The US Fast Casual Local Presence Index 2026

It is seven on a Thursday. Two people cannot decide where to eat. One of them opens a phone and types four words.

Places to eat near me. What happens in the next thirty seconds decides where forty dollars goes tonight — and, if it goes well, where it goes most Thursdays for the next year.

They will choose from three results on a map. And in nine of the ten brands we audited, if two of your restaurants appear in those results, there is nothing on the listing to tell a customer which is which.

So we read what they read.Fifty-seven restaurants across ten emerging US fast casual brands, seen exactly as a customer would see them. These brands carry more reviews per location than any category we have audited — an average of 1,032, with one location above 4,400. And nine of the ten publish their restaurants under the bare brand name with nothing to distinguish one from another.

10 brands are in this study. They are anonymised, and the letters are deliberately not in rank order — so if you work in this industry, there is a reasonable chance one of these scorecards is yours and you will not know which until you reach the end.

If you run marketing or brand

Read this as a list of things you can fix. You have already won the hard part — customers are leaving reviews at scale. What you have not done is make individual restaurants findable.

Most of what we found, you can fix yourself. Naming, hours, duplicates — a fortnight of attention and no budget. We tell you exactly what they are, free, and we would rather you just did it.
The part that does not stay fixed is review volume. Part Seven shows why: the same three bad reviews do twenty-five times more damage to a thin location than a rich one.
And every new location starts thin. Zero reviews beside siblings with hundreds, on a site you have just paid to open.

Full detail in Part Nine

If you run the company or lead expansion

Read this as a list of things to ask about. Every new opening starts at zero reviews beside siblings with thousands, and that ramp is a payback-period problem, not a marketing one.

This is externally assessable, with no cooperation required. Everything here was visible to any customer with a browser — which also makes it checkable before you buy something.
The repair cost is fixed and the exposure is not. Twenty-seven five-star reviews to recover from three bad ones, at any volume. Thin locations take the damage; everyone pays the same bill.
Nobody in the org chart owns it. It sits across marketing, operations and whoever opens new sites, which is why it appears on no dashboard.

Full detail in Part Nine

Who published this, and why you should factor that in

Amplispot sells digital presence management, including a review and listings product called ReviewSpot. We have an obvious commercial interest in a report concluding that local presence is mismanaged, and you should read it with that in mind.

What we have done to make it checkable anyway: the scoring formula and full deduction schedule are published, so you can recalculate any score yourself. Every figure came from public Google listings, so any claim can be independently verified. No brand was contacted before publication, paid for inclusion, or given advance sight of its score. ReviewSpot is not mentioned again in this document.

What follows

Thirty seconds on a ThursdayWhy the listing is the shortlist.
One brand does it properlyAnd it is not the one you would expect.
How we lookedOur method, our selection, and what it cannot see.
The findings that repeatNaming, hours drift, and internal variance.
A measuring stickFour components, 100 points, published in full.
The rankingAll 10 brands, scored.
What the ranking revealsWhere the real separation lives.
The scorecardsEvery brand, every defect.
What to do about itOne reading for marketing, another for the executive team.
Which brand are youWe will tell you privately.

Part One

Thirty seconds on a Thursday

You have solved reviews. You have not solved findability.

This is the first category we have audited where review volume is not the problem. These brands average 1,032 reviews per restaurant. For comparison, the senior living operators we studied average 38.

Which makes the naming failure stranger

Nine of the ten brands publish every restaurant under the bare brand name — no neighbourhood, no town, no identifier. In several cases that means two, three or four restaurants in one metropolitan area that a customer cannot tell apart, and that Google treats as near-duplicates competing for the same searches.

You have built the hardest asset in local marketing — tens of thousands of customers on record — and then made it difficult for a customer to work out which of your restaurants they are looking at.

Why it costs more here than elsewhere

Because the decision is fast, repeated, and proximity-driven. Somebody choosing a restaurant at seven on a Thursday is not researching a brand; they are choosing between three nearby options in under a minute. If the wrong location surfaces, or if two of yours surface and neither reads as the closer one, you lose the visit to whoever is third.

None of this is visible from inside. Nobody on your team searches for their own restaurant. That is the entire reason this report contains anything you did not already know.

If review volume is not the differentiator here, something else has to be. The answer turns out to be almost entirely structural.

Next, Part TwoOne brand does it properly

Part Two

One brand does it properly

One brand in ten names every restaurant by location.

Exactly one brand in this study publishes a location qualifier on every listing in its estate. It is also the smallest brand here by review volume — and it finishes seventh, because volume still dominates the index.

1,032

Average reviews per restaurant

The highest of any category we have audited. One location carries more than 4,400.

9 of 10

Publish the bare brand name

With no neighbourhood, town or identifier — including brands with four restaurants in a single metropolitan area.

16×

Review volume gap

Between the thinnest and richest estate, from 186 reviews per restaurant to 3,052.

