List of Google Datastudio Customers
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Since 2010, our global team of researchers has been studying Google Datastudio customers around the world, aggregating massive amounts of data points that form the basis of our forecast assumptions and perhaps the rise and fall of certain vendors and their products on a quarterly basis.
Each quarter our research team identifies companies that have purchased Google Datastudio for Analytics and BI from public (Press Releases, Customer References, Testimonials, Case Studies and Success Stories) and proprietary sources, including the customer size, industry, location, implementation status, partner involvement, LOB Key Stakeholders and related IT decision-makers contact details.
Companies using Google Datastudio for Analytics and BI include: Deckers, a United States based Retail organisation with 5500 employees and revenues of $4.99 billion, CARS24, a India based Automotive organisation with 6000 employees and revenues of $660.0 million, Properati Argentina, a Argentina based Construction and Real Estate organisation with 30 employees and revenues of $3.0 million and many others.
Contact us if you need a completed and verified list of companies using Google Datastudio, including the breakdown by industry (21 Verticals), Geography (Region, Country, State, City), Company Size (Revenue, Employees, Asset) and related IT Decision Makers, Key Stakeholders, business and technology executives responsible for the software purchases.
The Google Datastudio customer wins are being incorporated in our Enterprise Applications Buyer Insight and Technographics Customer Database which has over 100 data fields that detail company usage of software systems and their digital transformation initiatives. Apps Run The World wants to become your No. 1 technographic data source!
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| Logo | Customer | Industry | Empl. | Revenue | Country | Vendor | Application | Category | When | SI | Insight |
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CARS24 | Automotive | 6000 | $660M | India | Google Datastudio | Analytics and BI | 2020 | n/a |
In 2020, CARS24 implemented Google Datastudio as part of an Analytics and BI stack during its Google Cloud migration. The deployment centered on Google Datastudio dashboards fed by BigQuery to surface customer behaviour across the companys ecommerce platform in India.
The implementation configured Google Datastudio to produce interactive dashboards and reports combining clickstream and GA360 data, enabling segmentation, funnel visualization, and trend analysis. BigQuery served as the centralized analytics warehouse with SQL based views and scheduled extracts to populate the Google Datastudio visualizations.
Integrations included direct ingestion of clickstream events and GA360 sessions into BigQuery, with dashboards delivering consolidated views for sales and marketing teams. The operational scope covered ecommerce product, growth, and marketing functions across CARS24 India, supporting campaign targeting and product iteration workflows.
Governance was established during the Google Cloud migration in 2020 with an emphasis on standardizing data models and dashboard templates to ensure consistent metrics. The Google Datastudio implementation provided an overview of customer behaviour that helped tailor campaigns and speed product iterations.
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Deckers | Retail | 5500 | $5.0B | United States | Google Datastudio | Analytics and BI | 2020 | Jellyfish |
In 2020, Deckers implemented Google Datastudio dashboards built by partner Jellyfish to surface creative insights for its marketing organization. The Google Datastudio implementation used Analytics and BI workflows to visualize Analytics 360 and BigQuery results, supporting cross brand campaign optimization for UGG, HOKA, and Teva across global markets.
The deployment architecture centralized reporting in Google Datastudio, pulling datasets from Analytics 360 and BigQuery to create role specific views for campaign managers and creative teams. Functional capabilities included campaign performance visualization, creative insight surfacing, and trend exploration, with dashboards configured to refresh data from BigQuery sources.
Operational scope covered marketing teams across Deckers brands and global regions, enabling coordinated campaign planning and optimization across brands. Jellyfish delivered the dashboards and supported configuration, enabling standardized reporting artifacts for cross brand campaign reviews.
The dashboards helped Deckers spot consumer trends during the COVID-19 period and contributed to improved campaign performance and higher return on ad spend. This implementation links Deckers, Google Datastudio, and Analytics and BI to marketing decision making and cross brand campaign orchestration.
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Properati Argentina | Construction and Real Estate | 30 | $3M | Argentina | Google Datastudio | Analytics and BI | 2016 | n/a |
In 2016, Properati Argentina implemented Google Data Studio as part of an Analytics and BI deployment alongside BigQuery to accelerate high speed analytics and make large property datasets queryable. The Google Data Studio deployment was positioned to serve both product analytics and public research use across Latin America with an Argentina focus, leveraging a BigQuery data layer for scale and performance.
The implementation configured Data Studio dashboards for reporting and interactive exploration of property listings and analytics, with datasets modeled and queried in BigQuery. Data publication used a catalog backed by BigQuery to expose curated datasets for public access and analytic consumption, while dashboards provided repeatable reporting surfaces for product teams and research users. Development workflows were centered on queryable datasets in BigQuery to accelerate feature delivery and analytic iteration.
Operational coverage emphasized product, analytics, and public research functions, with an Argentina-centered rollout and broader Latin America research reach. Governance relied on a catalog-driven publication pattern to manage which BigQuery datasets and Data Studio dashboards were published externally versus used internally. The platform explicitly improved development speed and enabled public data access via the catalog backed by BigQuery.
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