List of SAS/STAT Customers
Cary, 27513-2414, NC,
United States
Since 2010, our global team of researchers has been studying SAS/STAT 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/STAT 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/STAT for Analytics and BI include: Verizon, a United States based Communications organisation with 99400 employees and revenues of $134.79 billion, Canadian Imperial Bank of Commerce (CIBC), a Canada based Banking and Financial Services organisation with 49824 employees and revenues of $21.30 billion, St. Jude Children's Research Hospital, a United States based Non Profit organisation with 5000 employees and revenues of $1.25 billion and many others.
Contact us if you need a completed and verified list of companies using SAS/STAT, 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 SAS/STAT 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!
Apply Filters For Customers
| Logo | Customer | Industry | Empl. | Revenue | Country | Vendor | Application | Category | When | SI | Insight |
|---|---|---|---|---|---|---|---|---|---|---|---|
 |
Canadian Imperial Bank of Commerce (CIBC) | Banking and Financial Services | 49824 | $21.3B | Canada | SAS Institute | SAS/STAT | Analytics and BI | 2014 | n/a |
In 2014, CIBC implemented SAS/STAT 9.2 procedures to ensemble domain expert intuition with multiple clustering models for customer profiling and text and structured data segmentation in Canada. The deployment used SAS/STAT as part of the bank's Analytics and BI toolset to support customer analytics and marketing analytics use cases.
The implementation centered on SAS/STAT procedures for clustering and model ensembling, combining outputs from multiple unsupervised models to create more robust segment definitions. The work explicitly integrated text segmentation with structured customer attributes to produce composite profiles, emphasizing reproducibility and interpretability of segment assignments.
Operational scope focused on Canadian customer populations and marketing analytics teams, with collaboration between domain experts and analytics practitioners to tune cluster definitions and validate business meaning. Documentation and reproducible workflows were published as a SAS Global Forum paper, providing the governance artifact linking methodology, model configuration, and interpretation practices.
Outcomes reported in the SAS Global Forum presentation included improved discovery of similar customer groups for marketing analytics and demonstrated gains in segmentation reproducibility and interpretability through the SAS/STAT based ensemble approach.
|
 |
St. Jude Children's Research Hospital | Non Profit | 5000 | $1.3B | United States | SAS Institute | SAS/STAT | Analytics and BI | 2015 | n/a |
In 2015 St. Jude Children's Research Hospital deployed SAS/STAT within its Analytics and BI environment to support advanced biostatistical workflows for longitudinal clinical studies in the United States. The deployment centered on the SAS/STAT application and its procedural analytics capabilities to standardize structural equation modeling and longitudinal analysis for clinical researchers.
Implementation work emphasized procedures such as PROC CALIS and related SAS/STAT procedures for structural equation modeling, longitudinal data analysis, and growth-curve modeling. Configurations focused on reproducible statistical scripts and procedure-level parameterization to handle missing data robustly and to support longitudinal model specification and estimation workflows.
Operational scope included biostatistics and clinical research teams across St. Jude, where SAS/STAT was used as the analytic engine for patient-level longitudinal studies and hypothesis testing. The analysis and methodology were published and presented at SAS Global Forum 2015, which documented the implementation patterns and illustrated SAS/STATs role in biostatistics for longitudinal clinical studies.
The published work emphasized methodological rigor, showing that SAS/STAT enabled robust handling of missing data and supported growth-curve modeling in clinical research, reinforcing its placement in the institution's Analytics and BI toolset and informing analytic standards and peer-reviewed dissemination practices.
|
 |
Verizon | Communications | 99400 | $134.8B | United States | SAS Institute | SAS/STAT | Analytics and BI | 2016 | n/a |
In 2016, Verizon implemented SAS/STAT in an Analytics and BI capacity to build customer lifetime value and churn models for CRM and marketing analytics in the United States. The implementation focused on statistical model development for customer behavior and credit management rather than application hosting or transactional systems.
The deployment used SAS/STAT procedures LOGISTIC, PHREG, and ROBUSTREG to develop logistic regression for binary outcomes, discrete time survival analysis for churn timing, and robust regression for LTV estimation and heteroskedastic data. SAS/STAT was used to construct end to end model workflows including variable selection, model estimation, and scoring datasets for downstream CRM use.
Operational scope covered CRM and marketing analytics functions, with models applied to credit-limit management and client behavior analytics across Verizon US customer segments. Modeling outputs were positioned to inform targeted retention and risk assessment processes within marketing and credit operations.
Findings and methodology were documented in a SAS Global Forum 2016 poster and paper, demonstrating SAS/STAT application to LTV estimation and business outcomes such as risk prediction and targeted retention. The presentation highlights the use of SAS/STAT as a statistical modeling layer within Verizon Analytics and BI to support predictive analytics for customer lifecycle management.
|
Buyer Intent: Companies Evaluating SAS/STAT
Discover Software Buyers actively Evaluating Enterprise Applications
| Logo | Company | Industry | Employees | Revenue | Country | Evaluated | ||
|---|---|---|---|---|---|---|---|---|
| No data found | ||||||||