I like to think of myself as a seasonal runner. As the name implies, I do not run year-round. I wait until the weather warms up a bit and I have more free time, which is usually when the spring semester ends. Then, I am running 2-3 times per week in the mornings. My runs are one of the few activities where I enjoy listening to audiobooks. Before this, I always found it hard to enjoy or stay engaged with audiobooks. But once I was running more regularly, that time became the perfect time for me to really focus on an audiobook and now I listen to a handful every year.

Because I don’t always listen to audiobooks, it doesn’t make sense for me to always subscribe to a service like Audible. Sure, I could buy books individually through Audible, but often it is cheaper for me to subscribe a few months at a time and get a backlog of books that I’ll chip away at while I run. On top of this, I am generally a frugal person. If there is a way to get audiobooks for cheaper, I will find it. Amazon seems to have some sense of this based on my use and whatever other data they have on me and every few months I will get an offer in my inbox to come back to Audible for a few months at a steeply discounted price, typically $1/month for three months.

When that email hits my inbox, I sign up and use my credit for a book I have been wanting and set a reminder on my phone to cancel right before the price goes back up to the higher normal tier. I get three books over the course of this discounted window and Amazon gets a little money out of me. After I cancel and eventually finish all my cheap audiobooks, Amazon inevitably sends me another one of these emails months later. Rinse and repeat.

Amazon isn’t alone in this sort of user-targeted discount behavior. Many online retailers will send you a discount code for a product you leave in your cart for a while. For instance, I recently was thinking about buying a new backpack and found one online that looked like it would work for me but the current price was a little higher than I wanted to spend at the moment. I had put it in my cart on their website and thought I would just come back later. About a week later, I received an email encouraging me to revisit my cart and take advantage of 10% off my purchase. That discount put the backpack at a price that was more appealing and so I bought it. Here too, I got the product I wanted and paid a little less, and the company still got some money out of me.

I am sure that many people have experienced similar things with online shopping whether with big companies like Amazon or others. Why do I bring this up? The pricing or discounting strategies that I just described sound like a good deal, but under Colorado’s recently passed individualized pricing bill (HB26-1210), they would be heavily restricted. After being introduced in February of this year, the bill went through multiple revisions before being passed in early May. As the passed version of the bill is written (full text of the bill can be found here), Amazon and other companies would not be allowed to use consumer data on me to offer discounts for something like an Audible subscription or other products. If the bill became law it would restrict a lot of individualized discounting (pricing) that occurs. That much is not in dispute as it is the stated purpose of the bill. The problems with it, as will be detailed below, are more about the broad reach it has and whether it will actually help consumers.

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What is in the bill?

Before I talk about any issues with the bill, let me go through a bit more about what the bill actually says because it is not as if the state legislators are simply trying to get rid of discounts. In November of last year, I had the opportunity to talk through some of these issues with one of the bill’s sponsors, Colorado State Senator Mike Weissman. We appeared together on a virtual panel hosted by MSU Denver’s College of Business for our MBA students. From that discussion, I gathered that Senator Weissman is worried about consumers unknowingly facing higher prices on a variety of goods and this bill is an attempt to address that problem. Many of the points I brought up in response will be made in this post now that the bill has passed.

From the perspective of Weissman and as stated by other proponents of the bill, its purpose is to curb companies’ ability to charge higher prices or set lower wages using algorithms. An earlier but related bill, HB25-1004, was aimed specifically at restricting landlords from setting rent using algorithms that many argued could allow for collusion among landlords (related to concern over RealPage). Governor Jared Polis vetoed this bill last year. This new bill is much broader in scope. Those in favor of this bill and others like it often frame the problem around examples such as customers facing higher prices for a flight to attend a funeral or ride-share companies like Uber and Lyft targeting individual drivers with unfairly low wages, but more broadly around large corporations using big data to squeeze consumers and workers. I am going to focus on the consumer prices portion of the bill. In my reading, the exceptions for individualized wage setting make the restrictions much narrower than the consumer prices side.

An “individualized” price is defined in the bill as:

“specific to or inferred about an individual or group, band, class, or tier of individuals with particular personal characteristics, online behaviors, or biometrics”

where personal characteristics are defined to broadly capture mutable and immutable qualities. The online behaviors part of the definition is itself defined broadly to include:

“an individual’s actions, habits, preferences, affiliations, associations, financial circumstances, or interests that are observable, measurable, or inferred through digital, online, or electronic observation or surveillance.”

