The client runs a multi-brand online beauty store offering a diverse collection of over 30,000 health, beauty, and personal care products across 50+ categories. Based in Canada, the client deals in domestic as well as imported products and ships them across the world.
Our client was looking for an outsourcing partner to proficiently manage the product data and store it in a single, centralized location for easy access. The client wanted us to recognize all the existing sources of product information, identify missing, incomplete, inaccurate and irrelevant entries and clean the database to finally consolidate all the product data into a single location. This information includes SKUs, product titles, descriptions, attributes, images, prices, reviews, etc.
With a catalog spanning over 30,000 SKUs across 50+ categories, the client was dealing with product data scattered across multiple sources. Before any data consolidation could begin, several critical issues had to be resolved, such as:
The product information was sourced from multiple suppliers, each using different naming conventions, units of measure, and attribute formats. This was making it impossible to match and merge records without first establishing a common data standard. Standardizing these inconsistencies at scale required a structured, rule-based approach and careful manual review.
A significant portion of the product records had incomplete or inaccurate data, including incomplete descriptions, missing product images, unformatted attributes, and incorrect pricing. Some records also contained factual inaccuracies that, if left uncorrected, could mislead customers or cause fulfillment errors. Our team had to identify and fill these gaps across all active listings within the strict timeframe to avoid negative impact on discoverability and rankings.
The same product appeared under multiple entries across different sources, sometimes with slight variations in title or attribute data. Identifying true duplicates versus valid product variants (e.g., different sizes or formulations of the same product) required careful cross-referencing and domain judgment — not just automated matching.
The client required the entire dataset to be cleaned, standardized, and consolidated within a defined timeframe, without interrupting their day-to-day store operations. Processing 30,000+ SKUs accurately and on schedule — while maintaining quality at every step — demanded a well-structured workflow and sufficiently trained resources.
We assigned a dedicated team to audit, clean, enrich, and consolidate the client's product data into a single, well-structured repository. We leveraged human-in-the-loop methodology (combining advanced automation with manual QC) to ensure 100% data integrity. Our product data management services covered:
Our team began by mapping all available data sources — including printed catalogs, supplier websites, manufacturer portals, and existing internal files. We extracted and compiled product information from each source into a working dataset, covering SKUs, titles, product descriptions, attributes, pricing, images, and customer reviews.
Each record was reviewed for errors, inconsistencies, and missing values. Our product data cleansing experts corrected inaccurate entries, filled in missing attributes using verified sources, removed outdated or irrelevant data, and flagged records that required client review. This step ensured only accurate, usable data moved forward in the pipeline.
To resolve inconsistencies arising from sourcing product information across multiple systems, our team developed a unified data standardization framework. This included defining uniform naming conventions, category taxonomy, attribute structures, units of measure, size formats, finish descriptors, and image guidelines for all product records. This framework helped us improve data accuracy, reduce duplication, strengthen catalog usability, and create a scalable structure for ongoing product data management.
Through a structured product data matching, we identified duplicate and near-duplicate records across multiple source files. Instead of relying only on automated SKU or title matching, we cross-referenced product identifiers, titles, descriptions, attribute values, pack sizes, formulations, units of measure, and category placement to determine whether records represented the same product or a valid product variant.
Where duplicate listings were found, we merged them into a single, authoritative product record, retaining the most complete and accurate data from each source. For genuine variants, such as different sizes, quantities, formulations, or finishes, we preserved them as separate records and mapped them under a consistent variant structure.
All cleaned and standardized product records were consolidated into a single central repository. The repository was structured to support easy updates, filtered searches, and seamless data distribution to the client's website and connected marketplaces — eliminating the need to manage product data across multiple disconnected systems.
To prevent future data integrity issues, we configured role-based access controls within the product database. Team members were assigned permissions based on their responsibilities — limiting who could edit, approve, or publish product records. This gave the client a structured data governance framework to maintain quality going forward.
Leveraging our scalable workflows, multi-level QC, and subject matter expertise, we provided the client with a fully consolidated, accurate, and ready-to-publish product database — built to support both their own storefront and third-party marketplace listings. We not only adhered to the strict timelines and required quality standards, but also helped the client achieve:
78% fewer data errors and inconsistencies
98%+ data accuracy across the catalog
65% faster time-to-market
Our eCommerce data management team has helped retailers across health, beauty, and multiple product categories to manage large-scale catalog data with accuracy and speed. Write to us at info@suntecindia.com to discuss your requirements.