5 Product Data Levels to Consider

As a merchant (dealer or retailer) you are probably evaluating how you can implement or improve your Product Master Data Management (Product MDM) and/or Product Information Management (PIM). When doing that, you can divide the different kinds of product data into the schema below:

Five levels

Level 1, Basic Data

At the first level, we find the basic product data that typically is the minimum required for creating a product in any system of record.

Here we find the primary product identification number or code that is the internal key to all other product data structures and transactions related to the product within an organization.

Then there usually is a short product description (if you use SAP, it is an only 40 character long field). This description helps internal employees identifying a product and distinguishing that product from other products. Most often the product is named in the official language of the company.

Here we also find the identification of the supplier and his product identifier.

Level 2, Trading Data

The second level has product data related to trading the product. We may have a unique Global Trade Item Number (GTIN) that may be in the form of an International – former European – Article Number (EAN) or a Universal Product Code (UPC). Here we have commodity codes and a lot of other product data that supports buying, receiving, selling and delivering the product.

Level 3, Recognition Data

On the third level, we find the two basic pieces of product information that came to existence when we started producing product catalogues and had the first ecommerce solutions online.

The extended product description is needed because the usual short product description used internally have no meaning to an outsider as told in the post Customer Friendly Product Master Data. Some good best practices for governing the extended product description is to have a common structure of how the description is written, not to use abbreviations and to have a strict vocabulary as reported in the post Toilet Seats and Data Quality.

We often see that the extended product descriptions need to be present in the range of languages covering the locations where business is done either if the business is international or done in a country with multiple countries. The trend of increased user customization (or should I say customization) drives this point further.

Having a product image is pivotal if you want to sell something without showing the real product face-to-face with the customer or other end user. A missing product image is a sign of a broken business process for collecting product data as pondered in the post Image Coming Soon.

Level 4, Self-service Data

At the fourth level, we have three main sorts of product information: Product attributes, basic product relations and standard digital assets. These data supports when customers makes buying decisions within eCommerce and other self-service scenarios.

Product attributes are also sometimes called product properties or product features. These are up to thousands of different data elements that describes a product. Some are very common for most products like height, length, weight and colour. Some are very specific to the product category. This challenge is the reason of being for dedicated Product Information Management (PIM) solutions as told in the post MDM Tools Revealed.

Basic product relations are the links between a product and other products like a product that have several different accessories that goes with the product or a product being a successor of another now decommissioned product. Product relations is described further in the post Related Products: The Often Overlooked Facet of PIM.

Standard digital assets are documents like installation guides, line drawings and data sheets as examined in the post Digital Assets and Product MDM.

Level 5, Competitive Data

As the fifth level we find elements like on the fourth level, but usually these are elements that you won’t necessarily apply to all products but only to your top products where you want to stand out from the crowd and distance yourself from your competitors. If you are a reseller, you typically make these data yourself, where level 4 hard facts are delivered from the manufacturer, as examined in the post Using Internal and External Product Information to Win.

Special content are descriptions of and stories about the product above the hard features. Here you tell about why the product is better than other products and in which circumstances the product can to be used. A common aim with these descriptions is also Search Engine Optimization.

X-sell (cross-sell) and up-sell product relations applies to your particular mix of products and may be made subjective as for example to look at up-sell from a profit margin point of view. X-sell and up-sell relations may be defined from upstream by you or your upstream trading partners but also dripping down on the roof from the behaviour of your downstream trading partners / customers as manifested in the classic webshop message: “Those who bought product A also bought / looked at product B”.

Advanced digital assets are broader and more lively material than the hard fact line drawings and other documents. Increasingly newer digital media types as video are used for this purpose.

Product Classification, Product Pricing and Product Lifecycle Status

All of the above-mentioned levels of product information is supported by product classification. Usually we see product classification handled as a reference data type across Product Information Management (PIM) and ERP solutions.

Product pricing is usually also a subject mainly belonging to the ERP side of things.

Master Data Management (MDM) is the discipline that connects the dots between these topics.

Take the processes to the next level:

Learn how our Product Data Pull concept drastically can improve your business processes in getting not at least the higher levels of product information in the right shape here.

How Merchants Can Sell More and Reduce Costs

In a data driven world being the best at receiving product information from your suppliers is a winning formula.