Individualized prices cannot be determined using a “price or wage setting algorithm” if the algorithm is a substantial factor in that determination. What counts as a price or wage setting algorithm is also quite broad:

“Any technology, software, program, machine-based system, or computational process that: uses statistical modeling, data analytics, artificial intelligence, or other data processing techniques to analyze surveillance data…”

So if a company collects, purchases, or otherwise obtains data on its consumers and then analyzes that data with some software and offers different prices, it is engaging in a deceptive trade practice. But the bill makes some exceptions.

The bill carves out exceptions for financial decisions such as creditworthiness, mortgages and other loans, and insurance. Additional exceptions include publicly disclosed eligibility criteria such as volume purchases, joining a mailing list or loyalty program, and special pricing for groups such as teachers, members of the military, students, and senior citizens.

If the bill becomes law, violations of individualized pricing restrictions are considered deceptive trade practices under the Colorado Consumer Protection Act. The Act lets the attorney general and district attorneys bring actions and lets private parties sue and recover attorney fees, so the cost a company weighs is not just a possible fine but the prospect of having to defend the practice at all.

Issues with the bill

Despite the exceptions and the use of words such as “surveillance” (which seem intended to make the bill appear as if it targets only the most nefarious version of individualized pricing), the bill is so broad that it will likely discourage companies from offering individualized discounts (prices) for fear of facing costs if this becomes law.

Let’s go back to the Amazon example for a moment. How is Amazon offering me the lower price for the Audible subscription? I don’t know exactly (the bill sees this as a problem) but I do know they have data on my use of the service, my purchase history, how long I have stayed subscribed in the past, and probably how I’ve responded to the discount emails I have received in the past as well. That information is some input into whether I and other similar customers receive the discount email. This might be fully automated by internal software, or maybe it’s AI. Who knows? The discount does not fall into a regular promotion to all customers like a Prime Day discount nor is it a discount for me being a teacher. As far as I can tell, this sort of pricing falls into the sort of individualized pricing that would be banned. Even if not exactly, is it worth it for Amazon to keep trying this and risk penalties? Or, is it easier for Amazon to stop offering these pricing promotions to customers in Colorado? My guess is the latter.

You might be asking yourself, who cares that you can’t get your precious discounted Audible subscription? Surely, it is worth it that some minor discounts go away so that the completely unfair practice of charging people their max willingness to pay for everyday necessities can be stopped. I might agree with that if the law wasn’t so broad and if this problem of people being charged dramatically different prices for goods was as common as the bill and its proponents appear to assume. One of the sponsors of this bill argued that this is really a bill about tackling affordability. I’m skeptical taking away the ability to use individualized pricing will have much of an effect on affordability.

One reason for my skepticism is that there are already mechanisms to discourage companies from charging high and unpredictable prices. For one, people already hate the worst version of the type of pricing the bill is aimed at. Even a more minor version, such as Wendy’s proposed dynamic pricing plan in 2024 (which may not be restricted under the bill, though that is not entirely clear), was met with anger from consumers and quickly walked back. Similarly, Instacart was found to be experimenting with algorithmic pricing on grocery items with price differences across customers on a wide range of products. After a Consumer Reports article on the practice came out, and the obvious negative reaction from consumers, Instacart stopped the practice. It also is not even clear that Instacart was engaging in “surveillance” pricing or price discrimination as typically understood in economics.

Organized consumer backlash such as in the two examples above is not always easy to achieve but it need not be organized. Competitive pressures can achieve the same outcome. Suppose Instacart quietly began introducing algorithmic pricing again. I get charged $4 for a jar of pickles and my pickle-loving friend gets charged $7. This happens across products and stores. More people start paying higher prices for certain goods and don’t really understand why. Whether or not people understand why prices are higher, people make adjustments when prices change. And other companies can try to capture customers who are disillusioned with using Instacart. Maybe Walmart promises its Walmart+ customers that the prices you see for your delivery order are the same as in the store you’re ordering from (this is something they already actually do). People start making the switch and get their groceries delivered from Walmart rather than Instacart. How might Instacart respond? If they lose enough customers, they might do away with algorithmic pricing again, no organized consumer backlash needed.

My point is that we have seen pretty effective use of consumer backlash against companies engaging in the sort of practices this bill is aimed at restricting and the pressure of competition points in the same direction. My main issue with the bill is that it doesn’t just target Instacart using AI to charge you more for lemons than your neighbor. It is broad enough that it gets rid of things like selective discounts which are pervasive and often a benefit to consumers.

Related to this point, I think a major flaw in the thinking behind this bill is the assumption that consumer data and pricing algorithms are only ever used to raise prices for consumers. Raising prices is not always the most profitable thing for a company to do. Of course, if a company can get a higher price for its product it will try to do so. But only under the expectation that the increase in revenue from raising the price is not offset by the loss in revenue from losing customers no longer willing to purchase at the higher price. I am not denying that the “surveillance pricing” described here can mean higher prices for some consumers, but the assumption that this is a necessary feature of surveillance pricing is incorrect. Companies are also interested in capturing customers that would never purchase from them at the standard sticker price. Being able to figure out who those people are and offer them lower prices is a benefit to both the company and the consumer. This expands the market and new consumers benefit who were priced out before.

