Delivery Wars

"DoorDash won the suburbs."
But did they?

Nick Chan Nick Chan · DataLane ↗

The DoorDash narrative is that they won the suburbs. But no one ever proved it, even as it has become cited in strategy courses as a core case study. So we pressure-tested it against our foundational data.

We looked at 48 archetypal suburbs across 4 archetypes, 12 markets each, 18,827 restaurants. It's true. DoorDash won the suburbs, but it wasn't a clean sweep.

There's so much more to learn from where they won, how they won, and how competitors like UberEats are tweaking their GTM motion to compete. Let's dive in.

One note — we are evaluating this from a "Who signed more restaurants" view. That view flattens nuance around which restaurants are driving the most transaction volume per platform.

DoorDash beats Uber Eats
38 / 48
Affluent Edge-City
9/12
Sun Belt
11/12
Legacy Inner-Ring
9/12
Working-Class & Diverse
9/12
The 48 suburbs we examined
Bubble = restaurant count · Color = leading platform
How to read this map
Dot color
DD leads UE leads
Each dot is one of the 48 suburbs. The color tells you which platform has higher restaurant coverage there.
Dot size = restaurants in market
~200 ~500 ~1,200
The sample runs from 84 restaurants (Cleveland Heights) to 1,171 (Plano).
Hover
Hover any dot for the city, sample size, and DD% vs UE% in that market.
Light-grey states are the 21 in our sample (the others have zero suburbs in scope).
DoorDashDoorDash leads
Uber EatsUber Eats leads
Platform coverage by market · grouped by archetype
% of restaurants integrating each platform · sorted DoorDash wins first within each stratum
How to read these bars
Left · the market
One row per suburb, grouped by archetype. The sub-line shows the metro and restaurant count (n).
Middle · the two bars
DD 47.6%
UE 43.2%
Top blue bar is the share of restaurants in that suburb with a DoorDash integration. Bottom dark-grey bar is the same for Uber Eats. Scale runs 0%–60%.
Right · DD lead
DD% minus UE%. Positive means DD leads; greyed-out negative means UE leads.
The two bars don't sum to 100% because of the following edge cases: a single restaurant often integrates with both platforms, and some restaurants are not on either platform.
Bar order per market DoorDashDoorDash Uber EatsUber Eats
Doordash won 77% of the suburbs we sampled. · the claim holds.

DoorDash leads Uber Eats in 37 of 48 suburbs (77%). The win is consistent across all four archetypes: 11 of 12 Sun Belt markets, 9 of 12 affluent edge-city, 9 of 12 legacy inner-ring, and 9 of 12 working-class & diverse. Uber Eats' remaining strongholds cluster in the Miami metro (Hialeah, Pembroke Pines, Coral Gables) and the NYC / Cleveland inner ring (Yonkers, New Rochelle, Parma) — and Round Rock is a dead heat. At the suburban coverage level, the claim survives. One caveat to read forward into Section 2: this is restaurant coverage (which platforms a restaurant lists), not order volume. The 77% headline is bigger than the underlying motion that produces it.

Section 2 — one level deeper

DoorDash won the suburbs — mega-chains.

We have the luxury of drilling our data down to the restaurant level. The trend we see is that DoorDash has been much more successful in signing AND onboarding national chains to their platform. Across almost every single suburb, DoorDash leads on franchised mega-chains with 1,000+ locations. Drop one more level — to specific brands — and the mechanism becomes obvious: DoorDash holds the contract on Taco Bell (+62pt), Papa John's (+53pt), Pizza Hut (+36pt). Uber Eats holds Panda Express (−32pt). The chain-size pattern holds in all 4 archetypes from Section 1. Whoever is better at selling to national franchised locations wins the market.

