How AI Simplifies Product Category Harmonization

Mergers and acquisitions present numerous challenges in data integration, especially when multiple information systems need to be consolidated. Harmonizing product categories is a complex task as it involves aligning different nomenclatures and ensuring classification consistency. AI automates and secures this process, significantly reducing human errors and processing time.

Project Context

Our client, a major player in the distribution sector, had to merge two product databases after a strategic acquisition. The challenges were numerous:

• Two distinct structures: Each company used a PIM (Product Information Management) system with its own classification rules.
• Complex matching process: Many similar products were classified under different categories.
• Varying levels of granularity: Some categories were highly detailed, while others were broad, complicating the merging process.

Without an automated solution, harmonizing the categories would have required labor-intensive manual work with high risks of inconsistencies.

Challenges of Product Category Consolidation

Merging databases from different systems involves several difficulties:

1. Heterogeneous nomenclatures: Each company follows its own classification conventions.
2. Risk of duplicates and errors: Manual processing increases the chances of inconsistencies and misclassification.
3. High data volume: With over 3,000 categories to process, a traditional approach would be time-consuming and costly.

Artificial intelligence provides an effective solution by automating the analysis and grouping of categories according to precise criteria.

The AI Solution Implemented

We designed an AI-based solution in three key steps:

1. Advanced Semantic Analysis

Using natural language processing (NLP), we compared category descriptions and identified similarities.

2. Intelligent Category Matching

Our algorithms automatically matched categories from both PIM systems, leveraging similarity rules and logical groupings.

3. Automated Process Integration

Once the matches were validated, AI generated the new classification structure, ensuring a seamless and consistent integration.

Results Achieved

The benefits of this AI-driven approach were immediate:

• 90% time savings: Automation drastically reduced processing time compared to a manual approach.
• Error reduction: AI-powered matching ensured reliable and consistent data harmonization.
• 3,000 categories successfully harmonized: A unified classification structure was implemented, ensuring a smooth transition.

Why Use AI for Product Category Merging?

AI is a powerful tool for data integration during mergers and acquisitions:

• Automated repetitive tasks: Saves time and reduces operational costs.
• Increased consistency and reliability: Automatic classification alignment eliminates human errors.
• Scalability: Adaptable to any data volume and PIM structure.

Conclusion

Harmonizing product categories is a crucial challenge for companies dealing with database consolidations. Thanks to AI, our client successfully merged 3,000 categories quickly, accurately, and without excessive manual effort. This automated approach is replicable for any company looking to improve product data management and integration.

Are you planning a database merger or looking to optimize your product category management? Contact us to discover how AI can simplify your project!