In addition to the misunderstanding that individualized pricing necessarily means higher prices for consumers, one of the sponsors of the bill, Representative Javier Mabrey, has emphasized that it is some of the biggest companies in the world behind much of the problem. I agree that bigger companies like Amazon are able to use individualized pricing at a much more sophisticated level than a small business. But if individualized prices are defined as any price that uses consumer data and the price is set using an algorithm which could be anything from using a spreadsheet on consumer data to look at trends to using something like ChatGPT to analyze customer data, there is no reason to think that many small businesses wouldn’t also find themselves in violation.

Many small businesses use services like Toast that help with consumer insights and offer help setting prices. Even if you sell something on Ebay here and there, the website has features that allow you to use their software in helping set prices and target customers who are viewing your product with different prices. Those are software programs that could be considered to be a substantial factor in setting price and now a locally owned retailer could face legal costs too. And if a small business might also be in violation, they will likely find it much harder to fight against complaints and legal costs made possible by this bill. Amazon has millions of other customers they can focus more on. Amazon or other large corporations are unlikely to take a major financial hit because of this bill, but small businesses might, depending on how strong enforcement is.

Two final issues I will raise are related to the uncertainty that the bill creates about what is and isn’t restricted.

First is the algorithm’s role in pricing. As the bill is written, it must be “a substantial factor in setting, offering, or determining a price.” What constitutes “substantial” here? According to the bill it “means more than a de minimis or incidental factor that informs the price…” What if a company uses an algorithm whose inputs are consumer data and spits out a range of prices but then a human reviews and chooses the final price that is offered? What if customers are randomly shown a range of prices as a company experiments? Is that restricted or not? Depending on how steep the penalties are, it might not be worth it for a company to try and test the limits of what is substantial.

Second, the exceptions to this bill include differential prices “justified by temporal differences, including fluctuations based on supply and demand.” This sounds like a reasonable exception. How else are companies supposed to determine demand for a product other than collecting consumer data and using analytical tools to land on the right price? The demand curve for a company’s product is not directly observable. Demand must be estimated and consumer data is a useful input. But what falls under the exception is not very clear.

Even something as simple as A/B testing prices is a way companies try to estimate demand and determine prices. That practice involves using what this bill defines as an algorithm to show different customers different prices as a way to find the profit-maximizing price. Is this going to be restricted too? Companies may also segment customers into different markets and charge prices accordingly. Is that differential pricing based on fluctuating demand, or restricted individualized pricing? When Uber uses surge pricing after a concert, presumably this is because demand increases in that location. But Uber must use location data from customers to determine who sees the surge price and who doesn’t. The bill’s exceptions to using location data do not include something like Uber using surge pricing in this way. But it may be fine if this is considered a fluctuation in demand. Again, I am not sure companies will take on the risk to find out and may just err on the side of caution.

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Conclusion

Overall, I think support for this bill comes from a misunderstanding of how differential pricing is used, the assumption that it necessarily (or at least typically) leads to consumer harm, and the fact that calling it surveillance pricing makes it sound scarier than it actually is.

I don’t know exactly where the line is to have a better version of this bill that does deal with at best annoying and at worst unjust pricing practices using consumer data. But this current version threatens the ability of companies to experiment with prices in ways that make more exchanges possible. I understand that companies do this to make more money and restricting this will mean they make less money. However, harming the profits of companies by taking this tool away does not imply consumers will be made better off.

If the goal really is to avoid only the truly unfair or deceptive uses of individualized pricing, I am not sure any version of this bill is necessary given the existing Colorado Consumer Protection Act. The Act already makes it a deceptive trade practice for any business to knowingly or recklessly engage in “any unfair, unconscionable, deceptive, deliberately misleading, false, or fraudulent act or practice” (see Section 6-1-105(1)(rrr)).

I would think that deceptively charging some customers unfairly higher prices based on factors they have no idea about or lowering some wages using similar practices falls under this provision. I am no legislator and I’m guessing there is good reason a bill was proposed to supplement the existing consumer protections. But if enforcing the existing law on a more case-by-case basis can avoid creating uncertainty, causing unintended limitations to pricing practices that help companies and consumers, and creating additional compliance costs, it should be done. Regardless of whether the goals can be achieved under existing law, Governor Polis should veto this bill as currently written.

Colorado’s Surveillance Pricing Bill Deserves…