DD lead · mega-chain only
+6.0pts
Among restaurants whose parent has 1,000+ locations. The one chain-size bucket that explains the whole suburban headline.
DD lead · everywhere else
+1.8pts
Average across singles, small, mid, and large chains. Statistically a tie.
DD's biggest brand-level win
+62.3pts
Taco Bell: DD 78.4% vs UE 16.2%. The mega-chain effect, in one chain.
UE's biggest brand-level win
-32.3pts
Panda Express: DD 6.2% vs UE 38.5%. Uber's biggest confirmed brand-level win.
A · The lead comes from one bucket — mega-chains
Restaurant-level coverage by parent account size · all 48 markets
How to read this chart
Left · the row
One row per chain-size bucket (Single → Mega chain at 1,000+ locations). The n = X shows the restaurant count in that bucket across all 48 suburbs.
Middle · the dots
Filled blue dot is the share of restaurants in the bucket with DoorDash. Filled grey dot is the same for Uber Eats. Both plotted on the 30%–60% scale above.
Right · the gap
DD% minus UE%, in percentage points. Bluelane when DD leads by 2 points or more; greyed when under 2 — that's a tie.
Coverage is independent, not market share. A restaurant on both platforms counts in both bars, so DD% and UE% don't sum to 100% — they're separate measures of how many restaurants list each platform.
Parent account size
30%
37.5%
45%
52.5%
60%
DD lead
The gap is concentrated, not distributed.

If DoorDash were winning the suburbs at the restaurant level, you'd see a DD lead in every chain-size bucket. You don't.

Across 15,344 restaurants in singles, small, mid, and large chains, the two platforms are within ±2.5 points. That's a tie.

The entire +6.0-point lead lives inside one bucket — mega-chains (1,000+ locations) — where DD is on 60.2% of restaurants versus UE's 54.2%.

What lives in the mega-chain bucket: McDonald's · Subway · Starbucks · Wendy's · Chipotle · Wingstop · Papa John's · Burger King · Taco Bell · Jersey Mike's · Chick-fil-A · Pizza Hut.
B · Strength by cuisine exists, but brand-level contracts are the real story
Rolled-up cuisine buckets + brand-level coverage · 48 markets · n ≥ 30 per brand
1. Rolled-up cuisine
Cuisine bucket
← UE leads · 0 · DD leads →
DD lead

We collapse labeling variants — Pizza (all) = Pizza Restaurant + Pizza Delivery + Pizza Takeaway; Chicken (all) = Chicken + Chicken Wings; Mexican (all) = Mexican + Tex Mex + Taco.

2. Brand-level coverage
National chain
← UE leads · 0 · DD leads →
DD lead

Each row is a national chain in our 48-market sample (n ≥ 30). DD lead = DD coverage minus UE coverage. Brand-level skews run an order of magnitude larger than cuisine-level skews. What looks like "DD wins fast food" is really "DD won Taco Bell." Same goes the other way.

Three brands opt out entirely
In-N-Out (n=22 · DD 0% · UE 0%), and Olive Garden (n=29 · DD 0% · UE 3.4%) run their own delivery and don't integrate with the major third parties at scale. We've pulled them out of the chart so the contract-pattern reads cleanly.
C · Robustness check — the mega-chain signal holds in every suburb archetype
Chain size × stratum · DD lead in points · pattern is real, not driven by one stratum
How to read this heatmap
Rows × columns
Rows are chain-size buckets (Single → Mega chain at 1,000+ locations). Columns are the 4 archetypes from Section 1: Affluent edge-city, Sun Belt growth, Legacy inner-ring, Working-class & diverse. 20 cells in total.
Cell content
Each cell shows the DD lead in percentage points for that chain bucket inside that archetype, plus the cell's sample size. Color encodes magnitude and direction:
UE ≥5pt UE 2–5 Tied (±2) D 2–5 DD ≥5pt
Right · All 48
The total column on the right rolls the row up across all four archetypes — the same numbers as Section A's dumbbell.
Mega-chain (bottom row) is the only row that's blue across all four columns. The chain buckets above it flip color by archetype — blue or tied in S1/S2/S3, grey or tied in S4 (working-class & diverse). The contract pattern is real; the rest is a coin flip.
Chain size
Affluentedge-city · 12 mkts
Sun Beltgrowth · 12 mkts
Legacyinner-ring · 12 mkts
Workingclass & diverse · 12 mkts
All 48
UE +5pt or more UE +2 to +5 Tied (±2) DD +2 to +5 DD +5pt or more
Not a sample-size artifact.

