Firms selling things have a dilemma. Price something too low, and, whilst it will sell well, it won’t make enough money to be worth doing (leading to the old joke: “We’re selling each item at a loss; but, don’t worry, we’ll make up on it in volume.”). Price something too high, and you won’t sell enough widgets to make enough money. The traditional view on this is that it is a tradeoff; find a mid-range price where you sell enough widgets at a high enough price. If you can’t do this, then the business isn’t viable.

This is finessed by the notion of adaptive pricing. This is where the same widget is sold to different people at different prices. This makes more businesses financially viable. This is where firms adjust prices based on some information that they can observe, or some structuring of how/when/where/to whom the products are sold:

• Selling to different demographics based on broad ability to pay. Discounts for students or retired people, who are likely to have a lower income. Changing prices at different times of the day, based on the demographic that is around (e.g. a price premium for buying a coffee at the station at peak commuter time; or, more simply, the idea of peak time tickets).
• Rewarding time/organisation: tickets come on sale at a particular date/time, but there are only a finite number at that price. People who are time rich/cash poor can spend time to be organised to buy at the cheaper price, whereas people who have more money don’t have to spend the time, they just buy at the higher price later.
• Selling at different prices in different locations. This has a dark side too; some firms have exploited the lack of transport options of poor people living in cut-off areas by selling at a higher price.
• Auctions, where items are sold for a bespoke price based on demand.
• Secondary markets, where a firm sells widgets cheaply and efficiently, but a secondary retailer (such as a ticket tout) buys up some of them and sells them on to the final purchaser at an inflated price.
• Hiding prices. Rather than a price being given up-front, you have to go through some intermediary system that judges your ability to pay, or your need for the product, and adjusts prices accordingly. The watch shop that judges whether you are a middle-income watch enthusiast or a rich person who wants to brag about the cost of their watch; the retailer of tools who judges whether you will be using the tool day-in-day out or are an occasional user who would buy it for a sufficiently low price.
• Similarly, making use of your purchasing history to adjust prices on an online system.
• Micropayments. Rather than paying up-front to purchase something, you pay by the number of minutes/hours that you use it, or what you use it for.
• Time-adjusted pricing. You show an interest, and if you want it right now you pay the price; the price goes down with time, but if you wait too long you run the risk (perhaps entirely artificially generated) that stock will run out. The TV-based retailer PriceDrop is canonical here.
• Rewards. You all pay the same price up front, but more price-sensitive customers are given some of that money back as vouchers so that their average spend per widget is lower in the long run.
• Direct demand-adjusted pricing. Uber’s entirely-up-front “surge pricing”, for example. Again, speaks to the time/money tradeoff; someone who needs a lower price might be prepared to wait for half-an-hour to see if surge pricing goes away.
• Artificial hobbling. You all buy the same product, making manufacturing easy, but some features are turned off on the lower product range. Tesla cars work like this; you can buy a cheaper version, which has a lower distance range; but, the hardware is the same as the premium product, the distance is just limited by a software switch in the cheaper version.
• Things that seem more different. The same object sold with changes to the branding. Surplus stock sold to a poundshop on the condition that they repackage it. Cheap train tickets sold through a different brand, but when you show up you are on the same train in the same seats as people who paid a lot more.
• Superficial benefits. Exploiting that some people will pay for “the best” regardless. First-class train travel is probably a decent example here; a slightly more comfortable seat and free tea/coffee, but sometimes at a price premium which seems irrationally larger.

I would make an educated guess that cracking adaptive pricing will be one of the big innovations in business in this century. It is increasingly used, but there is still a huge amount of finesse to do here. Already, supermarkets are experimenting with systems such as electronic price displays, allowing dynamic adjusting of price during the day, either by broad demographic shifts, or by minute-by-minute demand. And there are already critiques: the transport company that (algorithmically) increases its prices following a natural disaster, the company that (algorithmically) sells the music of a recently-dead star at a premium.

Interestingly, there is a weird potential consequence to all of this. Will this mean that differences in income become less pronounced? If I had an ideal adaptive pricing system, where, say, I charged people not a price, but a proportion of their income, for my product, then that would have the outcome that people would de facto have the same income. Clearly, the systems above are not at that level yet; but, each adaptive pricing innovation brings us closer to that.