Taxonomy: From Classical Roots to Modern Application
The concept of taxonomy has deep historical roots, originating from humanity’s earliest attempts to bring order to the natural world. Ancient philosophers like Aristotle laid the groundwork by classifying living organisms based on observable traits, while Carl Linnaeus later formalized this practice in the 18th century through his hierarchical system and binomial nomenclature. These foundational efforts enabled scientists to communicate more precisely and understand complex biological relationships, establishing taxonomy as a cornerstone of scientific inquiry and organization. Today, that same structured thinking underpins modern product and retailer taxonomies, where clear classification systems are essential for searchability, discoverability, and operational efficiency across digital commerce platforms. As Confucius once said, “The beginning of wisdom is to call things by their proper name,” a principle that remains just as relevant in today’s data-driven economy.
The Evolving Role of AI in B2B E-Commerce
Data is the backbone of B2B e-commerce, powering everything from seamless transactions to supply chain optimization. Yet, as businesses scale globally, managing and standardizing vast amounts of product and retailer taxonomy becomes increasingly complex. Variations in product descriptions, regional language differences, and inconsistent retailer classifications create inefficiencies that hinder analytics, decision-making, and operational growth.
To remain competitive, organizations are embracing Generative AI (GenAI) as a strategic enabler of data quality and efficiency. By harnessing large language models (LLMs) and multi-modal AI, and Compound AI architectures, businesses can automate taxonomy enrichment, enhance searchability, and unlock deeper insights—all at scale. The result? A more intelligent, streamlined approach to data management that drives better business outcomes.
Background: Inconsistent taxonomy in B2B E-Commerce
A global leader in brewing, a multinational beverage company’s B2B platform connects retailers and businesses with a diverse portfolio of consumer goods, including beverages, snacks, and packaged foods. Operating at this scale requires a robust, data-driven approach to ensure seamless transactions, optimized supply chains, and enhanced business intelligence.
However, inconsistent and incomplete product (SKU) and retailer taxonomy became a growing challenge as the company’s B2B platform expanded. Data sourced from external partners and third-party entities often contained variations in brand names, item descriptions, and taxonomy levels, resulting in non-standardized and misformatted taxonomy. Additionally, regional language differences, slang, and manual input errors caused discrepancies in retailer classifications across markets.
These inconsistencies hindered analytics, limited predictive modeling capabilities, and slowed operational scalability. Without high-quality taxonomy, the major international beverage manufacturer faced challenges in:
- Extracting meaningful insights to drive business decisions
- Standardizing product taxonomy for improved searchability and classification
- Optimizing supply chain and marketing efforts with reliable data
- Scaling data-driven initiatives to support global operations
Recognizing the potential for AI-driven transformation, the multinational beverage manufacturer partnered with Lovelytics to conduct a Proof of Concept (POC) focused on automating taxonomy enrichment and standardization using Generative AI (GenAI). Leveraging Large Language Models (LLMs) within their Azure and Databricks environments, the project aimed to demonstrate the feasibility of a scalable AI-powered solution that would improve taxonomy quality, enhance analytics, and streamline operations.
Solution
Lovelytics implemented a GenAI-powered solution to automate, standardize, and enrich SKU and retailer taxonomy. Using LLMs hosted in the organization’s Azure environment and integrated with the Databricks Data Intelligence platform, the solution delivered scalable and automated taxonomy enrichment.
- Data Analysis: Analyzed SKU and retailer data to identify gaps and define taxonomy fields.
- Context Engineering: Developed tailored context and prompts for structured taxonomy outputs, improving operational efficiency and decision-making.
- Compound AI Architecture: Designed a scalable AI framework integrating LLMs, third-party APIs, internal tools, and Delta tables for context enrichment.
- Multi-Modal LLMs: Enabled analysis of textual data, storefront images, and product packaging to extract product attributes like packaging, flavor, and retailer category, enhancing taxonomy accuracy and searchability.
- Batch Processing & Scalability: Used PySpark for large-scale data preparation and batch processing, ensuring efficient handling of high-volume datasets.
- Validation & Quality Assurance: Implemented rigorous validation against client-provided ground truth to ensure taxonomy accuracy, consistency, and reliability.
Technologies Powering AI-Driven Taxonomy Enrichment
Lovelytics leveraged the Databricks Data Intelligence Platform, Azure OpenAI LLMs for
automated classification, taxonomy enrichment, multimodal analysis and Mosaic AI for integrating multi-modal AI workflows. PySpark and Delta Tables ensured efficient handling of high-volume datasets, while MLflow and Unity Catalog provided robust model management and governance. Additionally, Azure Maps and Google Streetview APIs enriched retailer taxonomy with location-based insights, enhancing classification accuracy.
By leveraging AI-powered automation, scalable cloud infrastructure, and high-performance data processing, the Fortune 500 company successfully enhanced taxonomy accuracy, improved analytics, and unlocked operational efficiencies. This cutting-edge technology stack empowered the company to scale seamlessly, optimize decision-making, and drive business growth in the competitive B2B e-commerce space.
AI-Powered Automation Unlocks Operational Efficiency
The implementation of the GenAI solution significantly enhances the organization’s taxonomy management capabilities, driving measurable improvement. For product taxonomy, the solution achieved approximately 90% accuracy, enabling enhanced analytics and modeling across the SKU dataset. The retailer taxonomy generation successfully produced an initial classification structure, laying the groundwork for further refinement and scalability. These outcomes improved the ability to standardize and enrich taxonomy, supporting better decision-making and operational efficiency.
Conclusion
The successful deployment of Generative AI for taxonomy enrichment—led by Lovelytics in collaboration with the major international beverage manufacturer —has not only improved product taxonomy accuracy by 90% but also established a scalable framework for future AI-driven innovations. By leveraging LLMs, multi-modal AI, and the Databricks Data Intelligence Platform, the company has significantly enhanced taxonomy quality, streamlined operations, and strengthened analytics capabilities. Looking ahead, the organization, with Lovelytics as a strategic AI partner, is poised to expand its AI initiatives beyond taxonomy management, unlocking new opportunities such as automated real-time taxonomy updates, intelligent product recommendations, and AI-powered supply chain optimization.
By integrating cutting-edge AI solutions into its data strategy, the Fortune 500 beverage company, and Lovelytics are not just improving operations today—they are building an intelligent, scalable foundation for the future of B2B e-commerce innovation. This transformation sets a new benchmark for how businesses can harness AI to drive efficiency, data-driven decision-making, and long-term growth in a competitive global market.
Ready to unlock the power of GenAI for your business? Lovelytics delivers cutting-edge GenAI solutions tailored to automate workflows, enhance data quality, and unlock deeper business insights. Whether you’re looking to streamline operations, improve decision-making, or scale AI-driven innovation, our expertise can help you turn complex data challenges into actionable opportunities. Contact us today to explore how GenAI can transform your business.