If the mega-chain DD lead came from one archetype — say, affluent suburbs — we couldn't generalize it. So we split chain size by archetype: 20 cells, 18,827 restaurants.

The result is in the heatmap to the left. Mega-chain is the only row where DoorDash leads in all four archetypes (S1 +7.1, S2 +7.5, S3 +5.8, S4 +3.0). It's also the only row that stays blue end-to-end.

Below mega, the picture flips by archetype. Uber Eats still wins small chains inside working-class & diverse suburbs — Hialeah, Pembroke Pines, Chula Vista — and mid and large chains there are a dead heat. Run the same cut on cuisine and the pattern holds: Pizza's DD lean and Chinese's UE lean show up in every archetype with enough sample.

D · Validation — brand-level findings match public partnership announcements
DataLane's restaurant-level data direction and magnitude align with dated, named enterprise BD deals
DoorDash-locked chains
Largest data skews tied to named DD partnerships
Taco Bell
Exact match
Data: DD 78.4% vs UE 16.2% (+62.3)
Nationwide partnership announced Oct 2020 across 5,500+ stores (~75% of US), after Taco Bell ended its prior exclusive Grubhub deal (Yum Brands, 2018). Taco Bell newsroom · PR Newswire · Restaurant Business · Oct 2020
Papa John's
Exact match
Data: DD 72.3% vs UE 19.3% (+53.0)
National DD partnership covering 1,400+ restaurants; supplements Papa John's in-house drivers in rural and exurban areas. Papa John's IR (PZZA) · Restaurant Dive · Restaurant Business · QSR Magazine
Pizza Hut
Exact match
Data: DD 48.7% vs UE 13.0% (+35.7)
Pizza Hut + DoorDash deal confirmed; Pizza Hut laid off 1,200 in-house drivers when shifting to DD's commission model. Per Diem · DoorDash newsroom · SEC filings
Wingstop
Explicit exclusive
Data: DD 78.7% vs UE 62.7% (+16.0)
Wingstop CEO: "DoorDash gets the volume it wants as the exclusive delivery partner." Partnership since 2018, multi-year renewal in 2025. 70% of Wingstop sales now digital. Wingstop IR · DoorDash newsroom · Franchise Times · Per Diem
Uber Eats–leaning chains
Data direction matches legacy + ongoing UE deals
McDonald's
Historic exclusive
Data: DD 78.2% vs UE 78.9% (-0.7)
McDonald's + Uber Eats was exclusive 2017–2019 across ~64% of US stores; DD added Jul 2019. Six years on, coverage has fully converged — exactly what you'd expect when a historic exclusive unwinds into a multi-platform strategy. McDonald's corporate · CNBC · Restaurant Dive · PYMNTS
Panda Express
Direction confirmed
Data: DD 6.2% vs UE 38.5% (-32.3)
Deep Uber Eats API integration (via NovaDine — Menu & Order APIs). No public "exclusive" announcement, but the operational depth is unusual. Hospitality Technology · Uber Eats brand page · Coca-Cola "And a Coke" campaign
Chick-fil-A
Multi-platform reality
Data: DD 77.8% vs UE 83.8% (-6.1)
Chick-fil-A officially works with DD, UE, and Grubhub. The Chick-fil-A app itself is powered by DoorDash, so app orders flow through DD but get logged differently. The UE coverage lead reflects on-platform listings. Chick-fil-A delivery page · Chick-fil-A customer support
Self-delivery / opt-out chains
Zero coverage rows reflect corporate strategy
In-N-Out
Exact match
Data: DD 0% · UE 0%
Official no-delivery policy. In-N-Out sued DoorDash for trademark infringement over unauthorized delivery. CEO has publicly rejected delivery + East Coast expansion. Fox News · NRN · Tasting Table
Olive Garden
Match
Data: DD 0% · UE 3.4%
Darden Restaurants runs in-house "Olive Garden To Go." Minimal third-party participation across the Darden portfolio. Darden corporate · Olive Garden site
Reading: every major finding in our brand chart traces to a dated, public partnership announcement.
Verdict · three things to take away.
1 · Winning and onboarding national franchisees is a core competency
DoorDash's suburban lead is the residue of specific enterprise deals — Taco Bell, Papa John's, Pizza Hut, Wingstop. Uber Eats has its own list — Panda Express, Dairy Queen, Jack in the Box, Chick-fil-A. Those deals deserve a dedicated enterprise / franchise team. They should never be worked by a junior rep.
2 · Some chains are unwinnable
In-N-Out and Olive Garden largely run their own delivery. It's a reminder that some brands or restaurants can be a poor fit and should be removed from territories and GTM plans.
3 · Below the chain layer, it's a coin flip. This is not a won fight for anyone.
Across 15,344 independent and small-to-large-chain restaurants, DoorDash and Uber Eats are within 2.5 points of each other in these categories. There is no clear winner, and both teams need to continue finding new "edges".
— Section 3 —
Section 3 — looking at Uber's territory the same way we looked at DoorDash's

