Apps Purchases: 10+ Million Software Purchases
Founded in 2010, APPS RUN THE WORLD is a leading technology intelligence and market-research company devoted to the application space. Leveraging a rigorous data-centric research methodology, we ask the simple B2B sales intelligence question: Who’s buying enterprise applications from whom and why?
Our global team of 50 researchers has been studying the digital transformation initiatives being undertaken by 2 million + companies including technographic segmentation of 10 million ERP, EPM, CRM, HCM, Procurement, SCM, Treasury software purchases, 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.
Apps Run The World Buyer Insight and Technographics Customer Database has over 100 data fields that detail company usage of emerging technologies such as AI, Machine Learning, IoT, Blockchain, Autonomous Database, and different on-prem and cloud apps by function, customer size (employees, revenues), industry, country, implementation status, year deal won, partner involvement, Line of Business Key Stakeholders and key decision-makers contact details, including the systems being used by Fortune 1000 and Global 2000 companies.
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- Analytics and BI
| Logo | Customer | Industry | Empl. | Revenue | Country | Vendor | Application | Category | When | VAR/SI | Insight | Insight Source |
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Illinois Institute of Technology | Education | 1662 | $321M | United States | RSMeans Data Online | RSMeans Data Online Data Insights | Analytics and BI | 2020 | n/a | In 2020, Illinois Institute of Technology deployed RSMeans Data Online Data Insights to support construction estimating coursework. The implementation is categorized as Analytics and BI and used the RSMeans Data Online Student Edition to provide individual student access to current, localized cost data for academic estimating exercises. RSMeans Data Online Data Insights was provisioned to supply a cost database, localized cost adjustments, line item estimate construction and reporting capabilities, enabling students to build detailed estimates and capstone portfolios. Usage of RSMeans Data Online Data Insights is inferred from the Student Edition deployment, aligning analytics and estimating workflows with classroom assignments and portfolio deliverables. The rollout focused on academic programs teaching construction estimating in the United States, with instructor provisioning and student access controls integrated into coursework and capstone validation processes. Explicit outcomes reported include improved student preparedness for professional estimating roles and faster estimate validation during coursework and project review. | |
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Georgia-Pacific | Manufacturing | 30000 | $7.5B | United States | SAS Institute | SAS Model Manager | Analytics and BI | 2020 | n/a | In 2020, Georgia-Pacific implemented SAS Model Manager as part of a SAS Viya on AWS deployment to manage, deploy and monitor large numbers of machine-learning models that optimize manufacturing and supply-chain processes. The implementation is categorized under Analytics and BI, and SAS Model Manager serves as the central model lifecycle platform supporting model registration, deployment orchestration and runtime monitoring across operational pipelines. The deployment architecture leveraged SAS Viya on AWS, with SAS Model Manager providing a centralized model repository, model versioning and automated monitoring capabilities. The environment was configured to handle IoT-driven predictive maintenance workflows, ingesting sensor and equipment telemetry for online scoring and batch inference, and to operationalize models for supply-chain optimization and production scheduling. Operational coverage focused on US manufacturing sites and supply-chain functions, with business functions including plant operations, maintenance engineering and supply-chain analytics using the SAS Model Manager. Governance practices were enacted for model monitoring and post-deployment validation, including workflows for detecting model drift and triggering retraining or remediation. The program delivered measurable reductions in unplanned downtime and improvements in equipment efficiency through IoT-driven predictive maintenance and continuous model monitoring. | |
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Media | 4574 | $5.7B | United States | Sensor Tower | Sensor Tower | Analytics and BI | 2020 | n/a |
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Construction and Real Estate | 687 | $150M | United States | Sensera Systems | SiteCloud | Analytics and BI | 2020 | n/a |
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Oil, Gas and Chemicals | 1045 | $162M | India | Microsoft | Microsoft Power BI | Analytics and BI | 2020 | n/a |
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Professional Services | 1800 | $1.4B | United States | Sirdata | Sirdata Audience Insights | Analytics and BI | 2020 | n/a |
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Insurance | 70 | $10M | United Kingdom | Sistrix | Sistrix Platform | Analytics and BI | 2020 | n/a |
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Manufacturing | 80 | $7M | Germany | Sistrix | Sistrix Platform | Analytics and BI | 2020 | n/a |
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Leisure and Hospitality | 35574 | $7.9B | United States | ThoughtSpot | Mode Analytics | Analytics and BI | 2020 | n/a |
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Leisure and Hospitality | 50000 | $11.2B | United States | UrVenue | UrVenue Insights | Data Warehouse | 2020 | n/a |
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