In this video I'll explain how a PIM solution supports the overall product data journey, and how they're the glue that connects data sources to channels, turning chaos into organization. Whether it's dealing with pain points at the data source or the challenges of enrichment and syndication, PIM is the tool that adds order to the complexity.


So how do Product Information Management (PIM) solutions support the product data journey?

Well, let's start off with, what is the product data journey? And the way I like to describe the product data journey is a lot like the movement of goods. If we think about anything that you buy off the shelf, it starts out as coming from a source. It starts out as raw materials that are ripped out of the ground, something is done with them. They're then packaged and shipped to some location, either directly to your doorstep or to a store, in which you can go pick them up and then consume them, and that can be anything. That could be anything from clothing to food to furniture, it doesn't really matter. 

But if we were to draw that same parallel in product data, data goes through its own supply chain process. So it starts out at its source as raw data, and sometimes not so raw data. But if we think of it as just sticking to the source, data comes from various sources. 

So a PIM, in this instance, is coming in and allowing me to collect my product information from various sources. What are those sources? Well, those sources can be my ERP, as an example, that's like the most obvious, right, 'cause it has basic product information management in order to facilitate the purchase and sale of a product. It could be data that I receive from a supplier, it could be data that I receive through a portal that my suppliers log into and upload data from or upload data to and I download it from, it could be a data catalog, it could be a data pool, things like the GDSN or Global Data Synchronization Network, could be spreadsheets that are being passed around. This is very common. Even Fortune 100 organizations are still sharing spreadsheets of product information management. But it's just a ton of various sources that have information that is gonna be pertinent to packaging up and shipping that data to various channels or downstream consumers so that that data can then be used for either facilitating the sale of a product or finding information about a product, right? Both of these things are very important. 

But ultimately, a PIM is supporting the aggregation of data from data sources and the syndication or export of information to data channels. 

Now, what are channels? 

Well, channels are going to be sometimes the original source because of the activities that go on within a PIM. So it could be taking data from a source, doing something with it, and then sending it right back to that source in a nice, new version or fashion, sometimes called the golden record. 

Those channels could also be antiquated print catalogs that are still lurking around.  I think of the furniture catalogs, or in the B2B world, the big books, right? So print automation comes into play. They're consumers of that product information management. Sometimes it could be as simple as just simply my eCommerce store. Or better yet, it could be my retailers or dealers, right? So it could be their eCommerce store that they're putting this information in various marketplaces, Amazon as an example. It's kind of a Captain Obvious one. For some, it could be social channels, right? They're pushing information out through Instagram or TikTok or  any of these social sites that do any type of sale of a product or support the sale of a product, could even be branded portals, like especially for companies that have multiple brands. It could be microsites, it could be branded sites, it could be dealer portals, it could be even information that goes to call centers or customer service centers where they utilize that information to support and answer questions as they receive calls, or even just help facilitate the sale of a product if somebody has questions about a product. 

So ultimately, my data's coming from the raw material, the raw sources, something is happening to it, and then it's going to various channels. It seems simple enough, right? But that journey is actually very complicated. Because if we think about it, there are pain points at both the data source and the data channels. 

And PIMs are kind of the glue in between those two to make the chaos somewhat organized. Because if we look at just data sources as an example, what chaos could exist there? What pain points exist at my data source? It could be very simple, right? My product information is just not complete. I have information that my channels want that I don't know where it should go in any of the sources. I have channels that are asking me for marketing descriptions. I don't have any places in my ERP to put a marketing description. As a matter of fact, my description is only 50 characters long, and I can't go longer than that. Well, there's a pain point right there. I can't give you more than 150 characters. And you're trying to send that description to Amazon, and Amazon is like, "What is this? This is not a description." Right? It's something basic, something simple. 

But if we take that a step further, I'm getting information from data sources, and I'm getting duplicate information, or I'm getting conflicting information, or I'm not getting all of the information, I'm identifying missing information, right? So the PIMs are helping me collect, organize, analyze, and qualify data from various sources, right? So the PIM is there to support it, create order in the chaos of the collection of that data. Because now let's say some of those red flags go off, right? I'm missing information, or I have duplicates, or the information is conflicting. 

Well, who fixes it?

Well, that's what PIMs help with, right? 

That's what Product Information Management systems are there to help with: Add order to the chaos so that people are alerted about data errors, missing information, conflicting data, and they're making choices and decisions and fixing data, or better yet, they're enriching that data.

They're enriching it with digital assets, or they're enriching it with product specifications, or they're organizing and preparing it for a campaign launch of some sort. And then ultimately, preparing it for channel management or channel syndication. So that's one side of the house. Those are the pain points for the product data journey at the data source, right? 

Conflicting information, organizing it, getting it in order, getting it sanitized, cleaned, validated, approved, all of that. And how do I deal with the outliers? And how do I even report on that, better yet? Now, let's think about the channels. 

So if I do get all my ducks in a row and I get all that information into my PIM and I have a golden record, so I've de-duplicated everything and all of my data's perfect, well, it's only perfect in my organization. 

The moment that I send that data out to downstream systems to my external channels, maybe it's not correct. For instance, if you classified the item in a certain category, let's say you've said, "Okay, this is a laptop that includes mice and a keyboard," right? Or an additional keyboard and a case or something like that, right? And you said, "It's a laptop." Well, if you were to send that to an external marketplace, many of them may not say that that's a laptop, that's actually a bundle, and that that needs to go into laptop bundles. So now we have problems with our classification. So I can't send my various marketplaces my classification. I have to send it with their classification. And each one of the marketplaces that I work with, Walmart, Amazon, doesn't matter, any of them, they all have different classifications. None of them are the same. So now I need to be able to deal with that, right? I need to be able to handle that. And they all have different image requirements and different descriptions. 

As a matter of fact, just plain old putting information out there on the internet, I can't copy and paste the information for SEO purposes. I need to change the information ever so slightly between these sites so that it doesn't just look like the information's being copied over and over and over again from my various channels. Right, or better yet, I need to change it for my different retail partners. Each retail partner wants a different tailored experience. So I can't just sit there and say, "Here you go. You get the cookie-cutter information that I've got for everybody else." Right, because that is now a problem with the enrichment of the information. So not only did we have problems on getting it, but now we have problems on the enrichment and syndication of it. 

So a PIM supports the product data journey by allowing me to have variations of that information and identifying when are certain variations of that information needed, and then for which products, because I may not send all of my products to all of these channels. Especially if I have branded portals, they may not need to go to all of those, they only need to go to a subset of those. 

So ultimately, a PIM or Product Information Management System is going to support the aggregation of information and all of the pain points that come with trying to get that information together from various people and various systems, allow you to package it up, and then ship it out to all of the consumers of that information in the various ways that they want it, and it is there to provide a backbone. And different PIMs offer different features, but ultimately, all of them are there to provide that backbone to be able to connect the data source to the channel by allowing you to aggregate it, validate it, enrich it, organize and approve it, and ultimately send it out meeting those channel needs.

About the Author

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Adam Arbour

Principal Consultant, Data Practice

Adam brings over 12 years of experience in helping organizations solve their data challenges. Working with manufacturers, distributors, and CPG, has is a key consultant to the C-suite to drive digital transformation roadmaps. He's designed and implemented multiple software platforms supporting Master Data, Governance, Data Quality, and BI/Analytics engagements. He brings a depth of expertise and experience at driving business outcomes and simplifying complex technical engagements.

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