Can Markets Be Fair If Prices Aren’t Transparent?
A conversation on algorithmic pricing, consumer protection, and the future of digital markets in Canada.
What happens when companies can predict exactly how much you’ll pay, and charge you right up to that limit?
In this episode, Cara Stern sits down with Vass Bednar to unpack the rise of “surveillance pricing,” a growing practice where companies use everything from your location to your purchase history to figure out the maximum price you’re willing to pay.
At its core, this is a conversation about fairness. What happens when markets become less transparent, price signals become individualized, and consumers lose any common understanding of what things “should” cost?
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Below is an AI-generated transcript of the Missing Middle podcast, lightly edited.
Cara Stern: The next big hit to your wallet might not be inflation. It might be that stores can figure out the maximum you’re willing to pay and charge you exactly that price. It’s called surveillance pricing and politicians are starting to debate whether Canada needs to ban it. Today, I’m talking to Vass Bednar, managing director of the Canadian Shield Institute and author of the book, The Big Fix.
She’s someone who’s been writing about the problems with surveillance pricing since before almost any of us knew to worry about it, and we’re so glad to have her back on the program.
Vass Bednar: Thanks for having me.
Cara Stern: There’s algorithmic pricing, there’s dynamic pricing, and there’s surveillance pricing. What is the surveillance pricing that we’re talking about now?
Vass Bednar: Surveillance pricing sort of layers in with that computational data-driven pricing strategy. So beyond using a variety of factors like what your competitors are pricing something at, personalized algorithmic pricing requires excessive data use about who you are, where you live, your behaviours online, sometimes your past purchase history and sometimes where you are and where you’re going.
So it’s a much more invasive pricing tactic that’s supercharged by data and much more common in kind of an e-commerce context, where there’s way more information asymmetry. It’s kind of just you and a screen, whether it’s your phone and a loyalty program or, shopping online. That’s the bigger difference.
Cara Stern: The first time I remember hearing about this type of pricing was with Uber, where, if you’re on an iPhone versus an Android, you’d get different prices. That’s a bare minimum version of this. But then also people started getting used to dynamic pricing with Uber.
What’s different with this?
Vass Bednar: So dynamic pricing suggests supply and demand constraints. I think a parallel would be airlines, where we became pretty comfortable with price fluctuations that we could monitor, but weren’t necessarily tied to the individual. So if you were getting a last minute flight, it was maybe more expensive. You’re booking further in advance. There were more seats available. Now because of data driven pricing, there’s some evidence that suggests about a thousand different data points are used to calibrate the price of your seat on an airplane.
And back to the Uber example, some evidence that if you’re using a business credit card, Uber will charge you more. Again, inferring your willingness to pay and squeezing more there.
Where I think there’s a difference between the kind of supply and demand type of calibrations or I’ll use the euphemism pricing experiments that we’ve seen with Uber is external factors. Say it’s raining. There’s more demand and they’ll tell you prices are higher right now. Or, the Blue Jays just won the World Series, fingers crossed, there’s more people looking for rides out there.
Versus, this ride is going to cost you more, Vass, because you tend to take this route, we know you’re very likely to take this route, and you’re using a business card. So based on you more as an individual. But some of the individual and group stuff is also something we can dig into. I’m worried I’m making it more convoluted than clarifying it.
Cara Stern: I’m trying to understand it because I know different apps that’ll give you discounts based on things you’ve purchased before. I get sometimes with Shoppers, Canadian Tire, or Tim Hortons, they will say, “Hey, we know you like to buy this kind of sandwich and you haven’t bought it in a long time.”
Vass Bednar: What’s your favorite thing at Tim Hortons?
Cara Stern: Sometimes it gives me breakfast sandwich discounts because I like their breakfast sandwiches and they’re good in a pinch. Sometimes it’ll be a little bit of time since I’ve bought a breakfast sandwich because I get them when I have to go drive somewhere far, but it doesn’t happen all the time. And then I’ll get a notification saying, “Hey, you haven’t bought a breakfast sandwich in a while. Would you like a discount on that? If you buy it today, you’ll get this discount.” And to me, that feels like a form of surveillance pricing that already exists.
