Data Enrichment and Centralization in Digital Retail

In today’s competitive digital landscape, centralizing product data is essential for companies that handle large volumes of information. However, while this centralization is important, it brings a series of challenges—especially regarding data integrity and quality. Product catalogs can become chaotic without a solid structure and the right tools, leading to inconsistencies, duplication, and a lack of essential details. This is where data enrichment emerges as an indispensable solution.

The Challenges of Data Centralization

The goal of product data centralization is to consolidate all information into a single system, making it easier to manage large databases. However, frequent complications arise as the number of products, categories, and specifications increases. The lack of standardization, for example, can hinder data integration and increase the risk of errors during manual data entry.

Another critical issue is that most internal systems are not designed to keep up with the fast-paced nature of digital retail. Updating product records with detailed information—such as attributes, images, and e-commerce-optimized descriptions—can become a bottleneck. This impacts the final customer experience, which heavily depends on accurate data to make purchasing decisions.

In this context, Fabiola Santana, CEO of Umami, highlights:
“At Umami, we tackle these challenges with a focus on optimizing product data—both in physical and digital environments. Our platform helps retailers standardize and enrich product information, connecting internal and external operations efficiently. That way, the end consumer finds exactly what they need, with no information barriers.”

Data Enrichment as the Solution

Data enrichment is the most effective response to these challenges. It involves adding new information and improving the quality of existing data, creating a solid foundation for product management. This process may include more comprehensive descriptions, high-quality images, and detailed attribute information.

Additionally, data enrichment ensures that product records remain up-to-date, improving usability across internal systems and e-commerce platforms. Artificial intelligence and machine learning allow for continuous and scalable enrichment, reducing the need for manual intervention.

André from Koya AI adds:
“The report 'The State of Product Content 2024' reveals that 35% of consumers returned items in 2024 due to discrepancies between the product description and reality—an increase of 3% from the previous year. This shows that consumers are more discerning, and the shopping experience is becoming a major competitive differentiator. Structuring and enriching product data through AI has a direct impact on key e-commerce metrics, such as conversion rates and customer satisfaction. It also creates a strong foundation for improving recommendations, search results, and analytics—delivering a more personalized and accurate experience for shoppers.”

Practical Benefits of Data Enrichment

Companies that invest in data enrichment enjoy numerous advantages, including:

• Improved customer experience: Detailed information helps consumers choose the right product, boosting conversion rates.

• Error reduction: Continuous standardization minimizes the risk of inconsistencies and duplicates.

• Greater operational efficiency: Automating the enrichment process reduces time spent on data maintenance.

• SEO improvements: Optimized descriptions and detailed attributes make products easier to find online.

In short, data enrichment is the key to overcoming the challenges of centralized product records and ensuring a smooth and efficient digital retail operation.

Originally posted at: https://sejaumami.com.br/cadastro-de-produtos/enriquecimento-de-dados-e-centralizacao-no-varejo-digital/