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 Google Cloud. Open source.
Our Pricing Optimization Starter Kit is designed from the ground up for Google Cloud to efficiently leverage data processing, model development, and model management services provided by Google. The Vertex AI starter kit is completely open source, so it does not include any proprietary or licensable components.
AutoML under the hood
We use Google Cloud’s state-of-the-art capabilities to simplify the development and productization of pricing optimization solutions. In particular, we leverage AutoML capabilities provided by Google Cloud Vertex AI to automate model selection and parameter tuning.
Advanced modeling features
Our Google Cloud Pricing Optimization Starter Kit was created by price management and machine learning experts with extensive domain expertise in retail, manufacturing, and other industries. We incorporated many advanced techniques and best practices that are used by leading B2C and B2B companies.
AI pricing solution 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 Google Cloud?
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.
Google Cloud provides a powerful environment for development and productization of pricing optimization solutions. It helps to reduce development costs, release timelines, and the complexity of production operations.
Price management and optimization processes include many operations ranging from data collection to statistical modeling to customer-facing features. In GCP, the Pricing Optimization Starter Kit can be seamlessly integrated with your data lake, backoffice, and frontend services.
How it works
The Price Optimization Starter Kit that Grid Dynamics is unveiling today is an example of the innovation excellence upon which the company has built its reputation. This starter kit helps companies leverage the Vertex AI platform more efficiently and achieve compelling business results in a much quicker timeframe.
The Price Optimization Starter Kit that Grid Dynamics is unveiling today is an example of the innovation excellence upon which the company has built its reputation. This starter kit helps companies leverage the Vertex AI platform more efficiently and achieve compelling business results in a much quicker timeframe.
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