With the help of consumer data and big data, companies can precisely determine how much a customer is prepared to pay. But in the future, when individuals are allocated their own individual price schemes, we could all wind up paying dearly.
In digital supermarkets—and even in conventional retail—a far-reaching upheaval is in progress. In the past, it was common for the markets to determine prices which applied to everyone, on the basis of the relation between supply and demand. Classically speaking, this market price should reflect the scarcity of the product. This has been the central instrument for information and control, guiding consumers and businesses alike. That is how they decide how best to use their limited resources. Until now.
This world is being shaken up right now. Now companies can precisely predict a given consumer’s shopping behaviour and willingness to pay. This is made possible by collecting consumer data and, by extension, big data. This means that every consumer can have an individualized price calculated for them, reflecting the most that they are prepared to pay. In this way, a supplier can offer two different prices to two different consumers at the same time—based on the spending power or willingness to pay as indicated by the data.
In the past two years, this topic has gained increasing publicity, not least among the German Council of Experts for Consumer Matters and the German Consumer Protection Ministerial Conference. This is a good thing, because the issue does not just raise economic questions, but also profound political ones.
Transparent consumers: mobile and spendthrift?
Our previous shopping and online behaviour on websites we have visited, our location and the characteristics of our device and operating system give hints about our preferences. For example, consumers with mobile devices often tend to compare prices less than users with a desktop computer. The reason for this, whether ease of operability or the fact that mobile users are short on time and on the go, is not important: what matters is that they can be offered a higher price. Are Apple users richer than others, on average? That could mean that they are also willing to pay a higher price.
Prices tailored for individuals have previously only been known in direct negotiations, for example when buying a used car. The difference of course is that in this instance consumers know what is happening and can respond to the situation, for example by not putting on their best suit when they go to the car dealer. Furthermore, in such negotiations, while consumers are still in the weaker position structurally, at least the tricks of the trade are known to them. However, when online prices are personalized, this fundamentally changes the position of the consumer as a market participant. If every individual is offered an individual price, then at-a-glance price comparison ceases to be possible for consumers. Price transparency in the market falls, the cost of price comparison increases.
The consumer’s increasing structural disadvantage
If companies know your needs and behaviour “better than you do”, this shifts the existing power and information asymmetry in the market further against the consumer. When establishing the price, a provider’s algorithm looks at the purchasing and surfing behaviour of the last few years to establish preferences. This is compared with other users’ behaviour information to create a prediction of what price is appropriate for that consumer. Figuratively speaking, the individual is interacting with a company that can see into their head. No matter how smart a used car dealer might be, a conversation with him takes place face-to-face.
Individual pricing will lead to increased profits for companies, as they can charge consumers an individual maximum price. Economic theory may suggest that at the same time consumers with more limited buying power should profit because they can be offered goods at particularly low prices; but it is far from proven in practice.
Individually-set prices can be ethically highly questionable. Were such a system to extend into the medical sector, for example, the prices of urgently-needed medication could become much higher. As a society we must consider whether this is what we want, or whether we should refrain from offering personalized pricing in the health sector. Consumers appear to be conscious of this threat to their welfare. A great majority of the public is against individual pricing. This is demonstrated in negative reactions to known instances of individual price differentiation, as well as current surveys. However, respondents appear not to be aware that the already widespread practice of offering individual price discounts in fact constitutes an individual pricing policy.
Data protection must not entail financial punishments
Consumers who value data protection and take care to prevent any profile of them being accumulated in the servers of “big data” are shut out from preferential individual pricing. If the number of individual discounts increases, the originally advertised reference price must also increase in order to offset these discounts. Data-protection-conscious users are therefore at a long-term disadvantage: they will be obliged to pay the higher reference price.
Evidence for the price differentiation in online shopping is already available in American e-commerce websites, in particular. In Germany this practice was found in a study of package holidays undertaken for the Council of Experts for Consumer Protection. Individual cases are constantly coming to light. But there is little knowledge on the extent of digital price differentiation in Germany. A reason for this can be that evidence of personalized pricing is difficult to obtain. Companies appear to fear damage to their reputations should such practices come to light. However, none of this should obscure the fact that German consumers too will find themselves more strongly affected in the future by personalized discounts.
Personalized pricing needs boundaries
The risk to personal welfare must be reduced and consumers’ data sovereignty must be reinforced. That is why providers should be transparent if their prices are being adjusted to fit individual users. It should be stated openly what data and consumer characteristics are used in calculating personalized pricing. The statement must be made in such a format that the underlying data and figures can be summarized in meaningful and easily-comprehensible categories.
This statement of criteria can also give a hint as to whether a big-data-driven price differentiation using algorithms breaches discrimination law. That is, whether a systematic inequality in terms of pricing should begin to affect certain groups of people: for example, groups defined by religion, sexual orientation, origin or ethnicity.
Existing data protection rules provide a further sticking point: data may only be collected or used to shape individual prices, or passed on for that purpose, if the users have explicitly agreed that it can be used for that purpose. This permission has to be specific to a certain period of time and cannot be hidden in the general terms and conditions. Users must be able to refuse their permission for data processing for personalized price-setting, and still obtain access to the affected platforms, even if they then do not receive personalized offers.