According to Reuters, Instacart is currently getting the regulatory equivalent of a throat-clearing from the FTC, which has sent the grocery delivery platform a civil investigative demand regarding its AI-powered pricing tool, Eversight. Put another way, the agency wants to know why some people are paying substantially more for their organic granola than others.
The issue came to light after a study revealed that shoppers are seeing fairly different prices for identical groceries from the same stores — up to 23% higher prices in some cases. Instacart says these price tests were randomized, not tied to an algorithm that targets customers based on their browsing history. But when people are already anxious about affording eggs, that distinction probably doesn’t mean much.
Dynamic pricing isn’t new or necessarily nefarious. Harvard Business School will tell you it’s how digital platforms stay competitive. Airlines use it, hotels use it, Uber famously uses it. Companies argue that it helps balance supply and demand, maximizes profitability, and creates win-win scenarios.
But there’s a difference between paying surge pricing for a ride home from the bar and paying extra for groceries (food isn’t optional). So while the investigation doesn’t prove wrongdoing, it’s hardly shocking that the FTC — which has investigated data-driven pricing strategies by other companies — is reportedly asking questions. In an economy where everyone’s feeling squeezed, AI-driven price testing of kitchen essentials was bound to attract attention.
For its part, Instacart says the market misunderstands this particular initiative. “Much of what’s been reported has mischaracterized how pricing works on Instacart,” a spokesperson for the company tells TechCrunch. “First, our retail partners control their pricing strategies, and we work with them to align their online and in-store pricing wherever possible. Second, these tests are not dynamic pricing nor surveillance pricing – prices on Instacart do not change in real time nor are they based on supply or demand, and we never use personal, demographic, or user-level behavioral data to set item prices. These tests are a form of randomized A/B testing, similar to the way retailers have long run pricing tests between different stores.”