Vass Bednar: It’s a form of it. But I would say the more insidious is something like the Taco Bell app being able to infer when it’s your payday and increasing the price of your gordita deal versus incentivizing you to come back to Tim Hortons. Tim Hortons is actually a great example because they were investigated by the federal privacy commissioner and many provincial privacy commissioners for their invasive data collection in their loyalty program. Tracking you down to where you are.
An epic study from last year found that Target would make televisions in their store more expensive the closer you were to the store. That’s inferring a probability that maybe you’re going to make a purchase. It makes it harder for people to understand what things actually cost. We’re losing price universality when it comes to the levers we have.
I’m a big fan of the idea that you don’t really need to reinvent wheels most of the time. My joke is shopping our closet: What do we have? What can we wear? Do we have anything that actually suits this? And as Canada considers whether and when we’re going to tolerate this — because there may be some instances where we think it’s appropriate, say for discounting — we need to decide if we’re looking at it from a privacy perspective, consumer protection perspective, or a deceptive marketing angle. There are different ways to get at it.
To your point that it’s increasingly becoming a feature of how we experience markets. Absolutely. Even geographic pricing, which is more blunt. I used to think that my Secret deodorant costs the same at every single Shoppers Drug Mart. And that’s just not the case. And that’s okay.
There was a good Toronto Sun piece from a few months ago looking at Big Macs costing different amounts at different McDonald’s. So it’s not that the pricing differential itself is egregious. It just reminds us that that pricing strategy defies what we may have as an expectation of what the norm is with pricing, when actually something very different is happening.
Cara Stern: I get that the idea is that they’re using your personal information, and it seems people think that’s a little bit icky when people are talking about this. I see Abacus Data did some research into how people felt about it, and they found 83% of Canadians wanted it banned or regulated.
They found only 7% of people are convinced by the argument that this is just supply and demand at work. So I’m trying to understand what is it about it specifically? Is it that they’re using more data than they did before? Because we have had for a long time things like seniors discounts. We’ve had coupons offered to customers who’ve purchased before. There’s lots of different ways that companies have targeted people using their data for so long. And usually you use your loyalty card or their app, and so they’re collecting the data they get from your app, from the app that they created, that you’re choosing to use.
So what is different about it now?
Vass Bednar: What’s different is that, for example, discounts (such as senior discounts) are more blunt and uniformly experienced. If you’re over a certain age, you have equitable access to that discount.
That discount is not predicated on you having a mobile device or using a mobile device when you shop, sharing additional information. Couponing is a very dumb in the sense that it’s not supercharged by data. You and I can still access the same deals when they come in a flyer.
Where we can’t see each other’s universes is in these closed app ecosystems that are more finely calibrated to who we are. Are they necessarily discriminating against us as individuals? That’s where it gets tricky with privacy law. Privacy law is designed for harms that individuals experience, but more often than not, personalized pricing is about segmenting, creating particular cohorts, and particular profiles. And that needs to be part of our conversation.
How comfortable are we with people’s information beyond past purchase history and that relationship that you have with a store? I think our conversation in Canada on personalized pricing feels it very sudden. It feels it almost came out of nowhere. There’s been a lot of learning and overviews and “what do you mean this is happening.” It also comes out of the credit industry.
In the early 2000s, when Canadian Tire was continuing to develop their loyalty program, which is now called Triangle Rewards, they also had a credit offering. And this is more big data seductive era where we questioned less what we were doing with information and were just amazed by what data science could do. Canadian Tire found things like anyone that had ever purchased something with a skull on it in the past was not as reliable to give credit to. And the people that were most reliable was anyone that had ever purchased the little felt circles that you put under furniture. They were given leeway with credit because they’re seen as being responsible. So in that way, your data can privilege you. The personalization of pricing that I think has gotten a bit out of control as a function of our weak privacy law, tends to rely on much more.
