BtoB: In what new ways is predictive analytics being used?
Taylor: For b-to-b companies, the biggest new application is on the supply chain side, or how one evaluates a set of vendors—not only in terms of price but their entire value proposition. A lot of organizations have looked at supply chain management simply as procurement, but it's also about risk mitigation and getting the best price for the enterprise.
BtoB: How might a vendor be evaluated in this way?
Taylor: There are all kinds of capabilities a fuller-service supplier might bring to the table that a lower-priced vendor would not. There are modules to ferret out where the best value is, balancing risk mitigation with the price of service. Since a lot of marketing services are outsourced, you can evaluate these providers from a b-to-b perspective.
BtoB: How is predictive analytics being used as a marketing tool?
Taylor: To understand brand preferences, for one. Focus groups can be surveyed about their preferences for particular products, ranking those attributes from high to low. Applying a concept called "conjoint analysis" on these data points, a manufacturer can then invest more in areas that rank highest. And since any survey is fraught with misinformation, you'd ask the same question in a different way later in the survey. This is considered the workhorse in the marketing arena.
BtoB: It sounds b-to-c. How might this apply in a b-to-b sense?
Taylor: A manufacturer can help his b-to-b customers who are involved with a commodity offering [determine] how to differentiate themselves in the market. For example, you could ask the question, "What do you look at first, logistics or customers?" and one of the dependencies could be if you're offering a commodity product or not. If your product is very price sensitive, you want to think of the customer first. With a highly differentiated product, but with a lot of competitors in the field, you'll want to analyze logistics first.