DoorDash won most suburbs.
How did Uber win a few?

DoorDash won 37 of 48 suburbs in our sample. Uber Eats won the other 11. Section 2 explained DD's national lead as a mega-chain contract effect — but that doesn't explain how Uber still won a few suburbs.

So we ran the same restaurant-level cuts on those 11 markets. Where they won, UberEats managed to execute specific edges better in markets. DoorDash wins mega chains and franchises in every suburb, Uber never flipped that trend. But in the markets they won, we see that Uber managed to win large-review-count restaurants, specific cuisines, and regional 2–10 location count chains. Execution still matters. You can still slay the giant with great focus and intense execution.

UE's lead, 1,000+ review restaurants (UE-winning suburbs)
+7.1pts
Uber Eats out-covers DoorDash by 7.1 points on the most established restaurants in their 11 winning suburbs (n = 982). The advantage grows with review count.
DD's lead, <50 review restaurants (DD-winning suburbs)
+5.9pts
DoorDash's biggest restaurant-level lead is at the long tail — restaurants with under 50 reviews (n = 3,349). The advantage shrinks as restaurants get more established.
Median reviews, exclusives (UE-winning suburbs)
359 · vs 191
UE-exclusive restaurants in UE-winning suburbs carry an 88% higher median review count than DD-exclusive ones (359 vs 191).
UE's lead, small chains (2–10 locs)
+8.2pts
In the 11 UE-winning suburbs, UE out-covers DD by 8.2 points on regional small chains — the single largest restaurant-level gap in the dataset. Small chains require account-level relationships, not corporate BD.
A · In their strongholds — Uber does a better job signing high-review count restaurants
UE−DD coverage delta · 5 review-count buckets · in each suburb pool
How to read this chart
X-axis · review buckets
Restaurants sorted into 5 buckets by Google review count: <50, 50–199, 200–499, 500–999, 1,000+. Left-to-right runs from the long tail to established mainstays.
Y-axis · UE−DD gap
For each bucket, we plot UE coverage minus DD coverage. Positive means UE leads; negative means DD leads. Two lines — one for the 11 UE-winning suburbs, one for the 37 DD-winning suburbs.
The shape is the signal
UE's lead in their territory grows with review count — a relationship sale into known places. DD's lead in their territory shrinks with review count — a volume motion through the long tail.
Review count is a proxy for restaurant maturity and salience, not a perfect measure. 1,000+ reviews usually means 5+ years old and locally known; under 50 reviews usually means new, niche, low-traffic — or already closed.
In Uber's territory, their lead grows with review count.
In DoorDash's territory, theirs shrinks.

In the 11 UE-winning suburbs, the UE−DD gap goes from −1.5 points among low-review restaurants (<50 reviews) to +7.1 points at the 1,000+ tier. Uber's win is built on the established places people actually go.

