Product Information Management (PIM)

Turning raw product data into accurate, enriched, and consistent content across every channel.

Introduction

In this case study, I display my complete product information management process using a women’s tassel loafer family as the example dataset. I modeled the work on Akeneo PIM practices to show how raw vendor data is cleaned, enriched, structured, and prepared for different sales channels.

The purpose of this case study is to demonstrate my ability to design scalable schemas, normalize messy input data, enforce governance rules, and connect upstream and downstream systems. This work highlights the real business value of product information management: accuracy, consistency, and readiness for e-commerce scale.

Schema Design

This schema defines the key attributes required to manage a women’s tassel loafer family in Akeneo PIM. I marked core fields as required (such as brand, material, size, and GTIN) and separated optional or localizable attributes (such as description and care instructions). This structure establishes a consistent foundation for enrichment and ensures that every product variation meets completeness rules.


Table 1. Attribute Schema for Tassel Loafers

Product Model Structure

This schema diagram models a women’s tassel loafer family in Akeneo. Common attributes such as name, brand, description, care instructions, warranty, and gender are defined at the Product Model level. Variation is then managed in two layers:

  • Sub-Product Models capture material, width, and color.

  • Variant Products capture size, price, identifiers, and images.

This structure reduces redundancy, enforces data quality, and demonstrates how catalog teams manage complex assortments across attributes and channels.

Figure 1. Product Model Diagram in Akeneo PIM

Enrichment Workflow

This workflow shows how product data moves through structured stages of enrichment. I mapped roles, responsibilities, and validation rules — for example, the marketing team owns descriptions, operations validates GTINs, and governance checks completeness. This ensures that product data flows smoothly without gaps or duplicates.


Table 2. Enrichment Workflow in Akeneo PIM

Notes

• Letters (A–F) indicate output states (e.g., A = channel-ready, B = export-ready).

• Gate numbers (0–3) indicate workflow stages where tasks and criteria are reviewed before moving forward.

Channel Syndication

This table illustrates how enriched product data from Akeneo is adapted for different sales channels. Each channel — Amazon, Shopify, and Walmart — has unique rules for titles, attributes, and identifiers. I mapped how the same product information is transformed to meet these requirements, demonstrating readiness for multi-channel syndication.


Table 3. Channel Mapping Matrix

Import and Export

This section demonstrates how I modeled the transformation of a raw vendor feed into a cleaned, enriched dataset based on Akeneo’s product information management practices. The objective was to show how bulk product imports can be normalized, validated, and prepared for publication.

Table 4a presents the raw vendor feed, which contains messy inputs, inconsistent naming, missing identifiers, and broken image references. Table 4b shows the enriched dataset, where attributes are standardized, values are normalized, GTINs are validated, and care instructions and pricing are made consistent.

By comparing these two datasets, I highlight the practical steps of preparing bulk product data using product information management principles. This process ensures data quality before exports are generated for different sales channels.


Table 4a. Raw Vendor Feed (Pre-Enrichment)

Table 4b. Enriched Dataset (Modeled on Akeneo Practices)

ERP Integration

This table illustrates how upstream enterprise resource planning fields (such as vendor ID, material code, and net price) map into Akeneo PIM attributes. By showing these connections, I demonstrate my ability to align PIM with enterprise systems and ensure product data is ready for integration across business platforms.


Table 5. ERP to PIM Mapping Example

Conclusion

Through this case study, I demonstrate my skills in managing product data end to end within Akeneo PIM. I modeled a schema, enforced enrichment workflows, mapped channel outputs, and connected ERP inputs. This shows how raw, inconsistent data can be transformed into accurate, structured, and channel-ready product content. It reflects the practical, hands-on capabilities required for catalog, taxonomy, and merchandising roles.