Give customers the product information they want

I did a little research and had some specific criteria in mind for both products:

The Corral

• 36 inches high (Weimaraner’s can jump)
• 72 inches in circumference (Weimaraner’s get big)

The Monitor

• 32 inches (big enough for spreadsheet work)
• IPS Panel Type (hardware guides told me this was best).

Much to my surprise, I found that validating these products against my criteria involved having to jump between multiple retailer’s websites to cross-reference SKUs and model numbers and do a lot more scrolling and squinting than I expected. In some cases, the product information I needed was embedded into long descriptions with no way to filter or search, and in other even worse cases, completely missing! These gaps in information made finding the product I wanted difficult. These retailers were failing to give prospective consumers critical information about the products they were trying to sell!

Filling in Product Information Gaps

The notion of using mandatory fields to govern the presence of critical information within your product catalog seems both obvious and easy to implement for retailers. The reality is quite different though. Product catalogs today are massive and the challenge of ensuring integrity across such a large amount of data is only part of the problem. In an increasingly competitive post-Covid landscape retailers must also ensure their data stands up to the intense scrutiny of discerning customers and search algorithms whose requirements are constantly changing; The “Set it and forget it” mindset of yesteryear no longer works, even in the B2B Industry. To properly validate the presence of important product information and ensure “Completeness” sellers need to be able to:

1. Define the unique combination of critical information consumers need for each product type.

2. Account for multiple versions of this critical information across languages, regions, and sales channels.

3. Quickly and efficiently identify and fix missing information across an entire product catalog.

Let’s dig into these a little more:

The starting point for all product governance is defining exactly which information consumers need. Most enterprises today measure their product catalogs in the tens or hundreds of thousands of products and offer a diverse range of products with radically different product characteristics. For example, a big box retailer may sell Washing Machines and Laptops alongside High Heels and Blue Jeans. The information consumers want for each of these four products is radically different, but they must coexist and be accounted for in the same catalog. In this case a properly built product catalog will have hundreds or even thousands of attributes organized in a taxonomy of discrete product-type structures where the unique requirements of each product type can be accounted for. You cannot have just a few global mandatory fields, you must tailor your mandatory fields to the unique requirements of each product type.

The next consideration in ensuring a Product’s completeness is accounting for the contextualization of the product’s information across languages, geographic regions, and sales channels. It’s not enough to know that the “Description” of the English version of our Product on our eCommerce Website in the U.S. is filled out; we also need to know that the Spanish version of our Product in our Syndication channel in Argentina is ready for our customer’s eyes. Every adaptation and translation of our product, no matter how subtle, must be accounted for as part of our completeness check.

We can’t talk about product completeness without also discussing how to repair these holes in our product catalog. This can be a massive effort. A catalog of 100,000 products with 50 attribute fields has 5,000,000 data points that need to be monitored and fixed. This is an almost insurmountable effort if this product information is spread across multiple sources of truth like an ERP, eCommerce website, or even Excel spreadsheets (which is more common than you may think). Just having a single place of maintenance like a PIM system greatly helps this effort. Next, you need to be able to track and analyze the completeness of your products across the entire catalog and within different product types, business groups, websites, and regions.

Once we identify the missing information it’s important to have productivity tools, automation, and even solutions that can leverage suppliers to help fill in the gaps.

In my own endeavor, I ended up finding a Pet retailer site that gave me the exact specifications I needed and purchased a corral for my Weimaraner. This experience then led me to revisit the same site earlier this week when I needed to order a new collar because I was confident that I could validate what I was buying without having to cross-reference, scroll, or squint. In contrast, I struggled to validate the information for my monitor, which I decided was more of a “nice to have,” and gave up completely. The high-quality data of the Pet retailer earned my repeated business while the poor data from the Electronic retailers cost them a sale.

Customer experience depends on product experience

Many retailers today invest significant time and money to drive incremental improvements to their online customer experience by focusing on things like rich-content, SEO optimization, and merchandising. While these are all important considerations, what’s often forgotten is that these areas all have an underlying dependency on complete and accurate product data.  Companies who invest in the basics of building a strong foundation of complete product information find a positive ripple effect through all components of their digital commerce infrastructure that has a tangible impact on their bottom line. Stated simply, strive to exceed your customers’ expectations and provide them with more than enough compelling information to help them find what they need and desire from you, and not someone else.