Is big data bad for customers?

Digital technology can be a boon for the consumer. But, says Andrea Galeotti, the new breed of data brokers may be helping businesses


In 30 seconds...

  • ‘Big data’ can be of enormous benefit to the public, but the rise of data brokers means it has the potential to damage consumer interests
  • Data brokers are paid by client firms in proportion to the profits they make; hence the broker’s incentive is to maximise client profits
  • Given sufficient data on consumer preferences can enable firms to segment the market, eliminating price competition in relation to individual consumers, who all are all charged their maximum willingness to pay
  • In this way, a firm has a ‘monopoly’ of the consumers for whom it has detailed data and can extract what amounts to monopoly revenues from them in what appears to be a competitive market

That digital technology has given businesses a vast amount of data on consumers and their preferences is a commonplace observation. So, too, is the widely held view that, while this accumulation of information raises legitimate concerns, it can also be of enormous benefit to the public.

But what if ‘big data’, far from providing a benefit, was being used in a way that gives consumers a worse deal than would have been the case otherwise? This notion is an increasing concern for policymakers and regulators. To see why, we need to look at the data landscape as it has evolved in recent years.

Sitting between consumers and the firms from which they buy products are representatives of a relatively new business sector of which the general public knows little or nothing: data brokers. According to a major May 2014 report on the sector from the US Federal Trade Commission (FTC), these are “companies that collect consumers’ personal information and resell or share that information with others.”

The report points out that these companies collect data from commercial, government and other public sources. The data could include bankruptcy information, voting registration, consumer purchases, web-browsing activities and other details of consumers’ everyday interactions.

The report also points out that consumers are largely unaware of this practice, because the brokers don’t get the data directly from them. And, while an individual broker may provide only a few data elements about a consumer’s activities, together brokers can put all the elements together “to form a more detailed composite of the consumer’s life.”

Intensified price competition?

It is a longstanding assumption that the key concern in the data-broking business is the lack of interaction with (and permission-seeking from) the consumers whose information is being trafficked, but that the upside is that it intensifies price competition among suppliers, to the benefit of consumers, who can enjoy the goods and services they desire at a lower cost.

This, indeed, was the view of the White House’s Council of Economic Advisers, reporting in 2015 to then President Barack Obama. It stated, “We should be cautious about proposals to regulate online pricing, particularly if we believe that online markets are particularly competitive.”

Preferences are a mystery

This is textbook economics: the more information-rich a market is, the more competitive it is likely to be, as opportunities for price-gouging and similar activities are reduced – to the detriment of would-be monopolists and cartels.

Let’s take a simple example. Firm A and Firm B sell interchangeable products and compete for the business of four customers: Jane, Andy, Bob and Susan. The firms have an identical cost base and aim to maximise their profits in their dealings with the four customers. Each of these has different preferences for the products of Firms A and B; in other words, the amount of money they are prepared to spend on them. The two companies would dearly like to be able to gauge these preferences to allow them to discriminate in the prices they can charge each consumer, perhaps through offering personalised discounts.

But, at this stage, they do not have the information necessary. The preferences of Jane, Andy, Bob and Susan are a mystery to them, which means they have to set the same price for all four. This can reduce potential revenues in two ways. One is where the standard price is above the preference of one or more of the consumers, who thus decline to buy. The other is where the standard price is below what one or more of the consumers would have been prepared to pay.

"Digital data broking is an infant business, with policy and regulation lagging behind the rapid growth of its capabilities and its ability to use them"

The broker’s profit motive

Enter the data broker. It is paid by the firms that are its customers in proportion to the profits they make; hence the broker’s incentive is to maximise these profits. How should it employ the vast amount of information at its disposal in order to achieve this end – information capable of dispelling the mystery surrounding the preferences of our four consumers?

One way would be to sell to both Firm A and Firm B everything the data broker knows about those preferences. Each firm could then tailor prices and discount offers according to the preferences of each consumer. Let’s say Jane has a strong preference for Firm A’s product. Knowing this, Firm A can set a high price and extract the maximum amount Jane will pay.

This sounds fine – but Firm B, possessing the same information, can then undercut Firm A’s offer to Jane. From the point of view of the two firms, they are right back where they started before the helpful intervention of the data broker – in a market where the customer is king. In fact, they are in a worse position, because at least previously neither firm had any idea of the consumers’ preference. Now, both firms know all there is to know. For consumers, this is tremendous news, as they pay less for the products in question. Surely this is the “particularly competitive” online market described by the Council of Economic Advisers in 2015?

Perhaps not. Let’s assume the data broker chooses to distribute the information rather differently. It tells Firm A Jane’s identity and preference, and nothing else, so Firm A has all the details on Jane, but cannot tell Andy, Bob and Susan apart. In a similar way, it tells Firm B about Bob’s identity and preference, but nothing about Jane, Andy or Susan, whom the company cannot tell apart.

When both firms had all the available data, offers based on customer preferences would quickly be undercut by the other. But now, when Firm A targets a price aimed at Jane’s preferences, at the maximum she is prepared to pay, Firm B either offers the same price to Jane, Andy and Susan, whom it cannot tell apart, or chooses not to do so. The same is true of Firm A in regard to Andy, Bob and Susan. The broker has segmented the market, eliminating price competition in relation to any customer: they are all charged a price pitched at their maximum willingness to pay.

In this way, each firm has a ‘monopoly’ of the consumers for whom it has detailed data, and is able to extract what amounts to monopoly revenues from them, in what appears to be a competitive market. This is just one example of the hazards posed by big data. Dealing with the myriad problems it causes requires imaginative solutions.

A starting point ought to be ensuring that companies do not ‘data hoard’ or collect more data than is optimal for consumers. Discouraging this could be achieved in two ways. One is through taxation, with a tax proportionate to the amount of data collected, so more data means a bigger tax bill. The second is regulation, with fines for data breaches proportionate to the damage inflicted on consumers.

With the tax solution, it would be difficult for the revenue authorities to measure the amount of data being stored; thus the regulatory route may be more fruitful.

Persuading companies to scale back their data hoards would not only bring the amount of information they hold more closely into line with what would be optimal for consumers, but would also reduce risk of misuse of data by hackers.

Keeping data indefinitely

To end where we began, the FTC report found that some data brokers store all data indefinitely “even if it is later updated, unless otherwise prohibited by contract. For some products, these data brokers report that they need to keep older data.

“For example, they explain that even if a consumer’s address is outdated, it is important to keep the consumer’s address history in order to verify the consumer’s identity. For other products, however, retention of older data may not be necessary. An older address may be less relevant to deliver marketing to a consumer.”

Digital data broking is an infant business, with policy and regulation lagging behind the rapid growth of its capabilities and its ability to use them to the detriment of consumers. The FTC report comes to this key conclusion: “Although stored data may be useful for future business purposes, the risk of keeping the data may outweigh the benefits.”

Andrea Galeotti is Professor of Economics at London Business School