If you’re a B2B distributor or manufacturer looking to go digital, you’ve probably had this thought:
“Our data isn’t ready.”
Or worse:
“Fixing our data is going to be way too expensive and time-consuming.”
And that fear keeps you stuck. Meanwhile, your competitors (or even your own customers) are moving forward, solving problems, and making it easier to do business online.
The thing is you don’t need perfect data to succeed online. But waiting for a miracle (whether it’s AI, a fancy new PIM, or some magic software) isn’t the answer.
That’s exactly what we talked about with Jason Hein, Global Director of Product Content and Search at B2B eCommerce Association on our podcast. With decades of experience in B2B eCommerce (from McMaster-Carr to Amazon Business), Jason has seen it all: the common mistakes, the unnecessary overcomplications, and the smartest ways to tackle product data without stalling digital growth.
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The Real Problem: Most B2B Companies Let Their Suppliers Control Their Product Data
Jason explained that one of the biggest mistakes distributors make is assuming that their suppliers will give them clean, structured, and useful product data. But that’s not how it works.
Big suppliers like 3M, Honeywell, or Bosch aren’t customizing their data for you. They’re giving you whatever standard format they already have. That means:
- Messy attributes – One supplier calls it “1 in.”, another says “1.0 inch,” and a third uses “1” (good luck with filters and search).
- Generic descriptions – If your customers need to understand how a product works, supplier-provided descriptions won’t cut it.
- Missing details – Maybe the tensile strength is included, maybe it’s not. Maybe the coating type is listed, maybe it isn’t.
If you just take supplier data at face value and upload it to your site, your customers end up with an inconsistent, confusing, and frustrating experience.
So what do you do?
The 5 Rules of Clean Data
If you’re looking for a practical way to improve your product data, Jason laid out five core rules to follow.
Rule #1: Correct
It sounds obvious, but if your data isn’t accurate, nothing else matters. If a buyer purchases an industrial adhesive expecting it to hold up in 500°F temperatures, but the real limit is 250°F, you don’t just have a bad user experience, you have a safety issue.
Incorrect data leads to returns, lost trust, and costly mistakes. That’s why before anything else, your first priority should be ensuring data accuracy for your most critical products.
Rule #2: Complete
Ever tried filtering products by a key attribute only to get zero results because half of the products are missing that data? That’s what happens when product data isn’t complete. If a category requires a key attribute (like voltage for electrical components or PSI rating for fasteners), every product in that category should have that attribute filled out.
Without it, customers can’t easily find what they need, and your search and filtering functions won’t work as they should.
Rule #3: Consistent
This is where things get tricky. If one product lists its weight as “1.5 lbs.”, another says “1 ½ pounds”, and another just says “1.5”, you have a mess. That inconsistency creates huge friction for buyers. Filters don’t work, comparisons get harder, and customers feel less confident in what they’re ordering.
A standardized approach – ensuring all measurements, units, and naming conventions stay consistent across products – makes your catalog easier to search, easier to shop, and easier to trust.
Rule #4: Clear
Ever seen a product description so full of jargon that it’s impossible to tell what the item actually does?
That’s what happens when product data isn’t clear. Most supplier-provided descriptions are written for engineers, but your buyers might be procurement specialists, shop floor managers, or business owners. If they can’t quickly understand whether a product is right for them, they’re not buying.
McMaster-Carr does this brilliantly. Instead of dumping specs on a page, they explain what a product does, how it compares to alternatives, and when to use it. That’s what turns product data into a sales tool rather than just an information dump.
Rule #5: Contextualized
Even if your data is correct, complete, consistent, and clear, it still might not be useful in the right context.
Think about gloves. If a food factory worker is shopping for gloves, they care about sanitation and food safety compliance. If a welder is shopping for gloves, they care about heat resistance and durability. Same category, totally different context. Great product content adapts to who is buying and why. Whether it’s adjusting filters, using industry-specific terminology, or showing application examples, contextualized data makes it easier for customers to find what they actually need.
“We Have Too Many SKUs to Fix” and Why That’s a Trap
Another common hesitation? “We have 500,000 SKUs. Fixing all that data would take forever.”
And sure, if you try to clean up every single SKU at once, you’ll never finish. But not all SKUs are equally important.
A smarter approach? Let customer behavior guide your priorities.
- Look at what’s selling the most. These are the products that need better descriptions, images, and structured attributes first.
- Check your search and filter analytics. If people keep applying filters and getting zero results, that’s a red flag that those product attributes are incomplete or inconsistent.
- Identify the categories causing the most customer service inquiries. If people keep calling your team to confirm specs, that’s a sign your product pages aren’t doing their job.
Instead of spending months trying to fix everything, focus on fixing what’s broken where it matters most. That’s how digital leaders improve their catalog without getting stuck in an endless cleanup project. The key here is to set a clear standard for product data and stick to it.
Here’s what that looks like in practice:
Decide how product names should be structured, which attributes matter most, and how you want customers to find products on your site.
Instead of expecting suppliers to change, map their data to your format. This could be done manually, through automation, or using a PIM system if you have one.
Start with your top-selling categories and improve over time, rather than trying to fix everything at once.
If you don’t define your own standards, your product data will always be at the mercy of your suppliers. But once you set expectations and create a process, you regain control, making it easier to scale and manage.
Stop Overcomplicating It
Too many B2B companies let bad product data hold them back. They assume fixing it will take too long or cost too much. They wait for some miracle AI solution or the “perfect” system before making a move.
But the companies succeeding today? They’re not waiting.
They’re improving what matters most. They’re taking ownership of their product content instead of just accepting whatever suppliers hand them. They’re using customer data to prioritize what needs fixing instead of trying to fix everything at once.
And the result? Better customer experience, higher conversions, and an eCommerce site that actually works. So if you’ve been holding back, worried that your product data isn’t “ready,” here’s your sign: It’s time to start.
