Fixed pricing has actually only been around for about 150 years. Before that, personalised pricing was the norm - a vendor would charge their best customers less than those who shopped with them less frequently. Haggling and bartering were often how prices were determined, and where a vendor knew a customer could only afford a certain amount, they would only charge what they knew was within that customer’s means. That seems a lot more fair than the fixed price system in many ways. But, nonetheless, fixed pricing won out.
Fixed pricing changed the relationship between vendor and customer in substantial ways. Under personalised pricing, there was an unspoken obligation that when you entered a shop, you would purchase something - the same as with restaurants today. Under fixed pricing, however, customers were free to browse and to make their own mind up as to whether they would purchase or not. Thus began the era of shopping as we know it.
It’s difficult to imagine finding the person in front being charged a different price from you at the supermarket. The idea seems to alien to us that many of us would consider it unfair. But this received notion of fixed pricing is under some debate in an era where businesses have access to more information on their customers than ever before. The application of big data and intelligent machine systems are promising a more personalised shopping experiences, tailored to meet the needs of individual consumers.
Deep data collection and analytics are now allowing retailers to have a better understanding of the ways in which they can entice their individual customers into a purchase. Inference can be taken from your postcode, from who your friends are, from your credit score, and whatever other crumbs of data can be picked up from your browsing history. For example, a travel website recently hit the headlines for ascertaining that consumers using Apple Macs were prepared to pay up to 30% more compared to all other computer users, and thus adjusting their prices accordingly for those users.
Some retailers in European countries have also initiated ‘smart pricing’ strategies using electronic price tags that allow a retailer to change the price of individual products up to 90,000 times a day. A trial on two Spar stores in the Greater London area showed that dynamically pricing their food hall products resulted in increased revenue and a 2.5% increase in profit. Another result was a 30% drop in food wastage. This is, as such, the factor on which they are selling the dynamic pricing product: eco-efficiency.
A company called Market Hub have created a piece of software named Pulse, which analyses the weight, stock, sales, and competitor pricing of products to help retailers price their products in a way that maximises the probability of a sale. Roy Horgan, the chief executive of Market Hub, explains:
“If you have enough data you can get closer and closer to the ideal, which is giving your customers what they want and at the time they want it, rather than overwhelming them with deals.”
In short, whilst it may take consumers time to adjust to the idea of such rapidly fluctuating prices, once they see the benefits of dynamic pricing for getting the best deals, they may well change their minds.
But whilst dynamic pricing is on the increase, we are not yet at a point at which we can reasonably offer personalised pricing outright. B&Q tried it a few years ago, testing electronic price tags that showed different prices based on data gleaned from the customer’s smartphone. The idea, they say, was to reward regular customers with special offers and exclusive discounts - a bit like the shopkeeper of old. The brand denied the accusation that the trial was designed to ascertain who might pay more based on their purchase history.
If dynamic and personalised pricing takes off, the relationship between retailer and consumer will undergo a transformation. Whilst we search for the most discounted price, the retailer will be scouring the data to ascertain the most high-value customer.
If this sounds like a positive for those on a low income, allowing this group easier affordability, then that’s an assumption to be snuffed out. Retailers are more likely to offer deals to those who spend more with them, or those whom the data identifies as being able to afford more, as an incentive to purchase further. So whilst personalised pricing has the potential to be a democratising force for good, it could equally have the opposite effect.
This all means, of course, that there is an ethical consideration to be taken into account if the idea of a personalised pricing structure is to be implemented. After all, the depth of detail required to accurately ascertain whether a person would be prepared to pay more or less for an item would have to be incredibly thorough. For example, a person may live in an affluent area, but have little financial means themselves. To know this, a retailer would have to have access to some extremely personal information.
That being said, there is one major benefit for businesses that do choose a personalised pricing strategy. Theoretically, fixed pricing can be ineffective. Some customers may have been prepared to pay more, whilst some would have purchased if the item had cost less. Personalised pricing, on the other hand, could prevent this loss of revenue. Nonetheless, consumers are generally adverse to the notion that another customer would have paid less than them for the same item, and were they to find out that this was occurring, there is a strong chance they would take their business elsewhere.
Where the product itself is personalised, however, we know that customers are prepared to pay a price premium. Technically, the customer is buying a different product from others, and so the pricing would necessarily differ. But as to whether this premium could be charged based on data on individual customers, it is more than likely that this would put customers off.
Whilst personalised pricing is entirely legal, it is very risky to businesses. There are instances in which it can be beneficial to companies and consumers alike, but the disadvantages appear to far outweigh the benefits. Discounts for regular shoppers or first-time buyers are a way of personalising pricing, and are regularly used, but anything far beyond that is likely to land companies in hot water.
There may be a solution in the future in which the pros of personalised pricing outweigh the cons, but until such a solution becomes available, fixed pricing remains largely the fairest, low risk strategy.