What this tells you about the category

These are well-run brands with genuinely engaged customers. The failure is not effort or quality — it is that listing construction has never been anybody's job. In an emerging chain, the first ten restaurants get their profiles created by whoever opened them, and by restaurant thirty nobody has gone back to look.

Ten brands are the subject of this study. Before the numbers, here is how we selected them and what our method cannot see.

Next, Part ThreeHow we looked

Part Three

How we looked

Everything here was visible to anyone with a browser.

No brand gave us data. None was contacted before publication. Every finding was equally available to the brand itself.

Step 1 · Find the restaurants

We searched each brand by brand name across the state or region where it is most heavily concentrated, so that restaurants are compared against genuine local peers.

Step 2 · Record what the listing says

For every restaurant we captured the listing name, street address, telephone number, published opening hours, star rating, total review count, and the review text Google displays.

Step 3 · Compare restaurants against each other

Most defects only appear across a whole estate — a name that differs from every sibling, a shared contact route, a listing with no reviews at all. This is why internal teams miss them.

Step 4 · Score it mechanically

Components were calculated from the captured figures using the formulas and deduction schedule in Part Five. No judgement was applied afterwards.

What this method cannot see

We sampled one principal market per brand rather than a national census. Every brand here operates far more restaurants than shown. Per-restaurant figures are unaffected; totals are floors, not counts.
We sampled one region per brand rather than a national census. Several brands here operate considerably more restaurants than shown.
A single point in time. Ratings and listings drift, and some defects may already be fixed.
We did not measure owner response rate. The public data source does not expose owner replies as a retrievable field, so rather than estimate it, we left it out.
We hold no internal data from any brand.

Beyond naming, three findings repeat across the estates we read.

Next, Part FourThe findings that repeat

Part Four

The findings that repeat

Three defects, and one that only shows up at scale.

None of these are failures of food or service. They are artifacts of growing a chain faster than anyone reconciles the digital estate.

One: restaurants that cannot be told apart

The dominant finding. Nine of ten brands publish bare brand names across their estates. Four brands have three or more restaurants in one metropolitan area with nothing distinguishing them. Location-qualified names are one of the few remaining direct levers on local pack placement, and almost nobody in this category is using it.

Two: hours that contradict the rest of the network

One brand has a location publishing weekend closure and an early weekday close while five siblings open seven days. It may be correct — a business-district site with genuinely different trade — but nothing on the listing explains it, so to a customer it reads as a brand that is unreliably open.

Three: the internal gap that only appears at volume

One brand carries a thirteenfold difference in review count between its strongest and weakest restaurant in the same metropolitan area. Another carries nearly a full star between its best and worst location. At this category's volumes, an internal gap that wide is not noise — it is a location that is being experienced differently, and the brand average conceals it entirely.

The finding that matters most for a growing chain

Every new restaurant opens at zero reviews next to siblings carrying thousands. At this category's volumes that is not a minor disadvantage — it is a structural handicap lasting months, on a unit you have just spent heavily to build. The brands here that cluster most tightly are also the ones for whom each new opening is hardest to make findable.

That is one component of four. Here is the full measure, published so you can recalculate your own score.

Next, Part FiveA measuring stick

Part Five

A measuring stick

Four things, 100 points, no black box.

An index you cannot audit is a marketing device, not a measurement.

Component 01

Review density

Reviews per restaurant. Count is a ranking input in its own right, not just a confidence signal for humans. Log-scaled.

35 points

Component 02

Listing integrity

Whether the estate is correctly represented. Starts at full marks and loses points for each defect found.

35 points

Component 03

Rating

Volume-weighted average across the estate, scaled 3.0 to 4.9.

20 points

Component 04

Consistency

The gap between the best and worst restaurant. A wide spread usually means nobody is watching at restaurant level.

10 points

The deduction schedule, in full

Integrity begins at 35 points. Each defect costs the following:

Acquired or renamed restaurants not migrated to the group brand−10
Listing names inconsistent, or missing a location qualifier−8
Live listing with no reviews, or no published hours−8
Identical review text appearing across multiple listings−8
Corporate headquarters listed as a public destination−6
Shared national contact number across the estateobserved, not scored
Unusually wide rating variance between restaurantsreflected in consistency

Applied to 57 restaurants, that measure produces a table that looks very little like a ranking by size.

Next, Part SixThe ranking

Part Six

The ranking

All 10 brands, scored.

#	Brand	Restaurants	Reviews	Per restaurant	Rating	Defects	Score
1	Brand C	4	12,208	3,052	4.59	1	87
2	Brand G	6	11,228	1,871	4.55	1	83
3	Brand A	6	10,780	1,797	4.48	1	81
4	Brand H	6	6,936	1,156	4.57	2	81
5	Brand E	6	5,838	973	4.67	2	80
6	Brand J	6	4,592	765	4.56	1	78
7	Brand F	6	1,202	200	4.49	0	75
8	Brand I	5	2,753	551	4.36	2	70
9	Brand B	6	2,170	362	4.44	3	67
10	Brand D	6	1,119	186	4.25	2	56

Volume dominates, and structure decides the rest

Every brand in this study rates between 4.25 and 4.67 — a spread of four-tenths of a star across an entire category. Sentiment separates nobody. What moves this table is review volume and whether the estate is constructed so that individual restaurants can be found.

