Instacart’s Double Squeeze: Surge Pricing on Workers and Customers
Surge pricing used to be simple. When demand spiked, Uber charged riders more and paid drivers more. Everyone saw
Surge pricing used to be simple. When demand spiked, Uber charged riders more and paid drivers more. Everyone saw the multiplier. A 2x surge meant double the price and double the earnings. It was transparent, predictable, and applied the same way to everyone looking at their phone at the same time.
Companies now use invisible algorithms to charge different customers different prices for identical products while simultaneously paying different workers different wages for identical jobs. The same technology that maximizes what you pay also minimizes what workers earn. Both sides get squeezed, and neither side knows it’s happening.
Instacart Pays Workers Whatever They’ll Accept
A December 2025 investigation revealed that Instacart doesn’t just manipulate customer prices. The company uses algorithms to pay workers different amounts for nearly identical deliveries. Researchers studying Instacart’s Washington DC workforce found workers doing the same job getting paid different rates based on what the algorithm predicted they’d accept.
Instacart workers earn an average of $7.66 per hour after accounting for expenses like mileage and payroll taxes. Half of all Instacart jobs pay below the federal minimum wage of $7.25 per hour once you subtract those costs. Some workers reported seeing their overall wages drop 30 to 40% as Instacart refined its algorithmic pay system.
The algorithm operates as a black box. Workers have no idea how their pay gets calculated. They see a delivery offer with a payment amount, and they either accept or reject it. If they reject it, the same job often reappears minutes later with slightly higher pay. Instacart is essentially auctioning each delivery to find the lowest bidder willing to do the work.
This creates a race to the bottom. Workers who need money immediately accept lower-paying jobs because they can’t afford to wait for better offers. The algorithm learns from this behavior and continues offering lower pay to workers it identifies as desperate or price-insensitive. Workers who reject low offers eventually see better pay, but only after losing income while they wait.
The company also uses customer tips to subsidize its own costs. When customers tip generously, Instacart reduces the base pay it offers workers, essentially pocketing the difference. This means tips don’t actually increase worker earnings as much as customers think. The algorithm adjusts base pay downward to capture most of the tip’s value for Instacart rather than passing it through to workers.
Customers Pay Whatever the Algorithm Thinks They Can
While Instacart experiments with paying workers less, it simultaneously runs experiments to charge customers more. The same December 2025 investigation tested 437 shoppers and found that 100% of participants were placed in pricing experiments without their knowledge or consent. Every single person using Instacart was being charged algorithmically determined prices based on their personal data and behavior.
The price variations were substantial. Identical items from the same store had up to five different prices depending on which customer was shopping. Some products varied by just 7 cents. Others differed by $2.56 for the exact same item. Overall, prices varied by up to 23% between customers buying identical products. A basket of 20 items cost some shoppers $114 while others paid nearly $124 for the exact same products.
Instacart tracks your purchase history, browsing behavior, location, time of day, and dozens of other data points to calculate the maximum price you’ll accept before abandoning your cart.
Consumer Reports estimated this kind of surge pricing could cost families $1,200 per year compared to paying consistent prices. About 72% of Instacart users said they don’t want different pricing for different customers, but Instacart implements it anyway because it increases profits.
The company acquired Eversight, an AI pricing software company, in 2022 specifically to build this capability. Internal communications revealed a program called “Smart Rounding” that uses machine learning to adjust prices up or down based on what will maximize profit. The company describes it as improving “price perception,” which is corporate speak for charging whatever customers won’t notice or complain about.
Squeezing Both Sides Simultaneously
Traditional surge pricing at least maintained a relationship between what customers paid and what workers earned. When Uber charged 2x during a surge, drivers also earned more. The increased price compensated workers for accepting rides during high-demand periods.
Instacart broke that connection. The company charges customers variable prices based on willingness to pay while paying workers variable wages based on desperation to work. There’s no correlation between the two. A customer paying premium prices for fast delivery might have their order fulfilled by a worker earning below minimum wage because the algorithm determined that worker would accept low pay.
This creates maximum value extraction from both sides of the transaction. Customers pay more than necessary. Workers earn less than they should. The difference flows directly to the company as profit. It’s surge pricing evolved into a tool for squeezing every available dollar from everyone involved in each transaction.
