List of SAS Advanced Analytics Customers
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Since 2010, our global team of researchers has been studying SAS Advanced Analytics 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 SAS Advanced Analytics 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 SAS Advanced Analytics for Analytics and BI include: Db Insurance South Korea, a South Korea based Insurance organisation with 4479 employees and revenues of $13.51 billion, Ulta Beauty, a United States based Retail organisation with 20000 employees and revenues of $11.21 billion, Toyota Financial Services Italia (TFS Italia), a Italy based Banking and Financial Services organisation with 200 employees and revenues of $25.0 million and many others.
Contact us if you need a completed and verified list of companies using SAS Advanced Analytics, 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.
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| Logo | Customer | Industry | Empl. | Revenue | Country | Vendor | Application | Category | When | SI | Insight |
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Db Insurance South Korea | Insurance | 4479 | $13.5B | South Korea | SAS Institute | SAS Advanced Analytics | Analytics and BI | 2023 | n/a |
In 2023, Db Insurance South Korea implemented SAS Advanced Analytics, deploying SAS Fraud Decisioning for Claims on the SAS Viya platform as part of an Analytics and BI initiative to detect organized claims collusion networks across South Korea. The implementation moved the claims organization from reactive investigations to proactive, network based fraud detection across the insurer's claims lifecycle.
The SAS Advanced Analytics deployment was configured to support network analysis, automated scoring workflows, and decisioning rule execution focused on collusive behavior. Functional capabilities emphasized entity link analysis, case prioritization and automated triage to surface high risk claim clusters for investigator review.
Deployment architecture used SAS Viya as the analytics engine and embedded SAS Fraud Decisioning for Claims into claims operations and investigation workflows. Operational scope covered the nationwide claims team in South Korea, integrating analytics into claim intake, routing and investigator casework to enable continuous network monitoring.
The implementation shortened analysis time from hours to about two minutes, improved detection accuracy by approximately 99 percent, and enabled the claims team to process roughly 30 times more cases. These outcomes supported a shift to network based detection workflows and higher throughput in claims review.
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Toyota Financial Services Italia (TFS Italia) | Banking and Financial Services | 200 | $25M | Italy | SAS Institute | SAS Advanced Analytics | Analytics and BI | 2024 | n/a |
In 2024, Toyota Financial Services Italia implemented SAS Advanced Analytics in the Analytics and BI category, deploying SAS Viya including Visual Analytics, Visual Statistics and SAS Studio to centralize fragmented customer and CRM data and to build predictive models for customer retention, personalization and lending decisions across Italy. The deployment targeted customer data consolidation and analytical model development to support financing and leasing offers for Toyota Financial Services Italia, aligning analytics and business function needs within the Analytics and BI domain.
The implementation configured SAS Viya components to support end to end analytics workflows, using Visual Analytics for reporting and self service dashboards, Visual Statistics for model development and predictive scoring, and SAS Studio for data preparation and analyst notebooks. The architecture consolidated disparate customer and CRM datasets into a centralized analytic environment, enabling data profiling, feature engineering and model iteration within the same SAS Advanced Analytics platform.
Integrations focused on ingesting and harmonizing CRM and customer data sources across the organization, feeding downstream scoring and decision support for marketing, credit decisioning and customer retention teams. Operational coverage included financing and leasing business functions in Italy, with SAS Premium Support services engaged to support the transformation and stabilization of analytics operations.
Governance activities centered on establishing centralized analytics governance, standardizing model development and validation workflows and formalizing productionization handoffs for scoring and personalization use cases. The project improved customer understanding and personalization for financing and leasing offers, while consolidating analytic capabilities under the SAS Advanced Analytics environment in the Analytics and BI category.
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Ulta Beauty | Retail | 20000 | $11.2B | United States | SAS Institute | SAS Advanced Analytics | Analytics and BI | 2021 | n/a |
In 2021 Ulta Beauty implemented SAS Advanced Analytics as part of an Analytics and BI initiative to centralize marketing intelligence for its loyalty program and omnichannel campaign execution in the United States. The deployment emphasized customer level data consolidation and model driven campaign orchestration, positioning SAS Advanced Analytics to support marketing decision workflows and personalized engagement across channels.
Ulta Beauty uses SAS Customer Intelligence 360 to unify vast first party data and to operationalize recommendation models and campaign decisioning. Configurations focused on building unified customer profiles, AI driven recommendation engines, and automated campaign decision logic to drive personalized messages for loyalty members and omnichannel shoppers.
Operational coverage centered on marketing and loyalty management functions across the United States, ingesting first party data from digital and store touch points to feed analytics and decisioning. Integrations are oriented around data consolidation and campaign activation pathways, enabling the analytics outputs to be consumed by omnichannel campaign systems and loyalty program workflows.
Governance changes included centralizing campaign decisioning and embedding model outputs into marketing automation workflows to standardize personalization rules and reduce manual segmentation. Outcomes reported by Ulta include stronger customer engagement and sustained approximately 95% sales penetration from its loyalty members, attributed to the use of SAS Customer Intelligence 360 and SAS Advanced Analytics.
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