Restaurant menu prices on DoorDash rose 3.1% in the year to September, but what diners actually ordered rose 2.4%, according to DoorDash’s State of Local Commerce 2026 report, published on 10 November. The gap is the company’s gauge of trading down: when the second figure runs below the first, the report says, diners are “shifting toward cheaper items”.
The monthly series on the report’s data site shows the ordered basket rising just 0.8% year over year in August 2026, the lowest reading in a series that starts in January 2024, while the fixed menu index rose 3.1%. By our arithmetic, that 2.3-point gap was the widest since July 2024.
Business Pill · Year-over-Year
A short explainer on year-over-year growth and the question it always raises: compared with what? It teaches the general idea only and does not discuss DoorDash’s indices.
The key insight: As we read it, DoorDash is showing two inflation rates for the same restaurants: menus rose 3.1% in the year to September, but the basket diners chose rose 2.4%, and in August only 0.8%, because people moved to cheaper items, which is how the report explains the gap.
DoorDash runs its Restaurant Price Index two ways. The methodology says “The fixed price index uses fixed weights (for consistent inflation tracking), while the floating price index uses weights that depend on the number of items that are ordered (to reflect changing ordering patterns)”. The fixed index rose 3.1% in September, down from 3.5% a year earlier, the release says.
The report says the floating index ran above the fixed one for a stretch in 2025, when consumers were buying more expensive items. It says “this has flipped since May 2026”, calling it “a sign that people are trading down to offset higher prices within food or elsewhere”. In the site’s data, the floating index peaked at 5.6% in July 2025, when the fixed index stood at 3.4%.
DoorDash Restaurant Price Index, year-over-year change by month, January 2024 to September 2026: the fixed index (same menu items) against the floating index (weighted by what people ordered). Data: DoorDash State of Local Commerce 2026.
The Price of a Cheeseburger Meal
DoorDash’s Cheeseburger Index, a cheeseburger, a soda and fries, averaged $18.61 nationally in September, up 2.6% from $18.15. In the site’s component data, the cheeseburger rose to $10.92 from $10.60, fries to $3.96 from $3.85 and the soda to $3.73 from $3.69; by our arithmetic the burger supplied about 32 cents of the 46-cent rise.
By city the meal ranges from $12.75 in Laredo, Texas, and $12.95 in Austin to $24.54 in Chula Vista, California, and $27.88 in Anchorage, Alaska. Anchorage’s meal costs about 2.2 times Laredo’s, by our arithmetic, and 64 of the 100 cities sit below the national average, by our count.
DoorDash Cheeseburger Index (cheeseburger, soda and fries) for the 100 largest US cities, September 2026, one dot per city, against the $18.61 national average. Data: DoorDash State of Local Commerce 2026; the 2.2x multiple and the 64-city count are ours.
Where Menu Inflation Is Slowest
The fixed index rose least in Washington, D.C. (2.1%), Richmond, Virginia (2.2%) and Cincinnati (2.2%), and most in Honolulu (5.9%), Detroit (5.4%) and Milwaukee (4.5%). The report adds that “Heartland and Sun Belt cities tend to have faster wage growth and slower restaurant pricegrowth than the coasts”, with Austin’s wage growth running 5.1 percentage points ahead of its restaurant pricegrowth in 2025.
The Structural Read
As we read the series, the gap is not new: the ordered basket also ran below the fixed menu through 2024, crossed above it for most of the middle of 2025, and has run below it again in every month since May 2026, the reversal the report points to.
As we read the methodology, DoorDash’s own AI assistant is pitched at the same pressure: among the requests it cites for Ask DoorDash are “Reorder my usuals while helping save money” and “I can not decide on what to get, I have $26 and I am hungry”.
DoorDash, State of Local Commerce 2026 report
“When the floating price index runs below the fixed one, diners are shifting toward cheaper items.”
Three Implications
FOR RESTAURANTS The report shows menu prices up 3.1% while the basket people ordered rose 2.4%, the gap DoorDash reads as diners trading down.
FOR DINERS BY CITY A Cheeseburger Index meal costs $12.75 in Laredo and $27.88 in Anchorage, against a national average of $18.61.
FOR THE INFLATION READ The fixed index slowed to 3.1% from 3.5% a year earlier, the release says, with the smallest city rises in Washington, D.C., Richmond and Cincinnati.
The framework reads: “The agentic surface — the harness — is becoming where value pools in the entire AI stack.”
As we read it, the budget prompts DoorDash cites for Ask DoorDash put its own agentic surface inside the trade-down the price index records; our piece on DoorDash’s AI index covers where that assistant is used most. The framework predates the report and does not discuss DoorDash.
In the report, site and release we read, DoorDash does not publish the item weights or order counts behind either index, so the gap between them cannot be split into a price effect and a mix effect from outside. Trading down is DoorDash’s reading of that gap. The August low and the July 2024 comparison come from the site’s monthly data, not from the report’s text. We did not contact DoorDash.
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DoorDash’s fixed menu index rose 3.1% in the year to September while the basket diners actually ordered rose 2.4%, and in August the ordered basket rose just 0.8%, the lowest in the series; DoorDash reads the gap as diners trading down to cheaper items.
A note on sourcing. We read DoorDash’s State of Local Commerce 2026 report (PDF) in full, its newsroom release of 10 November and the report’s data site, including the monthly price-index and Cheeseburger Index files the site loads. The August low, the gap comparison, the component shares, the 2.2x multiple and the 64-city count are our arithmetic from those files. We did not contact DoorDash.
Gennaro Cuofano is a CRO and tech executive who has worked in AI since late 2015, starting with bringing NLP, natural-language generation, voice and chatbot products to the marketing industry. His background is in law and finance: he holds a Master's degree in Law and an International MBA with an emphasis on corporate finance (LUISS Business School and the University of San Diego, 2012), and worked as a financial analyst at a real-estate investment firm in San Diego and as an assistant controller. His work focuses on business model strategy, business engineering and, more broadly, structural analysis: how companies make money, read from their own filings. He created FourWeekMBA and leads research there and at The Business Engineer, his newsletter on AI and business strategy, with over 95,000 subscribers and more than 1,000 published analyses. His writing has also appeared on Entrepreneur (for example, How to Digitize a Family Business in Europe) and HackerNoon. Find him on LinkedIn and Substack. See how we source.
