If your company sells online, you know keeping product data accurate, complete, consistent, and up to date is critical. This is even more challenging when using a 3rd party data source like AD, Sydigo, 1WorldSync or DDS. (See our Product Data Quality Article for additional tips and strategies.) But what does that process look like for your organization? Are there opportunities for cost reduction and accuracy improvement?
If you are manually importing data today, have you thought about how to auto-import data into PIM?
FACTORS FOR PIM DATA SYNC
- Do you have a lengthy manual process to obtain, format, and standardize the data before uploading it into your PIM?
- Do the products you sell have complicated data attributes?
- Are you currently displaying all the data you would like to from your 3rd party data feed on your eCommerce site?
- Are the data formats and ranges provided by the 3rd party data feed easily ingested into your PIM data model? (The feed includes the data "32 degrees", and you need it to be "32°")
- When a product displays out of stock will it be available to purchase soon? Are you showing a temporary substitute or the replacement part/brand?
Each of these factors poses significant technical challenges to overcome prior to implementation of an auto-import mechanism. With our deep understanding of product data and software architectures, Layer One has repeatedly solved these problems. In one example, we had a client in the wire and cable space who was struggling to import data, from a DDS feed into their PIM Inriver. At the time of import, five different channel managers had to manually map multiple fields for every SKU. Their previous solutions partner had told them that this was the best and only process.
AUTO DATA SYNC SOLUTIONS
Layer One stepped in and tackled two key issues.
- How to map feed fields to an Inriver Specification data “template.”
- How to convert the data in the feed fields to the desired format.
More specifically, they used a data model with their PIM that had independent fields for minimum and maximum temperatures, but their data source provided ranges or temperatures on different scales depending on the manufacturer. Our tool could identify, transform, and properly place these into the correct data fields. We identified data fields provided in the 3rd party data feed the client wanted that they were not capturing and mapped them. Finally, we connected their ERP to their PIM and were able to identify out-of-stock reorders, phaseouts, and discontinues to provide substitutable products when appropriate. All of this was now an automated process, saving dozens of hours per data import and increasing accuracy.
TECHNICAL EXAMPLE
From a technical standpoint, products within the incoming feed were “looked up” in the PIM, and its specification data template was inferred. This then allowed a configuration file to be used to “connect” the feed fields to the specification fields. An example snippet of this configuration file is as follows:
In the above, the Inriver Specification “Heat Shrink Tubing” is configured to map the feed field “S Ratio” to the Inriver Specification field “Shrink Ratio.”
Finally, the data within a given field sometimes needed to be converted to a different format. This was accomplished using transformation rules baked into the Layer One tool. Each piece of field data could be manipulated using configuration entries like the following snippet:
In the above transformation, temperature field data containing the word degrees is converted to the degree symbol.
Layer One tackles business issues like this every day for our clients. If you would like to know more about automating data feeds into your PIM or other product and eCommerce hurdles, reach out to us now!
Product Data Quality is the third of Layer One's 
See the other 13 Focus Points for Manufacturers and Distributors here!