measures the quality and traceability of available evidence, not independent verification.

Customer reference value100/100
  • Problem clarity20/20
    Measures whether the customer's operational problem is specific enough to compare.
  • Implementation depth25/25
    Rewards named components, data flow, integrations, and architecture detail.
  • Outcome specificity20/20
    Measures whether the reported benefit is concrete rather than a generic claim.
  • Quantified impact25/25
    5 metrics describe measurable impact.
  • Deployment scale10/10
    Rewards evidence of a live or scaled deployment and meaningful integration scope.
Evidence confidence87%
  • Source authority20/25
    The main evidence is an official vendor-published customer story.
  • Claim traceability21/25
    10 of 12 key fields link to a named source.
  • Direct evidence20/20
    6 direct source quotes retained.
  • Date provenance8/10
    The publication date comes from publisher-controlled metadata.
  • Source transparency8/10
    1 source reference document publisher, URL, authority, retrieval, and supported fields.
  • Implementation specificity10/10
    Rewards source-backed components, data flow, quantified impact, and a specific outcome.
02

Traceability

Sources & provenance

Field coverage shows which facts each source supports. Dates are shown only when documented by the source.

  1. AWS

    Ticketek customer story

    First-party
    https://aws.amazon.com/solutions/case-studies/ticketek-amazon-personalize-case-study/
    Source type
    Vendor-published customer story
    Published
    Jan 1, 2024
    Supports
    • Customer
    • Business problem
    • Solution
    • Products
    • Solution components
    • Data flow
    • Integrations
    • technical area
    • use case category
    • Business outcome
    • outcome category
    • Metrics
    • Architecture
    • evidence quotes
    • Publication date

Date evidence

Not separately sourced Industry, Region, Company size. Treat these normalized attributes as lower-confidence until a dedicated source is added.