Google Cloud Media and Entertainment Australia

Customedia

Data Lake / Data Warehouse Modernization · Real-time Analytics

With Google Cloud data and AI services, Customedia and Custom Analytics are aggregating data from client advertising platforms into a single source of truth and providing powerful data-driven insights to optimize advertising spend.

"We chose Gemini 3 Flash for its speed and cost-effectiveness and Gemini 3 Pro for its deep and rich analytics capabilities," says Santiago Moscatelli, Head of Analytics at Custom Analytics.

Reported impact

Business outcome

With Google Cloud, the organizations moved to a powerful, flexible, and integrated data stack and reduced data ingestion failures by 90%. Reliable access to data builds customer confidence and trust in the organizations, and positions them to step up the sale of existing and enhanced products to customers.

  • Customer Experience
  • Productivity Improvement

Solution

"The fundamental shift we've unlocked is a more robust, reliable solution that enables clients to have greater trust in what they're seeing and a profoundly greater ability to interrogate what they see," says Richard Warwick, head of digital at Customedia. "Our customers want to get under the hood to understand their data and generate their own reports and dashboards, and services such as Looker enable that." Meanwhile, Custom Analytics uses Gemini LLMs for powerful analysis of data from a range of platforms and to provide the resulting insights in plain language. Our customers want to get under the hood to understand their data and generate their own reports and dashboards, and services such as Looker enable that.

Solution architecture

5 components · 3 layers
  1. Compute
    • Gemini Provides the reasoning or generation layer used for classification, orchestration, content generation, or analysis.
    • Cloud Run Runs serverless application services and APIs with automatic scaling for bursty workloads.
  2. Storage
    • BigQuery Serves as the governed analytics and storage layer for high-volume operational data, features, and reporting.
    • Cloud Storage Stores source documents, media, or raw files that feed the automated workflow.
  3. Serving
    • Looker Serves dashboards, governed metrics, or natural-language analytics on top of the shared data model.

Architecture clues

  • In addition, the robust security and data controls within Google Cloud enable Customedia and Custom Analytics to meet customer requirements to manage access to certain types of data and retain it in certain locations for governance and compliance.

Evidence from the source

"The fundamental shift we've unlocked is a more robust, reliable solution that enables clients to have greater trust in what they're seeing and a profoundly greater ability to interrogate what they see," says Richard War
Democratizes the ability to query data with natural language on Looker
Improves customer experience with data ingestion failures cut by 90% with BigQuery
Meanwhile, Custom Analytics uses Gemini LLMs for powerful analysis of data from a range of platforms and to provide the resulting insights in plain language.
Our customers want to get under the hood to understand their data and generate their own reports and dashboards, and services such as Looker enable that.
Transparency Evidence & methodology 80/100 reference value · 77% 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 value80/100
  • Problem clarity20/20
    Measures whether the customer's operational problem is specific enough to compare.
  • Implementation depth15/25
    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 impact15/25
    1 metric describe measurable impact.
  • Deployment scale10/10
    Rewards evidence of a live or scaled deployment and meaningful integration scope.
Evidence confidence77%
  • 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
    5 direct source quotes retained.
  • Date provenance0/10
    The publication date has no documented provenance.
  • Source transparency8/10
    1 source reference document publisher, URL, authority, retrieval, and supported fields.
  • Implementation specificity8/10
    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. Google Cloud

    Customedia customer story

    First-party
    https://cloud.google.com/customers/customedia
    Source type
    Vendor-published customer story
    Supports
    • Customer
    • Business problem
    • Solution
    • Products
    • Solution components
    • Data flow
    • Integrations
    • technical area
    • use case category
    • Business outcome
    • outcome category
    • Metrics
    • Architecture
    • evidence quotes

Date evidence

  • First archived Mar 13, 2026 · Internet Archive · Independent First Wayback Machine capture; confirms the page existed by this date, not when it was published.
    Open date source
  • Sitemap last modified Feb 19, 2026 · Google Cloud · Publisher metadata Publisher-reported modification timestamp; not a publication date.
    Open date source
Not separately sourced Industry, Region, Company size. Treat these normalized attributes as lower-confidence until a dedicated source is added.