You will sell more if you have the most complete, accurate and timely product information in front of your online customers when they make self-service buying decisions.

You will reduce costs if  you can pull product information in one uniform way and let your suppliers push it in their many ways. Hereby you can automate the processes,  avoid errors and reduce product returns.

You will also be able to manage a broader product range by turning ad hoc products into a regular product in your assortment with minimal extra costs.

Our solution using emerging technologies within Product Data Lake will make you be easy to do business with in the eyes of your suppliers and make your product information transform into a powerful weapon in the quest for winning more online market share.

The people who may buy your product range deserves to know all about it and wants to get that information when making the buying decision. Remember: 81 % of visitors will leave a web-shop with incomplete product information.

Downstream sell more reduce costs

 

How to Combine eClass and ETIM

eClass and ETIM are two different standards for product information.

eCl@ss is a cross-industry product data standard for classification and description of products and services emphasizing on being a ISO/IEC compliant industry standard nationally and internationally. The classification guides the eCl@ss standard for product attributes (in eClass called properties) that are needed for a product with a given classification.

ETIM develops and manages a worldwide uniform classification for technical products. This classification guides the ETIM standard for product attributes (in ETIM called features) that are needed for a product with a given classification.

It is worth noticing, that these two standards are much more elaborate than for example the well-known classification system called UNSPSC, as UNSPSC only classifies products, but does not tell which attributes (and with what standards) you need to specify a product in detail.

There is a cooperation between eClass and ETIM which means, that you can map between the two standards. However, it will not usually make sense for one organization to try to use both standards at the same time.

PDL How it worksWhat does make sense is combining the two standards, if you as merchant use one standard and your manufacturer use the other standard. The place to make the combination is within Product Data Lake, the new service for exchanging product information between manufacturers and merchants.

Self-service Ready Product Data

The increased use of self-service based sales approaches as in ecommerce has put a lot of pressure on cross company supply chains. Besides handling the logistics and controlling pricing, you also have to take care of a huge amount of product data and digital assets describing the goods.

You may divide product information into these five levels:

Product Information Levels

Please learn more about the five levels of product information, including how hierarchies, pricing and logistics fits in, by visiting the product information castle.

Level 4 in this model is self-service product data being:

  • Product attributes, also sometimes called product properties or product features. These are up to thousands of different data elements that describes a product. Some are very common for most products like height, length, weight and colour. Some are very specific to the product category. This challenge is actually the reason of being for dedicated Product Information Management (PIM) solutions.
  • Basic product relations are the links between a product and other products like a product that have several different accessories that goes with the product or a product being a successor of another now decommissioned product.
  • Standard digital assets are documents like installation guides, line drawings and data sheets.

These are the product data that helps the end customer comparing products and making an objective choice when buying a product for a specific purpose of use. These data are also helpful in answering the questions a buyer may have when making a purchase.

Every piece of data belonging to any level of product information may be forwarded through the cross company supply chain from the manufacturer to the end seller. Self-service product data are however the data that most obviously will do so.

In order to support end customer self-service when producing, distributing and selling goods you must establish a process driven service that automates the introduction of new products with extensive product data, the inclusion of new kinds of product data and updates to those data. You must be a digitalized member of your business ecosystem. The modern solution for that is the Product Data Lake.

Chinese Whispers and Data Quality

There is a game called Chinese Whispers or Broken Telephone or some other names. In that game, one person whispers a message to another person. The message is passed through a line of people until the last player announces the message to the entire group. At that point the message is often quite different or very shortened. The reasons for that is human unreliability including how we put our own perceptions and filters into a message.

When working with data quality you often see the same phenomenon when data is passed through a chain. One area I have observed in recent years is within Product Information Management (PIM). Here the chain is not just the data chain within a given company but the whole data chain in ecosystems of manufacturers, distributors, retailers and end users.

While Product Information Management (PIM) solutions and Product Master Data Management (Product MDM) solutions – if there is a difference – address the issues within a given company, we haven’t seen adequate solutions for solving the problem in the exchange zones between trading partners.

Broken data supply chain

From what I have seen the solutions that upstream providers of product data work with and the solutions that downstream receivers of product data work with will not go well together.

Consequently, I am right now working with a solution to end Chinese whispers in product data supply chains. Check out the Product Data Lake.