Cara Stern: I think it came out of nowhere because you had politicians starting to talk about it. I wonder what can even be done to stop this, because the hard part I’m getting at is, where’s the line? Sometimes you’re like “That senior getting discount over that senior because we know that they don’t buy it, or they haven’t bought it in a while, that’s fine. Knowing that they have this much in their bank account? Don’t like that.” How do we actually draw the line when you’re making policy?
Vass Bednar: Okay, I’ve got a total grab bag on this. You’ve asked me a special question. I love being asked about policy solutions. But I also wanted to offer that algorithmic pricing also happens in labour markets, where we have gig platforms that are monopsonistic.
There’s evidence in the U.S. that a platform for nurses to take overtime shifts had went out and purchased credit and debt load data that they were layering in, essentially proxying a desperation score. So nurses that had more student debt were offered a cheaper price for their labor based on this calculation that said, “they are more desperate for the work and they need it more, so we’re not going to pay them as much.”
I think that’s important in terms of pricing for labour and also that it’s coming for white collar work, whereas nursing is something that we see is quite standardized and fairly predictable with work.
So there are other ways that data-driven pricing is hurting people and maybe not aligned with our values. What can we do? I think the provincial approach, framing as a consumer protection problem, which is what the province of Manitoba is doing, is pretty savvy. Federally, if we wanted to, this majority government could snap their fingers and make an amendment to our federal privacy law, PIPEDA, and say that, profiling, discriminating based on personal characteristics, is just a harmful practice and we can shut it down that way.
Of course, every day I’m refreshing the page looking for AI strategy, privacy policy, online harms. That’s a separate issue. The Competition Bureau, if there were a case that came forward, does have some ways they could think about this. One way that I think is novel is potentially double ticketing, where if there’s two different prices, you’re supposed to give the shorter one.
Is it a form of deceptive marketing?
A new piece of legislation that just says this isn’t allowed doesn’t get us that far because we have to agree on what kind of practice we are pushing back against, without hurting those abilities to get a legitimate discount. And loyalty programs are super interesting because that bargain is more explicit in terms of “I’m going to give up some privacy in exchange for points.”
But even that bargain is starting to fall down as people realize that many loyalty programs are ingesting more about them than they realize.
My biggest hope for Canada is that we kind of keep the conversation going, and don’t just get locked in this more blunt, “yes, no, I support it,” or there are some instances where we’re comfortable with it and we tolerate it, and therefore it is inherently good and helpful. This is not a pay what you can kind. We’re going to calibrate it to what’s possible for you. It’s fundamentally something that is extractive. And the fact that it’s increasingly part of people’s everyday lives and purchasing everyday essentials, I think is particularly egregious and concerning for thinking about Canada’s middle class.
Cara Stern: When it comes to how extractive it is, I understand that’s the goal of it. “Let’s take as much money as we can from that person.” There is a flip side of it where, when I heard about this, I was like, “I’m a pretty frugal person.” Sometimes I’ll wait on something, I’ll set alerts for when something goes down on Amazon and it’ll tell me when it drops to the price I want to pay.
I was thinking, in this case, would it know, “Cara doesn’t like to pay this much for this? We’re going to have to give her a lower price.” And someone who doesn’t mind as much and has more money and can pay more will end up paying more. Is it possible that it’ll turn turn out that way?
Vass Bednar: I’m never a fan of everyday people kind of trying to fight back on these structural failures themselves, but I do recognize there are plugins from Amazon. I’ve tried one.
I’m also in a phase of my life where I’m willing to splurge now and then for convenience. I have used Instacart in the past when I’m in desperate need for some diapers, need a few groceries to get me over the line, my husband’s traveling, I’m tired, or whatever. I’m fine paying a premium. I’m fine definitely tipping someone very well, and I’m fine paying weird fees that Instacart thinks are necessary.
What I’m not fine with is being put into what appears to be from research in the U.S., one of four pricing cohorts, and seeing a different price than is advertised in store and a different price than other people for milk, eggs, and food based on where I live, what I’ve purchased in the past, what other people in my neighborhood tend to earn, areas of the city I spend a lot of time in, or other websites that I go to.
That’s where I think it’s a little bit out of hand. It’s unnecessary.
