If you’re near Rochester, New York, the price for a carton of Target’s Good & Gather eggs is listed as $1.99 on its website. If you’re in Manhattan’s upscale Tribeca neighborhood, that price changes to $2.29. It’s unclear why the prices differ, but a new notice on Target’s website offers a potential hint: “This price was set by an algorithm using your personal data.”
A recently enacted New York State law requires businesses that algorithmically set prices using customers’ personal data to disclose that. According to the law, personal data includes any data that can be “linked or reasonably linked, directly or indirectly, with a specific consumer or device.” The law doesn’t require businesses to explicitly state what information about a person or device is being used or how each piece of information affects the final price a customer sees. The law includes a carve-out for the use of location data strictly to calculate cab or rideshare fares based on mileage and trip duration but not for other purposes.
The law also requires that the disclosure is “clear and conspicuous.” Target’s disclosure is not the easiest to find–a customer would have to know to click the “i” icon next to the price of an item, then scroll to the bottom of the pop-up. In the past, the courts have held that it’s not always reasonable to assume that a customer will click on “more information” links when it’s not required.
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In 2015, ProPublica found that the Princeton Review’s online SAT tutoring packages sometimes varied by thousands of dollars based on the zip code provided by customers. Similar to Staples [referenced earlier in the full article], the Princeton Review told ProPublica that its pricing was based on the “costs of running our business and the competitive attributes of the given market.”
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Beyond eggs and toilet paper, it’s not clear what else retailers are pricing algorithmically (or how). The disclosures could potentially shed some light on the variety of goods customers pay different prices for, even if it doesn’t necessarily help consumers understand why. The New York law might be followed by similar legislation in other states—at least one other state, Pennsylvania, introduced a similar bill earlier this year—and a federal bill addressing surveillance pricing was introduced in July. There’s broader regulatory interest in the ways that AI and algorithms can influence consumer pricing: According to JD Supra, over 50 bills related to algorithmic pricing, including those related to algorithmic price-fixing and the use of certain characteristics in dynamic pricing algorithms, have been introduced at the state level across the United States.
It does seem kind of obvious that prices would vary by location - Rochester, for example, is over 300 miles away from Tribeca, which is in downtown NYC. So like, obviously the cost of living would be pretty radically different there. Same thing with Tribeca and Queens at 10 miles apart and only a 30 cent difference.
What I’d be interested to know is what other factors are influencing this stuff beyond location. I remember reading stories in the past about how Target would raise the price if they detected your location was in the parking lot because they knew you were unlikely to go to another store once you were already there. Uber has also been accused of raising the price if your battery is low, since you won’t really have the luxury of shopping around or waiting for prices to drop. I wonder if these stores are using more than location and obvious cost-of-living differences to justify those prices, and to further “personalize” them.