In the 37 DD-winning suburbs, the picture inverts. DD's lead is biggest at the long tail — +5.9 points on under-50-review restaurants — and narrows to +3.1 points by the 1,000+ tier.

These are two different sales motions hiding inside one coverage metric. UE looks like a relationship sale into the popular, well-known places. DD looks like a volume motion that signs up everything in the territory, including restaurants that may not even be actively operating.

Review count proxies for: customer familiarity, operational tenure, neighborhood salience. Restaurants with 1,000+ reviews are typically 5+ years old, locally known, actively serving. Under 50 reviews usually means new, niche, low-traffic — or already closed.
B · The regional chains with 2–10 locations are the most important accounts to win over
Each pool's coverage by parent-account chain bucket · UE−DD inside the pool
How to read this chart
Left · the row
One row per chain-size bucket (Single → Mega chain at 1,000+ locations). The n = X shows the restaurant count in that bucket inside this pool of suburbs.
Middle · the dots
Filled blue dot is the share of restaurants in the bucket with DoorDash. Filled grey dot is the same for Uber Eats. Both plotted on the 30%–60% scale at the top.
Right · the gap
Absolute lead in percentage points — UE% minus DD% in the left panel, DD% minus UE% in the right panel. The "X LEADS" tag names the platform ahead in that bucket.
Coverage is independent, not market share. DD% and UE% don't sum to 100% — they're separate measures of how many restaurants list each platform.
UE-winning suburbs11 markets · n=5,023 restaurants
Parent account size
30%
37.5%
45%
52.5%
60%
UE lead
DD-winning suburbs37 markets · n=13,804 restaurants
Parent account size
30%
37.5%
45%
52.5%
60%
DD lead

Below mega, the two panels mirror each other. In Uber's territory, UE wins singles, small, and mid chains — with the biggest spread at small chains (2–10 locations), +8.2 points — and large chains are a dead heat. In DoorDash's territory, the same pattern runs in reverse. Mega-chain stays locked for DoorDash in both pools — corporate delivery contracts don't bend with local sales motion. That's the Section 2 finding showing up again from a different angle.

C · You can win by signing one location, then expanding
Important motion — sign and roll out exclusive delivery deals with regional chains
How to read these brand lists
Reading a row
Take Pho Que Huong on the left. 5 operational locations of Pho Que Huong appear in our 11 UE-winning suburbs. 3 of those 5 are on Uber Eats exclusively. 0 are on DoorDash exclusively.
Filter: brand must have 4+ operational locations in the sample (no one-offs; permanently or temporarily closed locations are excluded from every count) and exclusive presence on one platform. The two count columns (UE-only / DD-only) show the proof of that exclusivity directly — no math required. Interesting: just because you sign one location in a chain doesn't mean the rest of the locations will adopt. Chalk some of this up to locations in non-core, non-deliverable markets.
UE-exclusive small/mid chains
Within the 11 UE-winning suburbs · regional ethnic operators
DD-exclusive small/mid chains
Within the 37 DD-winning suburbs · national mid-chains
D · Strategic cuisines — UE's Latin American edge
Cuisine-level skew · Miami metro vs control regions · the next axis of the delivery war

Latin American restaurants over-index toward Uber Eats in important regions, regardless of whether DoorDash dominates that region overall. In the Miami metro, where Latin American cuisine is dominant, the effect compounds into a UE stronghold. You can win markets with a specialized strategic cuisines sales motion.

Florida · 23 cities tested · leader by city
DoorDash leads
Uber Eats leads
150 → 4,000 restaurants
Florida's delivery map isn't one state — it's five regions.

Miami metro is the country's densest Latin American restaurant scene. Uber Eats wins 8 of 9 cities we tested there, by margins from −2.3pt to −14.9pt (Aventura).

The rest of Florida shows DoorDash's familiar strength: SW Florida is a clean DD sweep (Naples, Cape Coral, Fort Myers, Sarasota — all DD). Central and N Florida are mixed-to-tied.

