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🏷️ actual retail price
🏪 unknowable marketplaces
Former meteorologist Terry Kniess famously memorised the Price is Right’s set of rotating prices and items, guessing exactly correctly with two perfect showcase bids. At the time, the immediate assumption from the show’s producers was that he cheated. As it turns out, it wasn’t a case of price rigging but rather the result of a conscientious person studying a predictable set of prices that could be learned.
Terry’s mind-blowing feat occurred in 2008, which is also the last year the Competition Act was updated, and the same year that the App Store launched. Uber, WhatsApp, Venmo, Slack, Square, and others followed in 2009. The characteristics and conditions of the marketplace have been fundamentally reshaped over the last 14 years, but competition law in Canada has been resistant to change - until now.
Budget 2022 announced the Government of Canada’s intention to introduce legislative amendments to the Competition Act that can help adapt the law to today’s digital reality.
What is today's “digital reality”?
A recent New York Times Magazine article captured the increasingly unknowability of prices well, observing that “costs are so fluid that household goods fluctuate almost like Bitcoin.”
Other expressions of data-driven price dynamism are informed by a range of variables harvested from the internet that tailor an advertised price just for you. This is distinct from something like a “senior” or “student” discount that is equitably distributed to consumers based on a clearly-stated and provable characteristic (an example of third-degree price discrimination).
Researchers have been exploring the dynamics of discrimination that come along with super-personalized prices. Such inequities may occur between an individual and a price on an app, as recently documented through research conducted by the Mozilla Foundation and Consumers International looking at Tinder. It may occur between a potential newspaper subscriber and a dynamic paywall that determines when to pitch you on converting and at what particular price, as with the Globe and Mail’s Sophi.io. While a price calibrated to an individual’s presumed sensitivity is difficult to discern online, price shifting is increasingly observable in brick-and-mortar contexts, too; like when two Starbucks that are 800m away from each other charge a different price for the same drink.
All of these examples are dependent on a price even being shown at all. Some catalogues no longer have a corresponding price list. While it’s typical to run an advertisement for a product or service that doesn’t include the price in a magazine or on television, the Amazon catalogue has not had prices since 2018. Even in an increasingly digital society, direct marketing is still the best value for a dollar. It’s interesting to see how a digital giant engages in ‘retro’ marketing activities.
Withholding information on a baseline price has implications for competition in terms of price variability, opacity, or no prices at all. While it is not necessarily an anti-competitive activity, it presents new challenges for consumers.
Regulators have recently come out against drip pricing; which is arguably the most familiar way that a product’s actual retail price is obscured in an initial headline and additional fees are incrementally added (think of the difference between an Airbnb’s nightly rate before the service and cleaning fees). The ability of hyper-dynamic (or “personalised”) pricing by algorithm feels unfair when it is not sufficiently acknowledged to the consumer. In our Vivic report, Ana Qarri, Robin Shaban and I suggested that unacknowledged personalised pricing could be a form of deceptive marketing.
These well-calibrated algorithms may be ‘efficient’ for the firms employing them, but they are manipulative for the shoppers and workers whose environments they dictate. This is not unlike the algorithmic management of gig platform workers that causes the remuneration of various jobs to oscillate based on a range of factors.
Any semblance of price stability is eroding offline, too.
Grocery stores are experimenting with digital pricing that can revise shelf prices with just a few taps of a keyboard. While this technological adoption is ostensibly being introduced to save labour costs as it is time intensive to change the prices on the shelf, it’s also a reminder that prices change often.
One tool for setting price standards in an otherwise opaque market is modelled by car dealerships. They typically have a “Manufacturer’s Suggested Retail Price” or MSRP which is a suggested price that is different from the “sticker” price. This could be a useful model for firms that do not set the shelf price for their items.
The pricing fluctuations that have come to characterise online shopping are fundamentally different from the second-degree pricing that influences something like aeroplane seats -- information: past bookings, remaining capacity, average demand for certain routes and/or the probability of selling more seats later.
Gaming the algorithm - while thrilling! - may not be an optimal solution to these exploitative pricing strategies. Nonetheless, a range of sub-optimal techniques for individuals to circumvent algorithmic pricing circulate online, like: browsing in incognito mode, disabling third-party cookies, or shopping and then making purchases on different browsers. While these tactics make it more possible for people to comparison shop, none of the interventions address the problem at its root.