I’m also totally fine with companies having pricing power. No one is saying that that should be taken away from them. They’ve always had that. Or with companies using data to set prices. Data based on what their competitors are doing is great for a competitive market.
Maintaining a high degree of information asymmetry with individuals? Hiding from them that you’re even testing out different prices with them?
If companies need to do this so badly — and that’s what we’re going to be hearing from more in Canada, because this is what the opposition is starting to organize with in the U.S., and I’m being very surveillant on that. It’s not hard. I just go around the internet — then they should be going out of their way to brag about when and how they’re doing this to us, because they’re hiding it in privacy policies.
And I think there is a sense of appropriate shame. But also there’s a novelty factor where it’s been really interesting to sort of design these apps and test out these prices and earn more money and learn more at the margins. That’s where we’re at.
Cara Stern: What would transparency look like? Would they be saying, your price has been adjusted based on this sort of thing? I don’t know how it would actually play out.
Vass Bednar: That’s one way. A couple of places in the U.S. have this, where they just have this baseline of disclosure. So Uber does show the price for this ride was set by an algorithm using your data. The Washington Post also has this notification now. Again, special offers trying to test what will bring you in. It’s calibrated in a particular way. PlayStation was recently caught running a pricing experiment where they were advertising different prices for different games.
It’s an interesting question for an Economics 101 class. Should we charge people who play video games more often more money because they’re likely to pay more because they play more and they value it more? Maybe, from an extractive “let’s optimize prices” situation.
But in terms of a what’s appropriate in the marketplace and how do people budget? How do you equitably access these goods that is the exact same thing. I think it becomes harder to rationalize charging someone more.
What fascinates me about all this is in this cost of living crisis, opposing personalized algorithmic pricing demands a kind of cross-class solidarity that we probably haven’t seen in a while, or ever, because we have to unite against companies extracting value from all of us by stepping over the line.
The question is, where is that line? How are we going to set it together?
Cara Stern: I guess the algorithm that they use right now, PlayStation will say, “If you’re someone who wants to play on day one, you’re spending this amount. If you want to play it close to release day, that’s the cost of it.” If you’re willing to wait a year, wait even six months, a year or two years, it’ll get cheaper over time.
That’s an algorithm that they’re using. I guess we’re okay with that sort of thing. Price goes down over time as more people get to play the game. But the difference that you’re describing is that, well, the day one price is different for someone who plays a lot versus someone who doesn’t.
Vass Bednar: Yeah. We observe gas prices changing, but you and I can see that. We can track that through the Gas Buddy app. If you and I are both at the gas station, we’re paying the same amount for that. I’m putting aside that we might be participating in loyalty programs.
You and I are both speaking in Ontario. Hydro prices. They fluctuate based on time of day. You and I experience that universally. If we can wait to do our laundry at night, that price, there’s some price dynamism there, but we all experience it equally and we can all predict it.
That’s not what people are opposing with the kind of personalized pricing calibrations. It’s that loss of price anchor. It is, eroding, kind of taking away all the consumer surplus and also creating really intense information asymmetry. You can’t discipline a market that you don’t know.
So I do agree with Premier Ford, who a few weeks ago now said he wants the market to be free, but he said he wouldn’t oppose personalized algorithmic pricing.
Cara Stern: He thinks this is part of a free market.
Vass Bednar: He thinks it’s part of a free market. And I would say that’s an area where we differ, where to my mind, to have a market be more free and fair, we need to have those principles of transparency. We need better privacy laws. You can’t discipline a market that you don’t know.
Cara Stern: You said that the federal government can use the Competition Bureau. Provinces have been talking about this. As you said, Manitoba is the first one in Canada to say something publicly that I’m aware of. What can be done at the different levels? Is there is there one level that really needs to take ownership? Is that federal, or are there things the provincial governments or municipal governments can do?
Vass Bednar: Provincial governments could do something with the Residential Tenancies Acts if they wanted to sort of say, we don’t want commercial landlords to use pricing algorithms or we want them to disclose, etc. That is one potential tool. I used to think that Manitoba was the only province thinking about it, but I’ll correct myself and say that the province of Quebec had updated their privacy law fairly recently.