The technology enables this by operating invisibly. Unlike Uber’s 2x surge notifications, algorithmic pricing happens behind the scenes. Customers see a price and assume everyone else sees the same price. Workers see a payment offer and assume it’s based on distance, time, and complexity rather than algorithmic predictions about their financial desperation. Neither side can compare notes easily because the prices and payments are individualized and constantly changing.
Digital Price Tags Make It Worse
The shift from paper price tags to electronic shelf labels accelerates this trend. Schnuck Markets, a grocery chain with over 100 stores, began rolling out Instacart-connected digital price tags in July 2024. These electronic displays can update prices in real time based on algorithmic decisions rather than requiring someone to physically change labels.
This infrastructure allows stores to implement surge pricing directly in physical locations, not just online. Prices could increase during peak shopping hours when stores know customers are less likely to leave. Prices could vary between the front of the store and the back, testing whether customers who walk further are less price-sensitive. Prices could change based on how many people are in the store, local weather, nearby events, or any other factor the algorithm identifies as relevant.
Patents filed by Instacart describe technology for calculating “shopper and product headroom,” which means determining how much more money each individual could spend overall and on specific products. The system analyzes your complete purchase history to identify products where you’re price-insensitive and products where you compare prices carefully, then adjusts accordingly.
This turns every shopping trip into a personalized extraction operation. The store knows which products you need versus which ones you want. It knows which categories you research and which ones you buy impulsively. It adjusts prices for each item to maximize what you’ll pay without triggering enough frustration to make you leave.
Regulation Can’t Keep Up
Governments are starting to respond but remain years behind the technology. New York passed a law in November 2025 requiring retailers using algorithmic pricing to display notices stating “THIS PRICE WAS SET BY AN ALGORITHM USING YOUR PERSONAL DATA.” California, Colorado, and Pennsylvania are considering bans on surveillance pricing. The FTC has opened investigations into multiple companies.
These regulations face immediate challenges. How do you enforce disclosure requirements on apps that can change their code faster than regulators can review it? How do you prove a company is using algorithmic pricing when the pricing decisions happen inside proprietary black-box systems? How do you define illegal price discrimination when companies claim they’re just running dynamic pricing experiments?
Instacart’s responses to questions about its pricing practices demonstrate how companies dodge accountability. When initially asked about variable pricing, Instacart said retailers control all prices. When investigators contacted those retailers, they said they don’t set Instacart’s prices. When confronted with the contradiction, Instacart admitted it does control pricing but claimed it’s just running tests. When evidence of systematic algorithmic pricing emerged, the company deleted references to pricing optimization from its website and claimed those features were never implemented.
This pattern of deny, deflect, and delete makes regulation nearly impossible. By the time investigators gather evidence of specific practices, companies have changed their systems, updated their websites, and prepared new explanations. The technology moves faster than legal processes, and companies exploit that gap aggressively.
Permanent, Invisible Extraction
More companies are adopting these systems because they work. Uber went from burning billions of dollars to becoming profitable after implementing algorithmic pricing for both riders and drivers. Studies show average rider prices per mile increased steadily after Uber switched from visible surge multipliers to algorithmic pricing, while driver earnings remained flat or declined.
That success made algorithmic pricing inevitable across industries. Delivery apps, ride-sharing platforms, grocery services, and increasingly physical retailers are all implementing similar systems. The economic incentive is too strong to ignore. Companies that don’t adopt these technologies compete against companies that do, forcing them to either match the exploitation or lose market share.
You never get a deal. You never pay less than the algorithm determined you could pay. Workers never earn more than the minimum the algorithm predicted they’d accept. Every purchase and every job becomes a perfectly optimized extraction of value from people with less information and less power than the companies running the algorithms.
Surge pricing was transparent, temporary, and at least theoretically connected to supply and demand. Instacart’s version is permanent, invisible, and designed to extract maximum value from everyone involved in each transaction.
SEO Title: How Surge Pricing Evolved to Exploit Workers and Customers Simultaneously
Meta Description: Apps like Instacart use algorithms to pay workers less and charge customers more for identical work and products. Here’s how the double squeeze works.
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