Features
End-to-end pipeline
We created reference implementations for all major steps of the pricing optimization pipeline including data preparation, demand forecasting, and various optimization scenarios such as end-of-season sales.
Power of Microsoft Azure. Open source.
Our Pricing Optimization Starter Kit is designed from the ground up for Microsoft Azure to efficiently leverage data processing, model development, and model management services provided by Microsoft. The starter kit is completely open source, so it does not include any proprietary or licensable components.
AutoML under the hood
We use Microsoft Azure’s state-of-the-art Automated ML capabilities to simplify the development and productization of pricing optimization solutions, leveraging built-in capabilities such as easy data exploration, automatic preprocessing, and intelligent feature engineering using deep neural networks to improve model scores.
Advanced modeling features
Our Microsoft Azure Pricing Optimization Starter Kit was created by price management and machine learning experts with extensive domain expertise in retail, manufacturing, and other industries. We incorporate many advanced techniques and best practices that are used by leading B2C and B2B companies.
AI pricing solutions use cases
Data-driven price optimization
Promotion optimization
End-of-season sell-through optimization
Dynamic pricing
Demand decomposition and analysis
Cannibalization analysis
Industries
Promotions and end-of-season clearance campaigns can be optimized through continuous sales progress tracking and data-driven price adjustments. ML models can be used for both long-term planning (e.g. 52 weeks-ahead) and ongoing adjustments on a weekly basis.
New product pricing and assortment decisions can be optimized through demand forecasting and product similarity models. ML models can be modified to help optimize pricing decisions in early stages of the product life, and to evaluate demand shifts induced by adding or removing items to the assortment.
Granular short-term demand forecasting at the store level can be used to improve inventory movement from backroom to frontroom. The forecasting solutions are typically integrated with hand-held devices used by store associates to provide instructions on how many units of which items need to be moved.
Demand forecasting pipelines can be used to optimize inventory replenishment decisions based on granular store-level and SKU-level forecasts. Typical objectives include maximizing inventory turnover and improving storage and logistics efficiency.
Why develop a pricing optimization solution in Microsoft Azure?
Custom-built price and revenue management solutions driven by AI empower your company with the freedom to innovate and build a competitive edge. Create unique capabilities at lower cost and greater speed than competitors using third-party software.
Microsoft Azure provides a powerful environment for development and productization of price optimization solutions. It helps to reduce development costs, release timelines, and complexity of production operations.
Price management and optimization processes include many operations ranging from data collection to statistical modeling to customer-facing features. In Microsoft Azure, the Pricing Optimization Starter Kit can be seamlessly integrated with your data lake, backoffice, and frontend services.
How it works
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