Forecasting consumer market share with SAP HANA Cloud and SAP Analytics Cloud

Improve market share forecasting accuracy and visibility using SAP HANA Cloud and SAP Analytics Cloud

Business analysts work closely with sales and marketing to help establish strategies through market share analysis.

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Improve accuracy of market share prediction with advanced machine learning models

Establish a sustainable analytical process to accelerate data-driven innovation and analyze market share patterns to develop more segmented, differentiated marketing strategies. A shift toward a strategic approach is based on granular insights, simplified access to market share information by an extended user group, and an architectural blueprint that can be reused for other analytics use cases.

  • Reduced manual work for extracting and reporting forecasting value

  • Optimized forecasting cycle

  • Improved forecasting accuracy

  • High accuracy prediction through advanced machine learning intuitive dashboards to communicate in real time

Why use SAP Business Technology Platform

Elevate data and analytics insights with new predictive capabilities to quickly identify trends and sales flow.

Accelerate data-driven innovation

Machine learning technology and predictive analytics improve market share forecasting accuracy and enable segmentation analysis.

  • SAP HANA Cloud offers a single database-as-a-service foundation for modern applications and analytics across enterprise data.
  • SAP Analytics Cloud enables integrated planning and analysis processes.
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Value-driven results

To gain a holistic view of its equipment, this SAP oil and gas customer used machine learning and predictive analytics using SAP HANA Cloud and SAP Analytics Cloud to achieve.

Gaining accuracy in understanding historical and future measurements

In the oil and gas industry one customer used SAP HANA Cloud, application development services from SAP BTP, and SAP Analytics Cloud to build predictive models for abnormal events based on sensor data and to provide the results through user-friendly dashboards and e-mail notifications. It achieved up to 77% accuracy for explaining abnormal events based on historical data and up to 70% accuracy for predicting future sensor measurements using root-cause analysis and time-series analysis, respectively.

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SAP Discovery Center offers your developers and IT teams the comprehensive implementation information needed to run this use case.

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