Us Fast-food Store Closures 2026

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US Fast-Food Store Closures 2026

The State of US Fast-Food Store Closures in 2026: QSR Footprint Trends

Which fast-food segments are shrinking, where closures concentrate, and how the US QSR footprint is reshaping in 2026 — tracked from public store-location data over time.

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US fast food is not contracting evenly. Behind a roughly flat-looking headline, some QSR segments are closing units faster than they open them, and the losses cluster in specific regions and store formats.

This report turns public store-location data, tracked over time across 40+ US QSR brands, into a clear picture of who is closing, where, and why the national number hides the real story. It is written for the teams that plan real-estate, supply, and franchise strategy around the QSR footprint.

Key findings at a glance
Three patterns stand out across the footprint data. (Figures below are illustrative previews — the full report breaks them down by brand, segment and metro.)

-2.4% — Net change in tracked QSR units across the year
40+ — US QSR brands tracked ...
... by store location
3 — Regions carrying most of the net closures

Illustrative figures — replace with your final dataset before publishing

Key finding 1: which segments are contracting
Closures are concentrated in older formats. Legacy sit-down concepts and dine-in pizza show the highest closure rates, while drive-thru-led chicken and coffee/snack formats are the most resilient.

The pattern tracks a broader shift toward smaller, drive-thru and digital-first footprints — chains are closing aging dine-in boxes and, in many cases, reopening leaner formats elsewhere, which a simple count of closures alone would miss.

Key finding 2: where closures concentrate
Closures are far from uniform geographically. The sample below shows net unit change by region (illustrative).

Midwest — Closures: High | Openings: Low | Net Change: -3.8%

Northeast — Closures: High | Openings: Moderate | Net Change: -2.9%

West — Closures: Moderate | Openings: Moderate | Net Change: -1.1%

South — Closures: Moderate | Openings: High | Net Change: +0.6%

The South is the one region adding units on net, while the Midwest and Northeast carry most of the contraction — exactly the kind of regional split that a national average erases.

Key finding 3: openings still offset much of the loss
Closures grab headlines, but openings matter just as much. Several brands are net-closing dine-in units while net-opening smaller drive-thru or delivery-only formats, so the footprint is reshaping more than it is simply shrinking. Reading closures without openings overstates the decline; reading both reveals where demand is migrating.

What the underlying data looks like
The report is built from store-location records tracked over time, like the one below — the structure buyers receive in a sample.
{
"brand": "Example QSR",
"segment": "pizza",
"store_id": "EQ-44120",
"city": "Chicago", "state": "IL",
"lat": 41.8781, "lng": -87.6298,
"status": "closed",
"first_seen": "2024-03-10",
"last_seen": "2026-05-22",
"format": "dine_in",
"captured_at": "2026-06-29T09:00:00Z"
}

Aggregated to a brand-and-region view, the same data rolls up into a flat file analysts can model on:
brand,segment,region,closures,openings,net_pct
Example QSR,pizza,Midwest,84,31,-4.1
Example Burgers,burgers,Northeast,52,40,-2.2
Example Chicken,chicken,South,18,46,+3.0
Example Coffee,coffee,West,22,29,+1.4

You will get the most from it if you are in:
Commercial real-estate & site-selection teams
Retail & QSR analysts
Franchise investors & operators
Foodservice suppliers & distributors
Lenders & equity researchers
Market & competitive intelligence teams

What is inside the full report
Net unit change by QSR segment
Closures vs openings by region and metro
Format shift — dine-in vs drive-thru/delivery
Brand-level footprint movers
Complete methodology, sample size and sources

Methodology & data
The findings are based on publicly available store-location data tracked across US QSR brands over time in 2026, then aggregated by brand, segment and region. Closures and openings are inferred from changes in published locations. No personal data is involved. The full report details the brands, regions and how each metric is calculated.

A note on the figures
The numbers and charts shown on this page are illustrative previews of the kind of analysis in the report. They are based on publicly available, non-personal web data in aggregate and do not represent any single named company. The full report contains the complete dataset, methodology and sources.

Read More : https://www.webdatascraping.us/us-fast-food-store-closures-2026.php
Originally Submitted at : https://www.webdatascraping.us

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