Introduction

This learning path is designed for individuals who need to gain a basic understanding of the Multifactor Elasticity Accelerator and illustrate how it uses machine learning to forecast demand and assess price elasticity and assist in forecasting quantity that would be sold at a given price.

This learning path will discuss the core concepts, functions, and features of the Multifactor Elasticity Accelerator from a high-level viewpoint and will serve as the foundational knowledge for the additional learning paths in this series.

Learning Prerequisites

Make sure that you have these aspects covered before moving on to the course:

• About Pricefx

• Pricing Basics

• Pricing Concepts

• Pricing Terminology

• Accelerator Overview

• Price Optimization Core Learning Path for All Audiences

Learning Synopsis

This learning path will delve into the functionalities of the Multifactor Elasticity Accelerator from a business user's perspective. It will emphasize the projected quantity and elasticity parameter outcomes of the Multifactor Elasticity model. The content will highlight the robust machine learning methodology used to evaluate elasticity within a forecasting model and the features enabling the prediction of the quantity to be sold at a specified price.

Learning Objectives

Core topics and takeaways:

• Highlight the goals and objectives of Multifactor Elasticity Accelerator for business users.

• Understand the step-by-step process for instantiating the machine learning model.

• Define the steps for running our calculation and initiate the training of the elasticity model.

• Illustrate the outputs from this Accelerator and the generated charts that check outputs, such as demand forecast per product, the elasticity curves built from these forecasts and an evaluation of the metrics.

Learning Journey

This learning path for the Multifactor Elasticity Accelerator is divided into multiple topics and each one is designed to be experienced in a sequential order, as each subsequent level builds upon the knowledge acquired in the preceding content.

This structured approach ensures that learners have the necessary foundation before progressing to more advanced concepts, optimizing the learning experience and maximizing the effectiveness of using the Multifactor Elasticity Accelerator.

Multifactor Elasticity Basics

• Overview

• Elasticity Model

  • Add Model

  • Define Data Source

  • Model Configuration

• Additional Sources

• Model Training

  • Start Model Training

  • Training Results

  • Elasticity Settings

• Model Predictions

  • Train Final Forecast

  • Charts and Tables Results

  • Predicted Elasticity

Time commitment: For this path you should dedicate approximately 1 hour.