The Associated Press had a great article that I read today (in the SF Chronicle) on the use of advanced mathematics to help determine product pricing strategies. So-called price-optimization tools from companies such as Khimetrics (acquired by SAP) and Zilliant analyze massive amounts of historical sales data to find clues for better pricing that would be difficult to discern without their sophisticated models. (These software systems cost in the 7–figures—assuming that Khimetrics&Zilliant apply their own analysis to their own pricing in a kind of post-modern self-reflexive business analysis, their customers must be hugely self-conscious about the “optimization” of their bill).
This whole field of analysis in part began, according to the article, when Khimetrics’ founder, Ken Ouimet, was studying complex systems in a university Physics department and he epiphonied (which should be verb) that shoppers have no more sense than a hydrogen atom (or something like that). Next thing you know, mathematical models developed to simulate the motion of atoms in gas are being used to model the purchasing behavior of beer-and-Doritos-buying consumers.
The article and its sidebar have several interesting examples of the successes of these systems. The systems determine, of course, which products have price elasticity and which don’t. That’s not necessarily difficult for experienced retailers to figure out. What is difficult is to fine-tune pricing on a huge inventory of widely differing categories of products with barely discernible differences within categories.
What’s even more interesting is their analysis of relationships between products and subsequent recommendations to exploit correlational behavior. Beer drinkers, for example, will pay careful attention to price when buying their brew (“10 cents cheaper? Mickey’s Big Mouth for me!”) , but will snatch up snacks to go along with the beer with little concern for cost. So, drop the margins on beer and crank them up on Cheetos—balance this adjustment correctly and you’ve just increased your bottom line.
And guess what? Those consumers care even less about price during big sporting event weekends—turn the pretzel-price up even higher during NCAA Tourney action! Increase the price of mint leaves during Kentucky Derby weekend and you’re golden. Who would have thought that sophisticated mathematics could improve the profitability of such unsophisticated businesses as Safeway’s and Albertson’s.
Personalization/Individualization is a consumer theme that has hit practically all consumer markets, with the extreme perhaps being the ability to completely customize your Nike shoes online so that no other shoe in the world is identical to the pair that you buy. This is normally viewed as empowering for consumers: a good thing.
Consider now the logical continuation of price-optimization. With store cards (e.g., Safeway cards) that people use to take advantage of item discounts, companies are amassing large amounts of personal information that can be correlated with buying habits. Cross-correlate this data with other databases that can be purchased from other sources, and the ability to personalize pricing becomes incredible once price-labeling become easily and quickly changeable (be afraid when grocery store prices are shown with LCD displays).
Herein lies the dark side of too much power from too much information.
Your price-optimization consultant tells you that students coming back from the bar after midnight don’t care too much about the price of frozen pizzas? Nudge those babies up by 15 cents every late-evening and watch your profits climb. Obese people less sensitive to the pricing of chocolate truffles? Put a weight sensor in the gourmet candy aisle. Mercedes drivers less discriminating towards wine prices? Do I really have to spell out for you what to do?
The AP article I mentioned at the beginning of this post predicts that store prices will become more like the mystical pricings of airplane tickets, and I doubt many consumers will relish that thought. Have you ever heard anyone say they wish other businesses priced their products like the airline industry? Where two people sitting beside each other who bought their tickets on the same website pay wildly different prices because their purchases were on different days? Imagine that you are in the register line at Virgin Records with the latest Bond DVD in hand, and the person in front of you buys the same DVD causing the price of your identical DVD to increase by $1. Welcome to the world of airline pricing strategy!
The days of setting prices based on a fixed margin, on prices from competitors, or simply on an incremental increase over last year’s prices is becoming a fading, quaint tradition. Welcome to the Machine.
I sound cynical, yes. But still…
I have to appreciate the evolution of process sophistication. Of modern thinking challenging and overcoming the wisdom of experience (goodbye Willie Loman). This is the essential nature of science, of business, of innovation: new ideas obsoleting the currently accepted lore. I particularly like seeing advanced mathematical theory being applied to such innocuous business processes as the pricing of ketchup. Luddites take note!
Truth be told, I’ve always had a warm spot towards the practical application of esoteric mathematical theory. In fact, since my college days I’ve had a warm spot towards the mathematical discipline of Information Theory (welcome “information theory” googlers!), probably because I tried a long time ago to apply it to neural signals and failed completely (but others eventually succeeded).
Information theory tells us, well, how much information is in something and how much information can be transferred by a transmission channel. How informative is the weatherman in San Diego when all he predicts in every forecast is that the weather the next day will be sunny and in the 80s? Even if is accurate 95% of the time? Information theory would tell you that his information content is low because there’s not much information in declarations of a near sure thing (Listen and be astounded: I am here to tell you that you will take a breath in the next 60 seconds! See?! How amazing is that?).
That being said, my prediction is that the next New Thing in business/marketing will be an information theoretic approach to marketing. Some marketing channels will be proven to have much more information capacity to target consumers than others, and the capacity of each channel will be calculated to the nearest bit, allowing companies to charge millions of dollars for advice on which channel will provide the highest information ROI for your marketing message. Advertising a NASCAR race on American Idol, or promoting hearing aids in Mad Magazine? That’s less than 1 bit of advertising information. Advertising for either product in Golf Magazine, however—that’s called maximizing your channel capacity.
Informationtheory.com is already taken. Marketinginformationtheory.com is not. What’s your guess on how long until all of the latter’s related domains are taken?