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.
Apply Filters For 10+ Million Software Purchases
- Professional Services
| Logo | Customer | Industry | Empl. | Revenue | Country | Vendor | Application | Category | When | VAR/SI | Insight | Insight Source |
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Volume Ltd | Professional Services | 150 | $20M | United Kingdom | IBM | IBM Watson Studio (ex IBM Data Science Experience) | ML and Data Science Platforms | 2015 | n/a | ||
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COYOTE | Professional Services | 240 | $119M | France | Dataiku | Dataiku Data Science Studio (DSS) | ML and Data Science Platforms | 2017 | n/a | In 2017, Coyote implemented Dataiku Data Science Studio (DSS) in the ML and Data Science Platforms category to automate detection and correction of speed limit data used in its embedded maps. Coyote’s IoT fleet and mobile apps generate billions of anonymized rows of speed and position telemetry, creating a high volume data input that quality teams needed to analyze for map accuracy. The two companies already enjoyed a long-term relationship, in 2015 Coyote deployed a churn project developed using Dataiku Data Science Studio which validated broader application of predictive analytics to Coyote’s core product development. Using Dataiku Data Science Studio, Coyote implemented machine learning workflows to segment roads into sections and analyze driving patterns within each segment. The implementation included anomaly detection and predictive modeling capabilities that estimate the likely speed limit for a given road section. Data mining and visualization capabilities in the platform were adopted to surface anomalies and support iterative model refinement through collaborative project workspaces. Operational coverage focused on product quality and map accuracy workflows within Coyote’s quality teams and product development organization, leveraging the high volume IoT-derived dataset as the primary data source. Workflows were engineered to process billions of rows of anonymized telemetry and produce section-level predictions that feed downstream correction pipelines and quality assessment processes. The deployment reinforced a data driven decision model across the company, shifting decisions from standard analytics reports to model based evidence and automated correction outputs. Collaborative features in Dataiku Data Science Studio enabled employees with differing skill sets to participate in model development, review, and deployment, expanding data mining and visualization practices beyond central analytics teams. The implementation automated parts of the speed limit correction process and embedded governance checkpoints for quality validation before updates were applied to map feeds. Explicit outcomes reported by Coyote include a 9% increase in speed limit reliability on analyzed datasets and automation of the speed limit correction process. The project also contributed to a global data driven spirit within the company and increased customer loyalty. Dataiku Data Science Studio served as the platform enabling machine learning driven quality assurance for embedded map speed limits. | |
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Professional Services | 80 | $10M | France | Dataiku | Dataiku Data Science Studio (DSS) | ML and Data Science Platforms | 2017 | n/a |
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Professional Services | 700 | $135M | France | Dataiku | Dataiku Data Science Studio (DSS) | ML and Data Science Platforms | 2017 | n/a |
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Professional Services | 140 | $22M | Japan | Vertica | Vertica Analytics Platform | ML and Data Science Platforms | 2017 | n/a |
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Professional Services | 28000 | $5.5B | United States | Amazon Web Services (AWS) | Amazon SageMaker | ML and Data Science Platforms | 2017 | n/a |
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Professional Services | 18200 | $18.8B | United States | Amazon Web Services (AWS) | Amazon SageMaker | ML and Data Science Platforms | 2017 | n/a |
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Professional Services | 16500 | $13.7B | United States | Amazon Web Services (AWS) | Amazon SageMaker | ML and Data Science Platforms | 2017 | n/a |
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Professional Services | 50 | $6M | United States | Amazon Web Services (AWS) | Amazon SageMaker | ML and Data Science Platforms | 2016 | n/a |
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Professional Services | 200 | $20M | United States | Amazon Web Services (AWS) | Amazon SageMaker | ML and Data Science Platforms | 2016 | n/a |
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