Industry experts say that product data is expected to go through dramatic changes in B2B markets, both in how it’s used and how it’s structured. These changes will have a profound and positive effect on the overall customer experience. Another way to describe this is a shift from traditional product data, or “discovery data,” to a contextual product experience, or “conversion information,” as stated by Jason Hein, the B2B lead at Bloomreach and long-time product-data consultant to distributors and manufacturers.
While product data has seen major improvements in the past five to 10 years, a massive opportunity remains for the next five years. This opportunity is about making product data more usable, or consumable, for B2B buyers. In other words, it’s about the needs and shopping requirements of the customer.
Many companies have a good amount of product data on their website. However, how it is organized and presented often falls far short of meeting customer needs, and the products aren’t discoverable.
To be discoverable, the data must be optimized for search engines, as this is where a majority of B2B buyers begin their journey. Appropriate keywords need to be aggressively employed. Failing here usually means a buyer does not take the next step to shop and buy from a distributor’s site.
Next, understanding how the customer searches is paramount. How will they ask the question to find what they need? Does the product data alone address what they need? In many cases, the answer is no. Assuming the buyer has made it to a distributor website, they need to be able to find the product. If they know the SKU number, it may be simple to find. Of course, if a SKU number is known, that also makes it easier for a buyer to purchase from another pure-digital seller, such as a marketplace.
Often a shopper goes to a distributor website, enters a search term, and is presented with page after page of product options. That isn’t helpful. The quicker and easier it is for the customer to filter and find what they need, the better the customer experience. So, how can the customer experience improve? For this, proper product taxonomy and filtering is important.
A new era of product information is contextual. Contextual information can be described as marketing information and/or conversion information as it can significantly increase revenue by improving the customer experience.
Additionally, if a buyer doesn’t know the name or SKU of the product and needs assistance in configuration and/or selection, having appropriate and useful product selectors and configurators enhances the customer experience. This is a capability we see rapidly increasing in importance in the future. Companies that can provide these tools, whether it is manufacturer or distributor provided, make it easier for customers to find what they need and keep the business.
After all this, what about conversion? The result everyone wants is a transaction, regardless of the method or channel that takes the order. Keeping the customer at the center is key to providing the information a customer needs to find a product, then transact. Websites will always play a critical role in assisting in the order process, which helps justify the digital channel.
Where Product Data is Going
So, how should distributors approach product data to increase the chances a shopping experience will lead to a transaction? Let’s look at where product data is going.
First, it is critical to ensure the 4 Cs of product data (thanks to Hein for the framework) are met:
One major area of opportunity for improvement in product data is in personalization. Personalization uses customer information to assist in presenting the right information based on a buyer’s role or segment/sector they are in, attributes that are usually slow to change. Personalization is already important in the B2C world as our basic preferences don’t change much over time, and data can help predict what we like and need.
Companies that will grow the quickest in the future are those that embrace contextualization. A B2B buyer’s behavior is generally dynamic in that they could be working on one project in the morning and another in the afternoon. That means the context of what they do is changing, so they require different products and solutions.
Localization is also important to both personalization and contextualization. We’ve worked with distributors where customers call a part one thing in one part of the country and something else in another part of the country. Having that context is key when a customer searches. This is also information a distributor is uniquely qualified to provide as a manufacturer is not likely to refer to a part by multiple regional names.
A marketing department can also be a resource for and provide contextual and conversion-related information that is solution- or locally oriented to differentiate product data.
Such differentiation is crucial if you want to show up in Google and other search engines. If I search in Google and over 100 distributors have the same product data, how does Google know which to show first? Sure, Google applies algorithms based on the device used, location and Core Web Vitals scores. Outside of that, Google will generally use the site with the highest domain authority. For example, if the product is available on Amazon, that usually appears high in the search engine results page due to Amazon’s massive domain authority. Relevant contextual information helps a distributor differentiate products and leads to higher conversions.
Here’s what to expect with product data in the future:
- A move away from synchronous emails and Excel files for updates. The new process will be automated, streamlined, and more agile – such as syndication of data with manufacturers. Automated data feeds fix the problem of stagnant data that comes from updating data through an emailed Excel sheet, outdated by the time you receive it.
- More detailed data. This includes a move from 20 fields of attributes to hundreds.
- More data normalization (such as consistent measurements across manufacturers).
- Distributors will use all data available from manufacturer, not just a subset. More will use services to analyze and bridge the gap between available and used data to make the data more useful to the customer. Data service providers will become a strategic partner.
- The cost of data acquisition will fall over time.