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Big data, value pricing and fairness

Value pricing has long recognized that products and services have different utilities and, consequently, different values for customers.

June 23, 2014 by Dale Furtwengler — President, Furtwengler & Associates, P.C.

In May, ABC News reported that online shoppers are being charged different prices for the same product. The reporters were astonished and dismayed at the apparent lack of fairness in this practice. Should they be?

The simple answer is no. Value pricing has long recognized that products and services have different utilities and, consequently, different values for customers. We often see this played out in the business-to-business (B2B) space.

A service that provides a 10 percent improvement in bottom line profits is more valuable to a customer that's generating $10 million in profits than it is to a company with $1 million in profits. Any economist worth his salt would tell us that the company getting the greater benefit should pay a higher price.

In retail, the price of a sweater can range from as little as $10 to $120 or more depending upon how important image is to the customer. Walmart customers value frugality whereas Nordstrom customers value quality and the image that quality affords.

Even within a given store chain, a price will vary from region to region depending upon how valuable the item is in that region. I dare say that Minnesotans value down-filled outerwear wear more than the folks living in San Diego.

If value pricing is fair, then why were the reporters so shocked? Was it the fact that the pricing disparity was based on customers' sensitivity to price determined by a profile created from big data?

Big data

If so, it shouldn't have been. Throughout the history of commerce, savvy businesspeople have been looking for ways to do a better job of serving their customers — of providing what they need in the form they prefer. That's good, customer-centric business. Companies employing big data are recognizing trends in the utility products have in various parts of the country, which leads us back to value pricing.

I'm not suggesting that all of the companies using big data are doing so effectively, but in some ways big data is still in its infancy. The companies employing it are learning more all the time. Can big data be misused? Of course, but that's true for everything we create. I can use an iPod to create a party atmosphere or drive my neighbors nuts. That doesn't make the iPod intrinsically evil.

Anyone who has read my blog with any consistency knows that I'm a value-pricing advocate. I believe that it aligns buyers and sellers more effectively than any other tool I've seen. It's also fair to both parties. The key to using value pricing effectively is the ability to communicate the value for a specific customer or prospect.

Online retailers are going to find it difficult to effect that value communication. Consequently, the pricing disparities their big data analysis suggests is going to be perceived as manipulative and unfair. Those perceptions will quickly be followed by distrust, which could easily cost these companies sales. The question companies using big data should be asking is, "Are these small price differentials going to make a difference in customers' decision to buy?" I seriously doubt it.

(Photo by Craig Murphy.)

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