UE wins · per region tested
Miami metro8 / 9UE
Tampa metro2 / 4tied
Orlando metro1 / 3tied
N Florida0 / 3tied
SW Florida0 / 4DD
1. Miami metro · UE lead by Latin American sub-cuisine (n = 5,030 restaurants across 9 cities)
Sub-cuisine
← Non-Latin baseline (UE +4.4) UE leads more →
UE lead

Dashed line is the non-Latin baseline (UE leads by 4.4 points across all 4,181 non-Latin restaurants in the same 9 cities). Every Latin American sub-cuisine leans toward Uber Eats — all ten carry a positive UE lead. Argentine restaurants are over 2.5× more on UE than DD (51% vs 19%); Cuban is +20.9pt.

2. The effect is structural, not Miami-only
Region
Sample (n)
UE lead · Latin
Pull vs non-Latin
Miami metro9 cities · UE-leaning baseline
849
+11.4 pts
+7.1more UE pull
SW Florida4 cities · DD-leaning baseline
389
+0.3 pts
+4.2more UE pull
TX suburbs4 cities · DD-leaning baseline
413
+0.7 pts
+2.1more UE pull

In every region — including DoorDash-dominant SW Florida and Texas — Latin American restaurants pull +2.1 to +7.1 points toward Uber Eats relative to the local baseline. Miami amplifies the effect (high Latin American restaurant density × already-UE-leaning baseline × stronger within-cuisine pull), but the structural cuisine effect is consistent everywhere we tested.

There are no accidents in GTM. How did Uber win a strategic cuisine?

One plausible mechanism: specialized BD teams. Spanish-speaking reps with cultural fluency working Cuban, Venezuelan, Argentine, Peruvian operators. We have seen an uptick in players in restaurant tech like Toast, DoorDash, and Uber hiring bi-lingual reps in key markets to execute on both outbound, inbound, and partnerships roles.

Sales is based on trust. Speaking the same language in a call builds trust and likely drastically improves conversion rates. We wrote more about the uptick in bi-lingual rep hiring here.

If you're building a sales team into local businesses, the implication is direct: Find markets where specific vertical concentrations exist, then build the specialized team needed to execute.

— Section 4 —
Section 4 — short-term GTM execution

How do you keep winning the delivery wars?
Sign new restaurant openings faster.

We reviewed every restaurant opening in our dataset detected in 2026. Then checked whether DoorDash or UberEats was present. DoorDash is maintaining their lead partly by signing new business openings significantly faster than Uber.

New restaurants on DoorDash
34.4%
All 2026 openings · n = 18,533. +10.7 points ahead of Uber Eats.
New restaurants on Uber Eats
23.7%
Same cohort. DD is on 1.45× as many new openings — in every single month of 2026.
Detection rate by opening month · DD vs UE
Every restaurant whose first Google review landed in 2026 · national · May–June still being scraped
Opening cohort
0%
12.5%
25%
37.5%
50%
DD lead
DoorDash reaches new restaurants first.

Across all 18,533 restaurants that opened in 2026, DoorDash is detected on 34.4% vs Uber Eats' 23.7% — DD signs the newest cohort roughly 1.45× faster.

Raw detection falls toward the present — the newest openings are still being discovered and re-scraped — but the ratio never moves: DD : UE holds at ~1.45× in January, February, March, and April alike. Every month a new restaurant is live on DoorDash and not Uber Eats is a month of GPV Uber never books — and a month DoorDash spends becoming the operator's default, preferred platform.

Caveat · scrape lag. Discovering a new restaurant and re-scraping its vendor presence takes weeks, so the newest months under-state detection for both platforms — May and June are still filling in and are excluded from the chart. The lag-proof signal is the ratio: DD reaches new openings ~1.45× faster in every fully-scraped month.
Verdict · DoorDash won the suburbs.

They have a sustained, detectable lead in a representative sample of suburbs. Win the mega-chains, win regional chains, and beat Uber to new openings.

But the delivery wars aren't over. Uber has proven that they can win specific markets, find edges on the margins (strategic cuisines), and sign their own mega-chain franchise contracts. Both teams need to keep stacking edges to maintain their lead.