What challenges did Uswitch face before AI implementation?

Uswitch needed a more nimble data platform than its old on-premises Hadoop setup, which had performance and maintenance limitations. The business also needed to replicate data science outputs across multiple brands in the RVU group and personalize deal selection in a market with thousands of offers. Older tools and approaches were constraining iteration speed and customer experience improvements.

Source

GCPEvidence: Medium50/100

Uswitch: Customer segmentation and personalized deal recommendations with BigQuery and Vertex AI

Use case typeCustomer targetingUpdated Jun 13, 2026

Uswitch, part of RVU, uses Google Cloud to support data-driven customer experiences in a highly competitive price-comparison market spanning energy, personal finance, insurance, and communications. The company migrated from on-premises Hadoop-based data infrastructure to BigQuery and later used Vertex AI as part of its machine-learning and personalization workflow to better understand customer behavior and segment users for product recommendations. By combining BigQuery-based analytics with Vertex AI, Uswitch aimed to make data science products repeatable across RVU brands and to simplify the presentation of deal options for customers.

Organization: Uswitch
Industry: Retail
Location: United Kingdom
Published: June 2015

Reported outcomes

Time: −50%

Time & speed

Impact: Approximately 10×

Catalog median for time & speed deployments: −50% across 295 reported metrics. Compare benchmarks →

Why do we believe this?Outcome claims, sources, and evidence checks

Normalized claim

Time: 50% decrease

Google Cloud Customer StoryJun 19, 2015Customer storyInferred claimMedium evidence strength

Analytics lead time was reduced by 50%.

Normalized claim

Quantified impact: 10 x increase

Google Cloud Customer StoryJun 19, 2015Customer storyInferred claimMedium evidence strength

Uswitch doubled the richness of its data every two years and increased query volume roughly 10x.

Why do we believe this deployment?Customer identity, provider attribution, maturity, and source checks

Customer: Uswitch, RVU
Provider: GCP
Maturity: Unknown
Linked source: Google Cloud Customer Story

No explicit deployment-stage evidence found.

Customer identity supportedSource describes one deploymentMaturity evidence evaluated

Primary read

Use case focus

Showing 3 of 5

1Customer segmentation
2Personalization
3Recommendation system

Uswitch migrated its data platform to BigQuery and shifted from traditional ETL to ELT workflows.
The team used BigQuery for lifetime value modelling and customer segmentation, enabling data scientists to work directly against raw data.
Vertex AI was plugged into BigQuery as the main data source to support machine learning and to help create repeatable data science products across different architectures and brands.

Technologies

BigQuery Vertex AI ELT

Architecture

Uswitch moved from on-premises Hadoop clusters to Google BigQuery as its central data platform, adopted ELT-style data processing, and used Vertex AI connected to BigQuery as the primary data source for machine-learning and personalization workflows.

Sources & evidence1

Evidence: Medium50/100Evidence strength