
Retail
Most retailers are challenged with managing at least two primary hierarchies: a back-end merchandise hierarchy and front-end e-commerce hierarchy. SkuDB excels at designing both hierarchies around a common set of products. One of SkuDB’s key functionalities for retailers is the ability to preview the end customer experience during the design process. "Preview Mode" allows users to simulate the front-end product experience, and test the integration of merchandise and front-end hierarchy designs to see how they will look before they are loaded to target systems.

Key SkuDB functionalities commonly leveraged by Retailers include:
• multi-tier data model (e.g., base-variant): Design and manage content at both the product and variant level for more effective maintenance and user experience.
• product collections: Group and manage ad hoc collections of products to support fast-moving merchandising requirements.
• schema management: Design data models that account for attribute maintenance and usage across more than one system and hierarchy.
• filter optimization: Metrics-driven filter optimization including fill rates, filter completeness rates, sequencing and competitive analysis.
• autoclassification: Practical and intuitive AI-assisted product classification to increase onboarding efficiency.
• data governance: Easy design and maintenance of governance-related content, including: category definitions and help text, attribute definitions & help text, data quality rules, style guidelines, and preferred term dictionary.

Manufacturing
SkuDB is an ideal environment for manufacturers designing back-end master taxonomies, front-end navigation experiences, and syndication rules. Legacy data models, new acquisitions, translation and localization requirements, and inconsistent practices overtime can lead to millions in lost revenue as data has to be reassembled and organized for various projects and business requirements. SkuDB helps design data models that centralize and govern master data, while making channel syndication more efficient and effective.
Key SkuDB functionalities for Manufacturers include:
• multi-tier data model: Maintain a two-tier (i.e., base-variant) or even a three-tier data model to optimize content and data management.
• reporting: Report on data quality metrics in multiple contexts (by product category, business unit, region, etc.).
• preferred term dictionary: Maintain a controlled vocabulary to drive content consistency and search relevancy.
• customizable exports: Flexible and customizable exports enable ad hoc data review files and alignment with syndication requirements.
• data governance: Easy design and maintenance of governance-related content, including: category definitions & help text, attribute definitions & help text, data quality rules, style guidelines, preferred term dictionary, and content localization management.
​Industrial Distribution
Distributors place value on a “collection taxonomy” that allows for content from hundreds of manufacturers to be mapped quickly into a unified hierarchy by leveraging autoclassification and data normalization rules. Accelerating item onboarding, increasing data fill rates and data consistency, and preparing data for “table view” are key focus areas for distributors and key areas of strength for SkuDB. When a day of item onboarding means a day of lost revenue, SkuDB helps design data models that enable the automation and semi-automation of repetitive tasks, shortening time to revenue for products and shortening navigation time and product comparison time for users.

Key SkuDB functionalities for Industrial Distributors include:
• data quality rules: Manage preferred terminology and formatting to enable automated normalization. Syndicate the preferred term dictionary to search technology to improve search relevancy.
• attribute management: Maintain a unique set of product attributes for each category or table, while also designing global attributes that meet the operational the needs of IT, supply chain and marketing stakeholders.
• product relationship management: Identify and maintain relationships between products for cross-sell and up-sell.
• table view design: Design and preview the display of product information in table format.
• autoclassification: Practical and customizable AI-assited autoclassification built specifically for large product catalogs.
• reporting: Dashboards summarizing key data quality metrics including fill rates, filter completeness, and structural analysis.

Grocery & Food Service
SkuDB has been used to design data models for several e-commerce platforms for major US-based grocery chains and food service distributors. Data models in grocery and food service place a high premium on data quality and often include multiple hierarchies, autoclassification requirements, and feeds from multiple data sources. SkuDB excels at designing these surprisingly complex data maintenance architectures and facilitates digital transformations by mastering product information and related governance content before it is loaded to target systems.
Key SkuDB functionalities for Grocery and Food Service users include:
• autoclassification: Practical and customizable autoclassification functionality that integrates AI with mapping rules authored by humans.
• multiple hierarchies: Design multiple hierarchies for different purposes (reporting, e-commerce, print catalogs, etc.) and manage the consistent classification of products across all of them.
• reporting: Dashboards summarizing key data quality metrics including fill rates and rule violations.
• attribute management: Maintain a unique set of product attributes for each type of product, while also designing global attributes that meet the operational the needs of IT, supply chain and marketing stakeholders.
• issue tracking: Customizable tracking of design issues at the category, attribute, or item level.​