Optimize retail margins with AI-driven dynamic pricing

Enables retailers to make faster, more profitable pricing decisions by combining rule-based logic, machine learning, and real-time market, sales, and competitor data. Designed for SAP-centric landscapes with integration to SAP S/4HANA and SAP Customer Activity Repository, leveraging master data, transaction history, and promotions. Pricing governance with centralized controls, approval workflows, and auditability while reducing manual effort.

Overview

Enhance customer consistency with unified pricing across channels

Delivers consistent and unified pricing across e-commerce and physical stores through a centralized SAP-powered pricing platform. Real-time competitor price inputs and margin-based rules ensure prices remain aligned across all customer touchpoints, while significantly reducing the need for manual price overrides.

Improve pricing control with a centralized governance framework

Provides a rule-based pricing approval framework that routes dynamic pricing decisions through defined approval workflows while leveraging SAP S/4HANA historical data for automated price recommendations. This improves pricing transparency, strengthens audit readiness, and enables localized pricing decisions without compromising central pricing governance.

Enhance margin performance with machine-learning-based pricing

Uses machine learning models trained on SAP S/4HANA sales data to forecast optimal pricing by category and region. Continuous retraining using controlled testing feedback improves pricing accuracy, supports better sell-through of seasonal inventory, and drives margin optimization across product portfolios.

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Details

Solution type

Extensions and Add-ons

Industry

Retail

Compatibility

Works with

This product is compatible with or enhances the functionality of these SAP solutions but doesn't require them.
SAP S/4HANA Cloud Public Edition, retail, fashion, and vertical businessSAP DatasphereSAP Markdown Optimization for RetailShow more

Features

Automate competitor price data collection

Extract data from Thunderbit to enable seamless downstream processing by leveraging Thunderbit connectors to efficiently pull both structured and unstructured data, while automating extraction workflows to improve ingestion speed, consistency, and overall data accuracy.

Automate competitor price data collection
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Build and train pricing models with Databricks

Trains pricing models using Databricks to deliver dynamic pricing recommendations at scale. Automated machine learning pipelines support continuous retraining, while optimized algorithms developed and deployed workflows enable ongoing pricing intelligence, adaptability to changing market conditions.

Build and train pricing models with Databricks
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Centralize pricing results in SAP Datasphere

Publishes pricing model outputs to Datasphere to provide centralized access and reporting. By integrating results generated in Databricks, the solution enables unified data consumption and delivers processed pricing insights that support faster, more informed business decision-making.

Centralize pricing results in SAP Datasphere
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Plans and pricing

Standard

Delivers end-to-end pricing traceability, including rule application, data inputs, and model outputs. This enables stronger pricing transparency and supports audit and compliance requirements.

Price unavailable in this region

Delivers end-to-end pricing traceability, including rule application, data inputs, and model outputs. This enables stronger pricing transparency and supports audit and compliance requirements.

Technical Information

Solution type Extensions and Add-ons
Category Quote-to-Cash Management
Industry Retail
Works with
  • SAP S/4HANA Cloud Public Edition, retail, fashion, and vertical business
  • SAP Datasphere
  • SAP Markdown Optimization for Retail

Resources

Dynamic Pricing Demo for SAP Retail

AI-Based Dynamic Retail Pricing Overview

AI driven dynamic pricing whitepaper

Publisher