Amazon’s price variability has motivated technological ‘solutions’ to price changes, allowing people to track pricing and make a better-informed decision about when to check out their cart. “CamelCamelCamel” is an Amazon price watcher and “Keepa” is a Chrome plugin that shows you Amazon price fluctuations.
Table 1 - “Keepa” fluctuations of LEGO Flower Bouquet (3 months)
Perhaps consumers could have the option alongside better disclosure of pricing volatility to either set a ‘range’ of what they are willing to pay against an anchor price or whether they want to gamble.
Instead of having each shopper spend more time attempting to price compare online, we may have some legislative tools at our disposal.
The US has specific antitrust legislation on price discrimination, like the Robinson-Patman Act. Recently, a bipartisan group of 43 lawmakers wrote to the Federal Trade Commission urging them to revive price-discrimination probes under the Act. Enforcing against price discrimination is all the more relevant in light of two recent reports showing that companies are making billions by pushing prices higher.
In Canada, two pieces of Canadian legislation could have the answer to addressing price differentiation as discrimination: federally, the Consumer Packaging and Labelling Act, and provincially, the Discriminatory Business Practices Act.
The Consumer Packaging and Labelling Act was intended to ensure that people know what they are buying based on the “can.” The legislation currently dictates that a firm must tell a consumer - what a product is, how much it weighs, and where it was made. Basically, relevant information so consumers can effectively make a choice in the marketplace. Is price an aspect of labelling here, whereby as an element of advertising the price indirectly promotes the sale of a product? Is a catalogue with no price akin to an item with no discernible “label”?
The purpose of the Discriminatory Business Practices Act is to “prevent discrimination in Ontario on the ground of race, creed, colour, nationality, ancestry, place of origin, sex or geographical location of persons employed in or engaging in business.” Perhaps this legislation could be updated to not only deal with dealings between businesses, but also when servicing consumers in the digital age. I wonder how algorithmic discrimination might be interpreted by this piece of legislation from the 90s.
💶 Our digital reality is one where the price is not quite “right,” but mostly just “right” - calibrated to the consumer’s context and the market’s sensitivity at that moment.
Given this period of inflation, Canadians are increasingly price sensitive. Shoppers deserve clear posted prices - online and off - that don’t constantly deviate without any negotiation.
At present, there are few ways to know whether and when first-degree price discrimination is occurring when you shop online. A previous indicator came from the now defunct “Sold by Amazon” program; if a merchant was part of the program, the firm had to agree that Amazon’s pricing algorithm would set the price for a product by scanning the web for the lowest price elsewhere. It was ultimately found that this was a violation of US antitrust law (in Washington state).
The growing disconnect between the goal(s) of consumer protection and the narrow focus of competition law points to the need for a more integrated, transversal approach to policy making that can satisfyingly respond to significant shifts in retail marketplaces. A consumer-centric approach that deeply considers what people need to know about new and novel pricing tactics may be best implemented by provincial consumer protection authorities.
Canada has notably decoupled competition law considerations (federal) from consumer protection concerns (provincial). This is distinct from other federalist approaches taken in the US or EU. As dynamic pricing continues to calibrate calculations that determine the advertised cost of a product, consumers may be paying very different ‘prices’ for that artificial separation.
Terry can’t memorise the game anymore, because there’s no real way to know the rules. The problem is ultimately one of information asymmetry. This new kind of pricing power also has implications for the stability and utility of the Consumer Price Index (CPI). What use is a basket of goods that will always be priced differently for Canadian consumers regardless of the product? 🛒
Reconciling with the growing murkiness of the marketplace demands a new kind of bespoke policy approach, calibrated to the issue(s) solving for and with a range of perspectives ‘at the table.’
Our individual digital habits and demographics have been modifying prices for years in ways that are ultimately invisible to us. We hardly even shop in the same store or marketplace anymore because we are each browsing in our own hall of algorithmic mirrors. 🪞
Put simply - it is no longer reasonable to assume that you are paying the same price as someone else when you shop online. Policy people need to consider whether the erosion of fixed pricing and the growth of automated pricing needs fixing; potentially through new transparency and disclosure requirements.