Introduction

This learning path is designed for technical developers who need to gain insights into the technical infrastructure, configuration, concepts and development capabilities of Product Recommendations Accelerator package within Pricefx.

It will focus on the core and common tasks associated with developing Groovy logic and configuration of this module and highlight key components of the Product Recommendation Package for Configuration Engineers to build their technical comprehension for the configuration and customization of this Accelerator for customer requirement

Learning Prerequisites

Make sure you have the aspects below covered before moving on with this learning path.

• Product Recommendation Learning Path for All Audiences

• Price Optimization Core Learning Path for Configuration Engineers

Learning Synopsis

This learning path covers recommendation models, types, and calculations, equipping you with the knowledge to configure, manage, and optimize product recommendations in Pricefx. It explores model classes, recommendation types (upsell, downsell, brand, customer-based), and calculation steps (data preparation, similarity analysis, recommendation generation). It also presents recommendation management tools (Summary, Review, Add Manual) and evaluation processes to continuously improve recommendation performance.

Learning Outcomes

Core concepts and takeaways:

• Demonstrate a comprehensive understanding of the various recommendation model classes, recommendation types, and the flexibility in using them.

• Develop the technical skills to configure and manage the complex calculation steps involved in generating personalized product recommendations, including data preparation, similarity analysis, and recommendation type-specific algorithms.

• Leverage the recommendation management tools and interfaces to review, refine, and manually supplement the generated product recommendations.

• Acquire the ability to assess the effectiveness of the product recommendations, using the insights gained to continuously improve the recommendation capabilities.

• Apply the learned concepts and techniques to configure and deploy the Product Recommendation Accelerator in Pricefx.

Learning Journey

This learning path is separated into sections that provide a basic roadmap for building your knowledge and understanding of Product Recommendations.

The components in this path are designed to be experienced in a sequential order, as each subsequent level builds upon the knowledge acquired in the preceding learning path(s). This structured approach ensures that learners have the necessary foundation before progressing to more advanced concepts, optimizing your learning experience.

Product Recommendation Technical Overview

• Technical User Reference

  • Product Recommendation 2 Model Class

  • Recommendation Types

  • Optionality of Recommendation Types

  • Disabled Recommendations

  • Library

  • Definition Step

  • Configuration Step

Product Recommendation Steps

• Product Recommendations Steps

  • Calculation: DataPrep

  • Calculation: LoadSimilarityMetaTable

  • Calculation: LoadSimilarRecommendations

  • Calculation: LoadUpSellRecommendations

  • Calculation: LoadDownSellRecommendations

  • Calculation: LoadBrandRecommendations

  • Calculation: LoadProductRecommendations

  • Calculation: LoadCustomerRecommendations

  • Calculation: LoadSegmentRecommendations

  • Calculation: PostProcessing

  • Summary Tab

  • Review Recommendations Tab

  • Add Manual Recommendations Tab

  • Evaluation

Time commitment: For this path you should dedicate approximately 6 hours.