Are you paying more than your neighbour? It could be 'surveillance pricing'

The union soldier NDP is introducing a question on midweek to censor so-called surveillance pricing, where businesses offer up different prices based on consumers' personal data. 

Winnipeg Centre MP Leah Gazan is leading the motion, which would ban the practice both online and in retail stores.

Consumers are likely familiar with dynamic pricing, where prices change automatically in response to market factors — like when ride-share rates increase in response to a surge in demand or prices change at certain times of day.

Surveillance pricing — also known as algorithmic personalized pricing — uses a consumer's personal data to offer different prices to individuals, or groups of individuals.

"When suppliers are collecting your data, analyzing your data … the reason they're doing this is to try to get as close as possible to your maximum willingness to pay," said Pascale Chapdelaine, an associate professor of law at the University of Windsor who researches algorithmic pricing. 

"From a competition law perspective, this is problematic." 

Of course, in an online shopping context, individual shoppers don't know what anyone else is paying for the same product.

Personalized pricing requires tracking online behaviour. 

Advertisers and data brokers "are recording basically everywhere you go and then drawing inferences from that. So where do you like to shop? What kinds of things do you like to read?" said Christo Wilson, a computer science professor at Northeastern University in Boston who researches digital consumer protection issues. 

Data brokers can use this granular information to create "massive dossiers" about consumers. They can then connect those digital trails with public records, such as your name or any property you own. That can in turn be combined with loyalty card data, linking consumers' online and offline lives.

We've seen high-profile examples of surveillance pricing in the U.S. For example, an investigation found that online grocery delivery platform Instacart was experimenting with personalized pricing, in which American shoppers were offered different prices on the same items at the same store at the same time. The disparity was such that the highest price was as much as 23 per cent higher than the lowest price. 

Instacart announced in December it was discontinuing this experiment.

Last month, some Washington Post subscribers were notified that their rates were set to increase, but told that the price “was set by an algorithm using your personal data,” although it's unclear exactly how personal data was used.

Christo Wilson says it's hard to gauge how much surveillance pricing is actually happening. 

There's evidence "there are companies collecting these kinds of data and trying to sell this capability as a service — like, 'We will take data, we will give you fancy algorithms to customize prices,'" he said. "But the extent to which those are being adopted by different e-commerce platforms or retail stores, we don't actually know."

Canadian law offers some tools for addressing this practice. Chapdelaine said "there are reasonable arguments to make under personal data protection laws that this would be an illegal practice," and that "it could constitute a deceptive marketing practice." 

She said with algorithmic personalized pricing, "it's not the price that is offered to you that is problematic — it's how it was arrived at."

In January, the Competition Board of Canada released the results of consultations on algorithmic pricing. 

Bradley Callaghan, associate deputy commissioner for policy planning and advocacy at the Board, said they heard from businesses that argued "they might be able to offer or target maybe more price-sensitive consumers and offer a lower price."

But consumers voiced concern about whether personal details such as socioeconomic status or where they live might be used to determine pricing decisions.

"The key thing that we really heard from individuals is about a lack of transparency," Callaghan said.

The Competition Bureau's mandate focuses on anti-competitive practices rather than a broader sense of "fairness." Callaghan says they're looking for factors "that lead to a softening of competition" — such as market concentration in which all companies are setting prices based on the information of a handful of data providers, "or putting companies in a better place to be co-ordinating their prices." 

An Abacus poll from March 18 found that while awareness of the term "algorithmic pricing" is quite low among Canadians, when it was explained to them, a little more than half of those polled considered the practice unfair. 

Wilson argues, "we have to start with transparency." 

"If we at least kind of know what's going on, then maybe we can make informed decisions."

Senior Technology Reporter

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