Their provincial privacy policy basically prohibits you from discriminating against someone based on their personal characteristics. That is a way to say you cannot personalize pricing. But to my knowledge, that law has not been tested, so a case has not come forward. We could better resource these institutions. Maybe a private action case could come forward. And though I love competition law and competition policy, the Competition Bureau is not my first pick because it’s more of a watchdog policing function of the marketplace, whereas privacy law and consumer protection feels more like an upstream, market shaping, carving conversation.
Of course downstream, that might be an interesting lever to get at this. I’d love to see a private action case come forward to the Competition Bureau testing this. I think that would be really interesting. Haven’t seen this yet. I’m not directly planning one, but on my mood board and Vass’s side schemes, yeah, that would be cool.
Frances Lankin, before she became a senator, one of the incredible things she was doing was running the United Way. And she had a hot dog stand, maybe a food truck for the day. She set it up in front of Queen’s Park, and she was protesting the gender wage gap and gender pink tax, also a place we tolerate differential pricing in ways that are weird.
She sold hot dogs to boys for a dollar and hot dogs to girls for $0.75. I thought that was great. I’d love to have a food truck for a day. I just want to look at them and be like, “Oh, you wear glasses? Your hot dog is $1.50. Oh, you bought a hot dog before? Your hot dog is $2.” And people would be upset and annoyed, and it would seem random and discriminatory because it is random and discriminatory. And I would also calibrate the prices in fairly fine ways. So again, it’s not the monetary value. It’s the principle that I think we need to be reacting to.
Sure, if you’re old, I could charge you a little bit less. I’m interested in confronting people with what it feels to be seen by a commercial actor in a way that is invasive.
Cara Stern: You and I both have young kids, and the place where I was willing to spend the most money is when you’re up at 4 a.m. in the first few months and you don’t know what to do. You’re googling something and you’re like, “I’ll buy anything that’ll get them to go to sleep.”
I end up with so many ridiculous things. And I just think, “Oh my God. If they have surveillance pricing allowed and they know that you have a young baby at home, you are screwed.” All of your life savings are going into yoga balls that you can bounce on or whatever else that they say will help with it.
It’s horrible. Hopefully we see some politicians pay attention to this and listen to you on how they can fix it, because it would really be nice to see some protection. We need more competition, but as you said, in a fair way would be nice. If it was transparent, that’d be lovely.
Vass Bednar: Yeah, more competition, but what kind and how? Hopefully we can be as detailed and attentive as the software programs and proprietary algorithms are when it comes to us as we approach this policy problem.
Cara Stern: Thanks so much for joining us. I really appreciate having you on.
Vass Bednar: I’m a huge fan of the show. Long time listener, second time caller.
Cara Stern: The third time, I think.
Vass Bednar: Third time caller?
Cara Stern: Yeah, because you were on our pilot. You were here talking about your book, The Big Fix. I recommend people go and watch that. I love that book. It’s one of those books where I was reading it and I was like “Yes, I’m so angry. I can’t believe this is all happening and no one cares about this.” Or some people care, but not enough people care about this. Get angry. It’s a great book and it’s the perfect length. You get into it and here’s a solution. I loved it.
Vass Bednar: Snack size. Exactly. Let’s go. Let’s make Canada better.
Cara Stern: Thanks so much for watching and listening. Our producer is Meredith Martin and our editor is Sean Foreman. If you have any questions about what calms a crying baby at 4 a.m., you can send an email to [email protected], and we’ll see you next time.
Additional Reading/Listening that Helped Inform the Episode:
Everything Costs More Because the Algorithm Says So | The Walrus
Canadians Are Skeptical of Algorithmic Pricing - Abacus Data
AI-Driven Pricing May Be the Next Shock to Canadian Grocery Shoppers
Algorithms are raising prices for everything. This must stop - The Globe and Mail
Avi Lewis is smart to shed light on surveillance pricing | Canada’s National Observer: Climate News
fascinating and funny