Standardize, cleanse, enrich & translate product data irrespective of format or source
The product data quality challenge seems straightforward — simply ‘cleanse’ product data to make sure it's standardized and correct before use, but the inherent complexity and variability of product data confounds traditional approaches and technology. As a result, most cleansing operations are done by hand — a fundamentally slow, expensive, unreliable and unscalable option that may not even work.
The DataLens System is the first and only solution built from the ground up to manage the unique challenges of product data, including:
- Product Data Cleansing & Standardization
- Problem – The first step when receiving new product data is to make sure it's consistent and error-free. Traditional coding and tool-based approaches choke on the variability of most product data, so the process has largely remained a manual task.
- DataLens Solution – Cleansing and standardization are automated to speed cycle times and improve quality ― forever changing the value and power of product information within the enterprise.
- Product Data Enrichment
- Problem – Sometimes information is simply missing or clearly incorrect and massive effort is required to find or validate it from external sources.
- DataLens Solution – The bulk of the cleansing and standardization effort can be automated and remaining gaps or errors are highlighted for faster, more focused resolution.
- Search Enablement
- Problem – If an item can't be found, it might as well not exist. Item searching has traditionally been a hit-and-miss proposition due to disparate descriptions and a lack of standardized attributes. This results in lost e-commerce sales or time and expense to rebuild the matching item online because an item could not be quickly found.
- DataLens Solution – Product descriptions and attributes can be standardized so that search (text or parametric) and guided navigation are optimized.
- Classification
- Problem – The inability to identify what an item is and how it fits into a classification scheme (or taxonomy) impacts everything from spend classification to loading a PIM/MDM or data warehouse. This ability is essential for systems to know how to group data for business intelligence or to route records for exception management.
- DataLens Solution – Profiling and classification to any taxonomy is automated, allowing a much higher level of business intelligence and process automation.
- Translation
- Problem – The company is global, but the most reliable product information is available in only one language.
- DataLens Solution – Product data can be easily translated on-the-fly, allowing companies to sell efficiently into global markets, search databases worldwide, and consolidate product information from global operations.
- Custom Publication
- Problem – Different internal divisions and different customers require product information in different formats. But because cleansing and standardization has traditionally been a manual effort, it's rarely done properly even once, let alone multiple times and in multiple formats to meet the varying demands.
- DataLens Solution – Once a product domain has been ‘understood’, it's understood forever and can be easily published into any format.
