Research Note

E095 Transcript Corrections Research Note

The raw transcript remains immutable. These corrections govern the public package.

Aug 4, 20262 min readBy Dalton Anderson

Source conversation

THE LOYALTY PENALTY: WHY YOUR FAITHFUL SHOPPING HABITS ARE COSTING YOU MORE

Keywords Instacart, Consumer Reports, dynamic pricing, AI, surveillance pricing, Eversight, customer surplus, price discrimination, grocery staples, algorithm ethics SummaryIn this episode of the Venture Step Podcast, Dalton Anderson dives into a recent Consumer Reports investigation regarding Instacart’s use of AI-enabled dynamic pricing. Dalton explores how the technology, powered by a company called Eversight, aims to reduce "customer surplus" by charging users different prices for the exact same goods based on their willingness to pay. The discussion highlights the ethical concerns of applying airline-style pricing logic to essential items like milk and eggs, the manipulation of discount perception, and the potential for discriminatory profiling against vulnerable populations. Takeaways While society generally accepts variable pricing for airline seats due to supply and demand, applying this logic to essential goods like bread and eggs raises significant ethical questions. A Consumer Reports investigation involving 437 volunteers found that 74% of items selected had different prices for different people in the same geographic areas. The study revealed massive markups, such as a 23% increase for Wheat Thins in Seattle and a 20% price swing for eggs in DC. This pricing strategy is driven by "Eversight," which uses AI to determine the maximum price a consumer will pay, effectively eliminating the savings a customer might otherwise enjoy . Additionally, the illusion of deals is created when algorithms artificially inflate the list price for certain users to make a standard discount appear larger. Brand loyalty can also act as a disadvantage; if an algorithm knows you will always buy a specific brand, it may charge you more for it. Ultimately, there are fears this technology could evolve into discriminatory profiling, similar to failed predictive policing models, targeting users based on personal data and location.

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E095 Transcript Corrections Research Note

Purpose

The raw transcript remains immutable. These corrections govern the public package.

Transcript framing	Publication correction
Instacart dynamically charges each customer according to willingness to pay	The investigation observed different prices. Instacart described the assignments as randomized A/B tests and denied using personal or behavioral data to set item prices.
All 437 volunteers supplied the analyzed result	Consumer Reports recruited 437 volunteers and says roughly 200 error-free screenshot sets supported the central analysis.
Seventy-four percent of items had different prices	Use the investigation's wording, about three-quarters of checked items, unless the exact denominator is reproduced from its data.
A family of four paid about $1,200 more	The $1,200 figure was an annualized estimate based on basket variation and spending assumptions, not an observed annual bill for every family.
Older, disabled, and food-desert shoppers were targeted	Consumer Reports described Instacart as important to those groups. Its participant sample did not establish that those traits caused assignment or higher prices.
Phone type, location, occupation, and shopping behavior set the observed prices	The investigation did not prove those inputs were used. Instacart denied personal, demographic, and user-level behavioral inputs for item prices.
Eversight independently powered the practice	Instacart acquired 100 percent of Eversight in August 2022 and integrated its pricing and promotion technology.
Target had no relationship, so the platform account was impossible to reconcile	Target said it had no formal business relationship. Instacart said it used public Target prices as a base plus an amount for its own costs and tested approaches on that storefront.
The FTC's later $60 million matter validated the pricing allegations	The FTC case concerned delivery advertising, refunds, satisfaction guarantees, free trials, and Instacart+ enrollment. It was separate from item-price testing.

Current-state correction

The transcript speaks in the present tense about item-price tests. Instacart ended item-level price testing on December 22, 2025. Public pages must describe the investigation in the past tense and state that promotions, discounts, loyalty offers, store-level variation, and retailer markups remain separate parts of the current system.

Editorial implication

The strongest public version of E095 is not a softened transcript. It is a transparent record of the question, the evidence that answered part of it, the counterparty explanation, and the later policy change.

Sources

Follow the evidence.

ag.ny.gov: attorney general james demands answers instacart about algorithmic pricingag.ny.gov
itl.nist.gov: pri332itl.nist.gov
instacart.com: promotionsinstacart.com
ftc.gov: ftc surveillance pricing study indicates wide range personal data used set individualized consumer pricesftc.gov
consumer.ftc.gov: online shoppingconsumer.ftc.gov
company.instacart.com: instacartpricingcompany.instacart.com
gov.uk: tackling the loyalty penaltygov.uk
company.instacart.com: instacart makes it easier for customers to save on groceries with acquisition of eversightcompany.instacart.com
instacart.com: 1586544648instacart.com
usa.gov: online purchase complaintsusa.gov
company.instacart.com: ending item price tests on instacartcompany.instacart.com
company.instacart.com: the truth about pricing tests on instacartcompany.instacart.com
itl.nist.gov: pri11itl.nist.gov
fca.org.uk: fca confirms measures protect customers loyalty penalty home motor insurance marketsfca.org.uk
consumerreports.org: instacart ai pricing experiment inflating grocery bills a1142182490consumerreports.org
investors.instacart.com: 9e9aff2c 95db 4f75 bdf1 0f4025e1468cinvestors.instacart.com