Client Overview
Our client is an established consumer electronics retailer with over six years of eCommerce experience, operating business across both a physical showroom and a large-scale online store. The business offers a wide range of product categories—including televisions, smart kitchen appliances, headphones, home surveillance systems, telephones, and power accessories.
With a catalog exceeding 1 million product listings and a customer base that continues to grow, the retailer has built significant market presence.
Project Overview
The retailer's catalog had grown faster than their ability to manage it efficiently. Product entries were incomplete, inconsistent, and often mislabeled—creating problems in site merchandising, pricing accuracy, and executing promotions effectively.
The retailer engaged us to systematically address these issues and establish a clean, scalable product data foundation. The scope of work included:
Project Challenges
Managing a catalog of 1.2 million products brought several challenges. Existing gaps and inconsistencies in the catalog data created issues across the website, limited marketing effectiveness, and slowed time-to-market. The key project challenges included:
A significant number of products had been assigned to a generic default product type rather than mapped to the appropriate category. Many of these entries also had attribute fields that were entirely disabled, preventing any meaningful product information from being displayed to shoppers.
Correcting this required manual review at scale—cross-referencing each entry against the correct product type and enabling the appropriate attribute structure for each category.
Faceted navigation and guided search—core tools for helping shoppers filter products by price range, color, brand, and specification—were effectively nonfunctional across large portions of the catalog.
Incorrect taxonomy labels, missing color values, and inconsistent textual data meant that many products were invisible to shoppers who were using filter-based browsing. It was directly reducing browse-to-purchase conversion.
Consumer electronics includes a wide range of product types, each with unique attribute structures and industry-standard terminology.
Accurately restructuring the product taxonomy and validating attribute assignments required team members with familiarity with the product categories—not just data entry proficiency. The team needed to identify data gaps that weren't immediately obvious without product-specific expertise.
Our Approach
To address the project challenges, Data4eCom assigned a dedicated team of 10 eCommerce data specialists. The engagement began with client-provided training on industry terminology, their data management system, and the guidelines for entering data within the client's portal.
This helped the team align with the client’s requirements and provide the following services:
The team conducted a comprehensive cleansing process on the dataset before implementing any structural changes. Various product data matching methods were applied to detect and flag duplicate records. All remaining entries were reviewed for accuracy—identifying and correcting incorrect values, inconsistent spellings, and variation mistakes that, if left unaddressed, would have negatively impacted the standardization work that followed.
Our team consolidated all product listing data within the client’s system and aligned key components—including titles, descriptions, measurement units, and abbreviations— to a unified format. Spelling, terminology, and numerical data were also standardized across the catalog. For example, the word “color” appeared in inconsistent forms such as “color,” “colour,” and “clr” across product pages. A single standard was applied across all listings to remove the discrepancy at the source.
Many product records lacked complete specifications or accurate descriptions. The team sourced missing information directly from manufacturer catalogs and brand websites. Further, it used that data to add information in the incomplete fields and correct inaccurate entries. This step improved listing completeness and enabled accurate, faceted searches across product types that were previously not visible.
A structured product taxonomy was designed with clearly defined parent, child, and sub-category levels. All products were reclassified against this framework, with the correct attribute set assigned to each entry. Universal Product Codes (UPCs) were standardized to support clean data exchange between the retailer, their suppliers, and manufacturers. Attribute-level sorting improved product discoverability across the entire store.
38%
Higher site search conversions resulted from implementing an accurate taxonomy and categorization framework. Product discoverability and user experience also saw improvement.
40%
Lift in campaign performance observed due to complete, consistent, and accurate product data across the website.
99%
Data accuracy achieved through cleansing, matching, and standardizing the 120,000-item product catalog.
Our team delivers product data management services that improve catalog consistency, increase product discoverability, and support more efficient day-to-day eCommerce operations. Write to us at info@data4ecom.com to request a service demo.
Request a Free Consultation