When an online seller of, say, power generators, displays a long list of product attributes on each product page, there’s a good reason.
Because as online customers click those attributes, revealing the ones most important to them, they provide the seller with invaluable information for subsequent marketing and merchandising efforts, says Jason Hein, principal consultant and senior strategist at consultants B2X Partners.
It enables the seller to understand in detail “what customers buy and how they buy,” Hein said during a presentation at last week’s B2B Next conference, which hosted more than 700 attendees in Chicago.
Hein, who has formerly worked at Amazon Business and industrial distributor McMaster-Carr, offered a simple example of purchasing everyday apparel, a category subject to extensive competition. “We all buy socks,” he said. But if an online seller lists such information as the thickness of the sole, the material and how the toe is designed, it could compile information on the attribute a customer most often chooses. “It could then anticipate [the customer’s] needs and show him a banner ad for that particular product attribute,” he said, adding that this is a “potential source of success in a market of disruption.”
But there’s more to this strategy, he added. Hein encouraged his audience to take a multifaceted approach to managing data, including:
- Allot 30 days or more to build a data model, including the taxonomies that group similar products into categories and lists of product attributes that describe each product’s features; these features include descriptive qualities like size and material, performance qualities like power output and related accessories.
- Acquire and learn to use product information management software, or PIM, that goes beyond the capabilities of a product database to help manage consistent product descriptions and identify discrepancies.
- Develop a company culture that values data and learns how to continuously improve how it’s gathered and put to use. “Constantly look at how customers are interacting with product data pages, look at heat maps and click paths,” Hein said, adding: “You need data, but you also need a culture that values data. You can’t be afraid of data—gotta love it.”
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