Who should have the burden of lifting product information as your suppliers have it to the way it is presented at the digital point-of-sales provided by you? Often this seems to be stalled in a standoff as described in the post Passive vs Active Product Information Exchange.
At Product Data Lake we offer merchants and suppliers an honorable way out of this standoff.
Interested in learning more? Get in contact:
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 will have the most complete, accurate and timely product information in front of your customers.
You will reduce costs if you can pull product information in one uniform way and let your suppliers push it in their many ways.
Our Product Data Pull solution using emerging technologies within Product Data Lake will make you “easy to do business with” in the eyes of your suppliers and make your product information a powerful weapon.
The people who will use 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.
Learn more about Product Data Pull here.
Get in contact and learn how to take product information to the next level:
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.
What 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.
The term End-to-End is used a lot in marketing jargon. Now, I will jump on that wagon too.
In reality, no solution will be an End-to-End solution for all your business needs. Therefore, my take will merely be to cast some light on an End-to-End need for which there are only very scattered solutions today.
If we look at Product Information Management (PIM) there are many good solutions for taking care of the End-to-End needs within your organisation. The aim is to gather the product information that exist within your organisation in various silos, have one trusted place for all this information and being able to publish this information in a consistent way across all channels – the omnichannel theme.
However, product information does in many cases not live just within your organization. In most cases, it lives in a business ecosystem of manufacturers, distributors, retailers and large end users.
Therefore we need an End-to-End solution for product information that encompasses the path from manufacturers over distributors to retailers and large end users and in some cases the way back.
If you are a distributor or retailer, you can use the Product Data Pull service to achieve tangible business outcomes through:
- Having complete, accurate and timely product information in front of your customers. You will sell more.
- Having a fast and seamless flow of product information from your upstream trading partners. You will reduce costs.
Black Friday 2017 is closing in.
One way to compete as a merchant is to have the most complete and accurate product information in front of your customers.
Using Product Data Pull from Product Data Lake is the way to get that done as fast and effortless as possible.
In the Black Friday spirit, we offer a free onboarding of your product portfolio if started before 24. November 2017.
All you have to do to get started is pushing your product portfolio with the required product information you need from your suppliers to us. And perhaps answer a few questions.
Then we will:
- Create a Product Data Lake testing account for you free of charge for 6 months *)
- Put your product portfolio into Product Data Lake
- Put your product attributes into there as well
- Put your digital asset types up there too
- Even put any related products requirements in play also
After that, you are ready to ask your suppliers to join, giving them a way to provide product information in the format, structure and taxonomy they have.
You will then be able to pull your product information in one uniform way and let your suppliers push it in their many ways.
Read more about Product Data Pull here.
The importance of having a viable Product Information Management (PIM) solution has become well understood for companies who participates in supply chains.
The next step towards excellence in PIM is to handle product information in close collaboration with your trading partners. Product Data Lake is the solution for that. Here upstream providers of product information (manufacturers and upstream distributors) and downstream receivers of product information (downstream distributors and retailers) connect their choice of in-house PIM solution or other product master data solution as PLM (Product Lifecycle Management) or ERP.
The PIM-2-PIM solution resembles a social network where you request and accept partnerships with your trading partners from the real world.
After connecting the next to set up is how your product attributes and digital asset types links with the one used by your trading partner. In Product Data Lake we encompass the use of these different scenarios (in prioritized order):
- You and your trading partner uses the same standard in the same version
- You and your trading partners uses the same standard in different versions
- You and your trading partner uses different standards
- You and/or your trading partners don’t use a public standard
Read more about that and the needed data governance in the post Approaches to Sharing Product Information in Business Ecosystems.
Then it is time to link your common products. This can be done automatically if you both use a GTIN (or the older implementations as EAN number or UPC) as explained in the post Connecting Product Information. Alternatively, model numbers can be used for matching or, as a last option, the linking can be done in the interactive user interface.
Now you and your trading partner are set to start automating the process of sharing product information. In Product Data Lake upstream providers of product information can push new products, attribute values and digital assets from the in-house PIM solution to a hot folder, where from the information is uploaded by Product Data Lake. Downstream receivers can set up pull requests, where the linked product information is downloaded, so it is ready to be consumed by the in-house PIM solution.
This process can now be repeated with all your other trading partners, where you reuse the elements that are common between trading partners and build new linking where required.
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:
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.
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.
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.