Product data and the strategies around it have existed as long as there have been product catalogs (yes, the ones we use to print). Product data strategy, though, has changed. The product data managed today is more complex than it was before. After all, there's no shortage of space on the internet to upload spectacular product photos, valuable product resources, and compelling product details.

A good product data strategy accounts for managing product data for internal processes and for each endpoint that data will be seen on. For most brands, that's a combination of sellers, sales channels, and marketing channels, as well as all collaborating departments.

Product data management subsequently has to work for all inbound and outbound product data, and for all the departments that need it at any point in the product life cycle.

Today’s product data includes:

Essential product data (SKUs, descriptions, etc.)
Enriched product data (images and video, care guides, etc.)
Technical specifications
Design specifications
Attribute categories, relationships, variations (and other taxonomy)
Channel or endpoint-specific variations of product information
Supplier and manufacturer data
Marketing data (SEO elements like keywords, product families, etc.)
Sales information (customer reviews, price history, etc.)

What is PDS (product data strategy)?

Product data strategy (PDS) is the management of product information in tandem with business-relevant strategies. That means your product data management (PDM) is tied to your overall business goals.

The relationship makes sense because the product data on a webpage is all that consumers have in digital commerce to appreciate your products. Product data, thus, is part of business-relevant strategies and needs to be managed strategically.

Strong PDS is needed for internal use and data distribution, too. If product data is managed in a different spreadsheet for the marketing team than for the web development team, there will be errors, discrepancies, and missing data in both databases.

When a brand manufacturer has a quality PDS, products sell and processes run the way they should.

PDS and the PIM (Product Information) Tool

PDS and PDM aren't the only acronyms you'll see when it comes to product data. It’s too bad that acronyms aren't acceptable on the Scrabble board because otherwise, this list would be a goldmine for anyone stuck with “P.”

In working with product data, there are tools designed to manage all that information, like the next-gen PIM (product information management) software. PIM is the most common acronym you'll see in the market, but brand manufacturers uncover a whole new layer of complexity when they see other PIMs listed as:

Product Content Manager (PCM)
Product Resource Manager (PRM)
Product Data Manager (yes, another PDM)

The goal of all these tools is the same, but the functionality of any product data management tool will depend on the quality of the software and the developer's relationship with brands. After all, no PIM can meet brands' needs without a partnership with the brands it serves.

Common faulty logic around PIM and PDS

Because of the alphabet soup of acronyms in product data management (and because most PIM advertisements focus on software features instead of business-relevant strategy), there are many common myths when it comes to product data strategy.

Below is just a handful. See how this faulty logic impacts your brand's PIM strategy—and how much of this faulty logic you've fallen prey to, yourself.

PIM strategy is a fundamental business-relevant strategy because product data is an asset and PIM is the only tool designed to manage all product data over a product life cycle.

That said, not all PIMs or other PDS-related software are created equal.

The faulty statement that “any software can do it” comes from a place of "you don't know what you don't know."

What brands even think to establish business goals related to PDS before starting to shop for a PIM? Typically, brands shop for a PIM before they really understand the opportunities and desired outcomes in the internal and external distribution of product data.

Avoid this faulty logic by establishing your data-related business goals first. Then, narrow the focus of what a PIM needs to do to help you reach specific PDS objectives. Then you're ready to learn more about how to select your PIM software.

FAULTY: "We have an ERP, we don't need a PIM"

Somewhat related to the faulty logic above, there are even those brands who think that other software like ERPs or PCMs can cover what a PIM covers. After all, aren't they all organizing product data or content?

While these other systems are valuable resources, they don't do the same things that PIM software can do. For starters, they don't map attributes and taxonomies of product data for each endpoint seller, sales channel, or marketing channel. They don’t include all product data in one place, either. What PIMs and ERPs have in common is matched in equal part to things they don't have in common.

FAULTY: Only the C-Suite Has a Say in PIM Implementation

A PIM impacts multiple departments:

Product development uses it to organize design specifications
Then marketing develops additional product data to go to market
Web development harvests the necessary details to build product pages
Customer service accesses data to answer queries, upsell and cross-sell
IT plays a role in the implementation, management, and security of the product catalog
And the C-Suite accesses product data to look at the future of the brand and its products

Because a PIM is used by multiple departments, all impacted teams should have a say in its implementation. Identify who will be affected and elect a spokesperson for each team. One individual or team will have the final say (probably the executive team), but multiple departments should have a voice.

FAULTY: PIM Software is for Larger Brands

The false notion that PIM is only for big enterprises robs many brands of reaching their PDS goals and their full potential. The complexity of digital commerce today requires even small and medium enterprises to manage their product data well for all endpoints.

Each brand will look at its need for PIM on a case-by-case basis. Start by working through the challenges in managing product data, preparing for launch, and collaborating internally where product data is needed. Determine what the status quo of both speed and efficiency are, and then review what those could be with the implementation of a PIM.

FAULTY: A PIM is Too Much Work to Implement

A PIM might feel like “yet another software to implement.” It might feel like “just another software to onboard the team to”. And with the collaborative nature of PIM, that could mean a lot of onboarding.

Fortunately, the next-gen PIM answers the market need for a faster and simpler PIM implementation process. A recent case study on next-gen PIM implementation for Sherrill Furniture Brands offers some exceptional takeaways from Lacey Griffith, VP of IT at Sherrill. Many of his quotes speak directly to the partnership his team developed with Amber Engine.

Read the case study to see what the PIM implementation meant for Sherrill Furniture Brands.

FAULTY: PIM is Too Expensive

PIM software was definitely expensive in the early 2000s. Legacy PIMs were that heavy software installed directly to computers, making its maintenance and update a constant drag on IT budgets for brands.

In the age of the next-gen PIM with cloud-based updates and subscription-based models, the cost of PIM can be offset faster than ever with the ROI of massively competitive time to market and lightning-fast internal processes.

Learn how to calculate the ROI for a PIM, and then ask yourself: can your bottom line afford not to implement a PIM?

PIM Is Business Critical Series: Most Common Faulty Logic Around PIM—Are You Guilty?