How to prevent 4 common mistakes in your product information

Product information data is designed to help you understand and locate all the products in your “catalog.” Ideally, this means it’s easier for everyone on your team and all of your third-party partners to have access to the same information at the same time – no matter where they are.

However, missing data, issues with naming conventions and naming governance, and other data-related challenges can make it almost impossible to locate what you need. In some cases, this can be more than just confusing; it can look unprofessional to customers, potentially damaging their experience with your products if your data isn’t set up the way you need it to be.

Populating product data means bringing together a plethora of data sources and teams to come up with shared data that becomes part of each asset within your system. This product data then goes seemingly everywhere within your organization as is distributed across all of your commerce channels. And if it’s not serving you the way it should, that may pose a problem.

  • Are you classifying data and naming and describing your products in ways that intuitively make sense for your team and your customers?
  • Is your product data serving you fully?

Here are a few ways you might be missing the mark, depleting the customer experience, and what you can do about it.

1. Your Product Information Data Is Inconsistent

Maintaining accurate product data is essential for achieving success in the fast-paced world of eCommerce.

However, if this data is inconsistent from one platform to the next, it can pose problems for your internal team and external partners. Moreover, this can make it hard for your customers to navigate your company’s products to discover what they are looking for. In fact, 25 percent of online returns result from customers receiving a product that differed from their expectations – often because the product information was incorrect or inconsistent.

Imagine it from the viewpoint of a prospective customer: They find a product that’s almost what they need, but not quite; they need that product in another size or color. However, because of inconsistencies in your product information data, these very similar products don’t share the same naming conventions. Prospective customers struggle to find what they need, so they abandon your eCommerce site and go to your competitor, where they can quickly find the product and purchase. Or even worse – they might purchase a product from you on one platform only to find it selling for a lower price on your eCommerce site. This could cause them to lose trust in your brand.

With more consistent product data, the loss of this sale to a competitor or the loss of trust in your brand could have been easily avoided.


This same kind of error can also lead to major issues internally. Inconsistencies regarding inventory numbers may lead to costly and unnecessary product reordering.

Inadequate and inconsistent data can also lead to inefficient product development. Working from inconsistent data, your team might waste valuable time and resources on the wrong thing. Forty-three percent of organizations have reported that data quality issues were a significant roadblock to efficient product development. A product manager may examine inconsistent data and then use this information to decide on a new product feature, causing delays, necessary revisions, and missed opportunities.


2. Your team uses non-intuitive language

Suppose your products don’t include intuitive language in their metadata and product descriptions. This is another way that you might not be helping customers locate the products they want.

Using compelling, vivid language might be exciting for a product description, but it might also keep customers from locating your product. For example, if you use exotic color names in your product description (think indigo or azure instead of blue, burgundy or port wine instead of red), a customer seeking a blue hat or a red bicycle may completely miss your product offering. Including intuitive language within the metadata makes it easier for customers and your team to locate these products.

This bad data can really chip away at earned revenue. If your brand misses chance after chance to sell a product because customers can’t find it, it may impact your revenue goals. It’s estimated that poor data quality can be blamed for 40 percent of failed business initiatives.

3. Forgetting to Optimize Product Information Language

Similar to leaving out intuitive language is forgetting to optimize your product information data for search optimization purposes. Here’s why: Google recently shared that over 65 percent of product-related searches on their platform include qualifying attributes.

Things like:

  • Waterproof
  • Eco friendly
  • Gluten-free
  • Travel friendly
  • BPA-free

If your product information omits these kinds of qualifiers, you may be missing out on sales opportunities.

You may think that the volume of product data needed today has increased exponentially compared to years past – and you’d be right. For example, you may not have needed to include terms like “BPA-free” for a water bottle just a few years ago. Still, with evolving consumer buying patterns, these kinds of differentiators can be significant.

Furthermore, you need to label these products appropriately to keep up with consumer trends and the vertical in which you operate.


4. Failing to Conceal Internal Language or Naming Conventions

It makes complete sense to draft language or use naming conventions meant only for your internal teams to see. But if you forget to hide this information on your public-facing platforms, it could look messy and confusing to customers who want a simple, easy experience.

This internal language might be related to product lines or marketing campaigns, but it might also include placeholder language until you land on the proper branding or messaging. Or, it might be product numbers or SKUs that mean nothing to your customers – but cloud the customer-facing platform.

Forgetting to remove or adjust placeholder language in the final version – which is easy to manage with PIM (product information management) and DAM (digital asset management) versioning and automatic asset updating across all content – can make your brand look cluttered and unprofessional.

How a smart PIM solution changes the game

Comosoft’s PIM system is an all-in-one solution to help your brand navigate all the complexities in managing product information data, including things like:

  • SKU numbers
  • Identifiers
  • Titles
  • Descriptions
  • Images
  • Pricing
  • Product quantities
  • And more

Multiply all this data by the hundreds or even thousands of products you sell, and it adds up to an insurmountable amount of data to track, manage, and keep up to date. This is especially true when you import product information data from multiple manufacturers and sources, all of which use different naming conventions and data governance processes.

You could spend countless hours reattributing all this data to match ­– or use our LAGO PIM system to handle all this complicated product data and make it work for you. As a single source of truth that’s also connected to your external systems, such as your sales, inventory management, distribution, and eCommerce platforms, LAGO makes product data management simpler and easier.

Ready to learn more? Book a demo today!

Credits: Images on Freepik and pikisuperstar (Freepik)