Optimization

The Optimization module provides a framework that helps you analyze and segment your business, optimize your product portfolio and improve pricing.

Optimization, which supports many data science techniques, performs data profiling and generates segment-specific optimized pricing and price guidance and delivers it to price lists, CPQ, Digital Commerce and ERP systems.

Structure

The Optimization module is highly configurable to meet various business needs. 

The main building blocks are:

• Pricing Guidance – Allows you to create a segmentation model or a product recommendation model.

• Model Classes – Allow you to build custom specific features, made of sequential steps that the user goes through. In each step, the user can run a calculation and then, in multiple tabs, work with interactive dashboards to explore the calculation results. A Model Class defines a user workflow based on logics and can use an engine, such as Optimization Engine, Market Simulation, or Python Engine.

  • Engines are a way for the Pricefx platform to run specialized calculations in a virtual environment and give back the results to the platform. Engines are used to run data science and optimization jobs.

• Models (MO) – Allow you to create many optimization scenarios based on a specific Model Class.

Note: Optimization Engine is the previous implementation of Model Classes and Models (MO).

The flow is as follows: Model Classes (or Model Types in the initial version of the Optimization module) bind together the logics and based on this class/type individual models are created. These models then process (with defined parameters) the specific datasets.

Available Configurations

Pricefx delivers several sample configurations which help you get started much quicker, such as:

• Pricing Guidance:

  • Segmentation

  • Product Recommendations

• Model Classes and Models (MO):

  • Optimization Engine

  • Market Simulation