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Classify Product Data: Classification Standards and How to Implement them Painlessly

Accurate product data forms an integral part of a consumer’s purchase decision. From search results to conversions, from brand recognition to comparative product evaluations to final purchase – the availability, clarity, and accessibility of clear product data enables the buyer to make a purchase decision.

And that’s why organizing their product information and classifying it is critical for customer experience. The process of classifying data into groups or taxonomies requires the use of classification standards – which can be thought of as a product data organizing system that lets retailers easily classify all kinds of products and services into characteristics or attributes that forms a hierarchy.

Here’s an example of a product hierarchy:

This hierarchy is made possible following a product data classification standard designed to enable efficient management of product data.

Here’s everything you need to know about product data classification standards including how Product Match Enterprise can help you incorporate these standards in your business.

What is Product Data Classification?

Product data classification refers to the process of grouping or categorizing product information based on a hierarchical structure. Products that have the same criteria, can be categorized in different groups and classified according to the multiple types of classification standards set by global trade bodies. The end purpose of data classification is – efficiency and effectiveness in use.

In its raw form, product data is unstructured. Each supplier uses different structures and vocabularies to describe its products. For instance, Vendor A may describe a phone as:

Samsung Note 20 Ultra Black, 256GB indicating brand, model, color and a storage attribute.

Vendor B may describe it as:

Samsung Electronics Galaxy Note 20 Ultra 5G Factory Unlocked indicating brand, model and capabilities.

This may not cause a problem for a 1-1 relationship where the buyer may get used to the private terminology of his supplier. In an ecommerce market place though, retailers cannot rely on assumptive structures. They must classify all products according to a standard classification schema that help buyers and suppliers in communicating their product information. Whether B2B or B2C category, product data classification can greatly affect a buyer’s purchase decision.

In order to make sense of these two varying descriptions, the retailer will need a classification system where they can parse these descriptions into attributes and then categorize it under the respective category (such as Phone -> Brand -> Model) to ensure a logical order.

This classification process enables the retailer to do multiple things:

      • Perform product data matching when needed (such as matching multiple vendor lists to make a business decision)
      • Easily review product inventory and catalog
      • Enable easy web navigation
      • Enhance user experience
      • Manage product data efficiently

In the e-selling experience, product classification can help retail businesses manage the proliferation of data standards and enable the consumer to make informed purchase decisions in the face of multiple options.

What are Classification Standards?

Product classification standards like UNPSC, GPC, eClass, and more developed by organizations, government bodies, and global trade communities to help eCommerce businesses trade and move products globally. Standards play a critical role in custom procedures where they are used as trade statistics for exports and imports; allowing for comparisons between countries.

Here’s an example.

Consider product number 00121. This number follows the Standard International Trade Classification (SITC) product categorization system maintained by the UN. This standard uses a hierarchy that follows: division group – subgroup – heading.

In this case, 00 indicates the primary category of live animals.

The following 1 indicates a group that could be a kind or a size.

The 2 is the category of sheep and goats.

The 1 specifies it is a sheep.

With this information, live sheep trading can easily be compared between different locations and periods.

There are several types of classification standards each catering to the specific rules and regulations of local and international trading. Three of the most common global standards used by retailers, suppliers, and manufacturers are:

UNSPSC: The United Nations Standard Products and Services Code (UNSPSC) managed by GS1 US for the UN Development Programme is a global, multi-sector standard for the classification of products and services. According to the UNSPSC, the classification system can be used for:

  • Company-wide visibility of spend analysis  
  • Cost-effective procurement optimization  
  • Full exploitation of electronic commerce capabilities


Global Product Classification (GPC) Code: 
The GPC classifies products by grouping them into categories based on their essential properties as well as their relationships to other products. GPC offers a universal set of standards for everything resulting in a common business language that is clear and instantly understandable. You can read more about how GPC works here. 

eClass: ISO/IEC compliant companies often use the eClass standard to standardize procurement, storage, production and sales within and between companies, industries, and countries. The standard is also frequently used between customers and suppliers, ensuring the sustainability of all parties involved. You can read about how eClass works here 

Of the three standards, Data Ladder uses the UNSPSC to create product taxonomies and classification modules. An open standard, available at no extra cost, the UNSPSC is one of the most widely used standards in the world of eCommerce trading. If you’re looking for a standard to sort, classify and maintain the accuracy of your data, you can start by following the UNSPSC codes.  

How Product Classification Standards Impacts Businesses  

Standards matter because it helps you save up on the business cost of poor, mismanaged product data. But cost-saving is just one aspect of it. Some key benefits include:   

      • Buyers and sellers share a common language within and across regions or countries
      • It’s easier to manage product data, ensuring data accuracy and integrity is maintained
      • Helps businesses simplify reporting across product categories
      • Helps retailers optimize their product information to enable consumers to make the right purchase
      • Acts as a guide for businesses to implement standards if they don’t already have an internal classification system


A successful information or product grouping process is critical in helping organizations set appropriate levels of control to keep up the integrity and consistency of their information. Moreover, it’s highly beneficial to the consumer who would expect to find the right information with the right search. 
 

