Is Customized Pricing Brilliant Or An Imminent Disaster?Written by Mark Rasch
Attorney Mark D. Rasch is the former head of the U.S. Justice Department’s computer crime unit and today serves as Director of Cybersecurity and Privacy Consulting at CSC in Virginia.
In the war between retailers and customers, where retailers want to charge the highest prices they can and consumers want to pay the least they can, the weapon of choice for both combatants is knowledge. The more retailers know about their customers, the more likely they are to be able to target advertisements and pricing specific to them. Consumers, likewise, can comparison shop for products and thereby bargain efficiently. But in this war, consumers may ultimately lose, because it is the merchants that pay for the very tools consumers use to find the information they need. A recent patent by search giant Google (NASDAQ:GOOG) may fundamentally change the sales process from a 21st Century marketplace back to a 7th Century shouk, with prices based on sellers’ perceptions of who their customers are and what they are willing to pay.
Last September, Google applied for a patent for a method of “dynamically pricing electronic content.” The patent application explains that the technology will be used for “determining a likelihood that a group of users will repurchase an item of electronic content, determining that a particular user is more or less likely to repurchase the item of electronic content than the users of the group, in response to determining that the particular user is more or less likely to repurchase the item of electronic content than the users of the group, adjusting a base price associated with repurchasing the item of electronic content, and providing the particular user with an offer to repurchase the item of electronic content at the adjusted price.”
Translation? Based on all the personal information Google has gathered about you, it will determine whether you are likely to pay more money than others for the same product and then charge you accordingly.
Now, we are all used to both targeted advertising and targeted marketing. If we only buy things with coupons, a retailer may be inclined to send us coupons. If we buy luxury items, we may get ads for those types of items. Prices may vary based on regional differences (higher in Alaska and Hawaii), retailer costs (Manhattan, N.Y., higher than Manhattan, Kan.) or seasonal fluctuations. In some industries, it is accepted that different people may pay widely different prices for essentially the same thing—think the airline industry, for example. We are used to loyalty programs that may offer participants a discount for goods or services in exchange for parting with personal information.
But the Google patent, if really applied, is something different. There is a huge difference between “dynamic advertising” and “dynamic pricing.” In the case of the former, for example, say I get an ad for a Toyota while my more affluent friend gets an ad for a Lexus. Fine, I didn’t want the Lexus anyway. In the case of the latter, we each get ads for the same Toyota Camry, but his price is different from mine. And that is based on what Google, and possibly the “Internet,” knows about him.
That’s the beauty and the misery of big data. The Web (particularly coupled with non-Web information) can create an intricately detailed and nuanced profile of individuals, predicting not only what they want (sometimes better than they know what they want) but also what they are willing to pay. It’s more than knowing the difference between an “urban core” consumer and an “elite suburbs” consumer. Big data can know whether you are a tech gal, an Apple fanboy or an Android geek. It can know what factors affect your personal purchasing decision—speed, design, ease of use, etc. And it can know what things you are willing to pay for, in addition to how much (or how much more) you are willing to pay for it.