Decimal Point Analytics

Decimal Point Analytics is a company that provides data analytics, market research and automation services. Headquarters country: not specified. Regions of operation: not specified; client and project references imply work for organizations across multiple markets but specific regions are not stated.

Services and Capabilities

• Market research and competitive analysis — delivery of market sizing, segmentation studies, and research reports based on quantitative and qualitative data collection and analysis.
• Data analytics and business intelligence — development of data pipelines, dashboards, and reporting systems to transform raw data into operational and strategic metrics.
• AI and machine learning solutions — implementation of AI models and predictive analytics for forecasting, trend detection, and decision support.
• Automation and process optimization — design and deployment of automated workflows and integrations to reduce manual tasks and improve operational efficiency.
• Compliance and risk analytics — analytics and monitoring systems aimed at tracking compliance metrics, cost drivers, and profitability factors.
• Custom software and systems integration — building or integrating software components, APIs, and data platforms to enable end-to-end information flows.

Industry Focus

• Financial services — analytics for cost management, compliance monitoring, profitability analysis, and forecasting.
• Healthcare and life sciences — market research and data-driven decision support for product and market strategy (inferred from service descriptions consistent with market research applications).
• Retail and consumer goods — market sizing, consumer insights, and demand forecasting enabled by analytics and automation.
• Technology and software — integration of data platforms, AI models, and automation to support product analytics and operational processes.

Technology and Delivery Approach

• Emphasis on integrating AI, automation, and data analytics into unified solutions that connect data sources, analytics models, and reporting interfaces.
• Use of data platforms and pipelines to consolidate information, enable analytics, and produce operational dashboards and reports.
• Deployment of predictive models and machine learning for trend forecasting and decision support, combined with automation to operationalize insights.
• Delivery typically involves end-to-end services: analysis and research, model development, system integration, and ongoing reporting or monitoring.