Product classification plays a crucial role in website conversion rates, directly impacting the purchase decision of the buyer. Standards applied in the data source can be replicated on the web front enabling the easy arrangement and depiction of product information into various categories and modules. Proper categorization also improves compliance and helps organizations adhere to GDPR, HIPAA, FERPA, and other data protection regulations.  

In simpler words, product classification standards help businesses to organize their product data – on the front end and the back end. Multiple parties benefit from product grouping done right.  

What are the Key Challenges to Implementing these Standards?

Bottlenecks in exchanging information have led to a plethora of different standards that should improve the situation. However, usually, there are either too many standards for multiple industries that are often unable to cover all the necessary detail of a certain product or industry. For instance, the UNSPSC covers all product domains, but it does not cover all the necessary details for some products such as the hardware and software industry that uses the Rosetta Net as a classification standard.  

To make it worse, existing problems with product data make the process of mapping classification standards excruciatingly difficultThese are:  

          1. Product data quality  the most critical challenge to the grouping and classification of products.  Your product data needs to be accurate, complete and standardized before it can be categorized and classified. This is why ProductMatch comes equipped with a data cleansing and standardization that helps retailers and manufacturers clean their product data of inconsistencies and duplicates before grouping it into taxonomies.You can read our comprehensive guide on Product Data Quality here.

            Product Data Quality Guide

            MANAGE YOUR RETAIL BUSINESS WITH A ROBUST PRODUCT DATA QUALITY SOLUTION

        1. Relying on Manual Methods – Most retail companies still have teams manually sorting product data via spreadsheets. Not only is this counter-productive but also detrimental to the case of product data quality. You could miss duplicates, have typo errors and standardization problems that will become a problem for downstream applications and processes. What businesses need is an automated solution to product data sorting and classification. You really cannot afford to manually type in codes to every product or spend days in charting out taxonomies.
        2. Limited in Time and Resources – Businesses are usually overwhelmed with the amount of data streaming in on a daily basis. They don’t have the time to really sit through each product and determine the right category or hierarchy. Most of the categorization is done based on gut instincts or on an already pre-defined system that has probably not been updated for years. Limitations in time and manpower prevent businesses from investing in the accuracy of their product data, resulting in poor analytics, costly mistakes, and low conversion rates.  

With limited resources, manpower, and outdated systems, businesses are having a hard time maintaining data accuracy in a time where consumers want better experiences, and competitors are just a click away.

Mapping the Standards on to Product Data  

Transforming a semi-structured or unstructured product description into a standard classification system as the UNSPSC is not a trivial task. Finding the right place for a product description in a standard classification system such as UNSPSC is not at all a trivial task.  

Each product must be mapped to the corresponding product category in UNSPSC to create the product catalogThe UNSPSC is a hierarchical classification, having four levels. Each level contains a two-character numerical value and a textual description. The order of the words in a title does not imply hierarchy or importance. There is an additional, optional suffix, which is currently defined with 2 digits; it is called the Business Function Identifier. A diagram of the five two-digit pairs is as follows: 

Classifying millions of product descriptions into a systematic standard as this requires intensive labor taking up nearly 30% of the time in data management alone. Not to mention, manual labor as this is error-prone and makes an even more frustrating experience for data managers. Traditional methods can no longer support the volume, speed and complexity of modern product data. We need solutions that can leverage on the power of machine learning to take on complex data challenges.  

For instance, teams can no longer sort millions of rows of data via spreadsheets or ETL formulas. They need a solution where tasks like cleaning errors, normalizing formats, and duplicates can be removed with just a few clicks.  

Businesses direly need for automation of the product classification process and automatic creation of product classification rules. 

How Product Match Enterprise Automates Product Classification Standards  

ProductMatch Enterprise is one such automated, ML-based solution targeted at supporting product classification according to various classification standards. It is designed to automatically classify products and create taxonomies based on their original descriptions. It uses machine learning and natural language processing techniques to process data and index UNSPSC 

Additionally, it allows retailers and manufacturers to:  

      • Clean, prepare, deduplicate and match product lists via an easy point-to-click interface  
      • Get automated product classification based on UNSPSC standards  
      • Create customized classification standards  
      • Manage product data diligently and efficiently  
      • Save up on time, resources and costs  
      • Make sense of millions of rows of semi or unstructured product data
         

What truly makes ProductMatch powerful is its integrated software environment. Users can perform a range of critical data quality tasks such as data profiling, data cleansing, data preparation, data matching to ensure their data is of the desired quality to be fit for classification. Once the data is prepared, our teams will assist you in the creation of product taxonomies and implement standard codes for each product.  

Electronic marketplaces have huge potential; however, product data needs to be modeled and mapped effectively to help businesses manage the growing influx of information. Product or content managers shouldn’t have to spend over 30% of their time in manually structuring, classifying, re-classifying, and optimizing large volumes of data to make product descriptions. In an age of automation, these mind-numbing, repetitive tasks must be automated to help team members focus on what truly matters – the user experience, business potential, and futuristic growth.  

Ready to classify your product data? Contact our team for a quick walk-through of Product Match Enterprise!   

Farah Kim is an ambitious content specialist, known for her human-centric content approach that bridges the gap between businesses and their audience. At Data Ladder, she works as our Product Marketing Specialist, creating high-quality, high-impact content for our niche target audience of technical experts and business executives.

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