Retail — E-commerce Product Search Indexation Pipeline

Overview

The purpose of this DAG is to enhance the product search capabilities within the retail sector by integrating data from various sources such as ERP and CRM systems. The ingestion pipeline begins with the extraction of product data from these systems, ensuring that all relevant information is captured. Once ingested, the data undergoes a normalization process to standardize formats and eliminate inconsistencies. Following normalization, the data is indexed using advanced semantic search technique

The purpose of this DAG is to enhance the product search capabilities within the retail sector by integrating data from various sources such as ERP and CRM systems. The ingestion pipeline begins with the extraction of product data from these systems, ensuring that all relevant information is captured. Once ingested, the data undergoes a normalization process to standardize formats and eliminate inconsistencies. Following normalization, the data is indexed using advanced semantic search techniques, allowing for more accurate and context-aware search results. Quality control measures are implemented throughout the process to ensure the relevance and accuracy of the indexed data, including checks for data completeness and adherence to access permissions. The final outputs are made available through a dedicated search portal, where users can efficiently retrieve product information. Key performance indicators (KPIs) such as search response time, accuracy of search results, and user engagement metrics are monitored to evaluate the effectiveness of the indexing process. This DAG ultimately provides significant business value by improving the customer experience, increasing product discoverability, and driving sales through enhanced search functionality.

Part of the Literature Review solution for the Retail industry.

Use cases

• Enhances customer experience with relevant search results
• Increases product visibility leading to higher sales
• Reduces time spent on searching for products
• Improves data accuracy through normalization processes
• Facilitates better decision-making with actionable insights