Two variables drive nearly all of that separation. Neither has much to do with quality of care.

Next, Part SevenWhat the ranking reveals

Part Seven

What the ranking reveals

A sixteenfold volume gap, and no sentiment gap at all.

Finding one: review volume

From 186 reviews per restaurant to 3052.

Brand C3,052

Brand G1,871

Brand A1,797

Brand H1,156

Brand E973

Brand J765

Brand I551

Brand B362

Brand F200

Brand D186

A sixteenfold gap between the thinnest and richest estate. Because volume feeds local ranking independently of score, the brands at the bottom of this chart are losing the thirty-second decision described in Part One to competitors they may well out-serve. Unlike a rating, volume is not a verdict on your food — it measures whether anybody is asking.

Why review volume is insurance, not marketing

Take a location sitting at 4.6 stars. In one difficult month it receives three one-star reviews — a staffing gap, a bad week, one genuinely poor experience shared by a family or a group. Nothing unusual.

What that costs depends entirely on how many reviews were already on file.

Reviews already on file	Rating after	Drop	Five-star reviews to recover
40	4.35	−0.25	27
100	4.50	−0.10	27
250	4.56	−0.04	27
500	4.58	−0.02	27
1,000	4.59	−0.01	27

Two things in that table matter more than anything else in this report.

The same three reviews do twenty-five times more damage at a thin location than a rich one. And the recovery cost — 27 five-star reviews — is identical at every volume. It does not get cheaper because you are large. It is fixed by arithmetic.

So a thin estate takes visible hits and pays the same repair bill. That is why volume behaves like insurance rather than marketing: you cannot prevent bad reviews, you can only dilute them, and dilution has to be running before the bad month, not after it. This category sits in the bottom rows — which is why your ratings are stable and why the opportunity here is structural rather than defensive. But every restaurant you open starts at the top row of this table, and stays there for months.

Finding two: ratings

From 4.25 to 4.67.

Brand E4.67

Brand C4.59

Brand H4.57

Brand J4.56

Brand G4.55

Brand F4.49

Brand A4.48

Brand B4.44

Brand I4.36

Brand D4.25

4.2★4.5★4.7★

Four-tenths of a star across ten brands. For a customer comparing two restaurants that difference does not register. This is a category where everyone has already solved the product and the advantage has to come from somewhere structural.

Below is every brand, with its component scores and each defect we found, described generically.

Next, Part EightThe scorecards

Part Eight

The scorecards

Brand by brand.

Brand C

87/100Strong

4restaurants

12,208reviews

3,052per restaurant

4.59★rating

1defects

Review density35/35

Listing integrity27/35

Rating16/20

Consistency10/10

NamingAll four restaurants publish under the bare brand name with no location qualifier.

Brand G

83/100Strong

6restaurants

11,228reviews

1,871per restaurant

4.55★rating

1defects

Review density32/35

Listing integrity27/35

Rating15/20

Consistency9/10

NamingAll six restaurants publish under the bare brand name with no location qualifier, including two in the same city.

Brand A

81/100Strong

6restaurants

10,780reviews

1,797per restaurant

4.48★rating

1defects

Review density32/35

Listing integrity27/35

Rating14/20

Consistency8/10

NamingAll six restaurants publish under the bare brand name with no location qualifier.

Brand H

81/100Strong

6restaurants

6,936reviews

1,156per restaurant

4.57★rating

2defects

Review density29/35

Listing integrity27/35

Rating15/20

Consistency9/10

NamingAll six restaurants publish under the bare brand name, with four in a single metropolitan area.
Thin volumeOne restaurant carries barely a tenth of the reviews of its sibling locations — a thirteenfold internal gap.

Brand E

80/100Strong

6restaurants

5,838reviews

973per restaurant

4.67★rating

2defects

Review density28/35

Listing integrity27/35

Rating17/20

Consistency8/10

NamingAll six shops publish under the bare brand name with no town qualifier, in a state with dense brand coverage.
VarianceHalf a star between best and worst, driven by one location where product consistency is the repeated theme.

Brand J

78/100Strong

6restaurants

4,592reviews

765per restaurant

4.56★rating

1defects

Review density27/35

Listing integrity27/35

Rating15/20

Consistency10/10

NamingAll six restaurants publish under the bare brand name, including three within a short drive of each other.

Brand F

75/100Fair

6restaurants

1,202reviews

200per restaurant

4.49★rating

0defects

Review density18/35

Listing integrity35/35

Rating14/20

Consistency8/10

CleanNo structural defects found in our sweep.

Brand I

70/100Fair

5restaurants

2,753reviews

551per restaurant

4.36★rating

2defects

Review density25/35

Listing integrity27/35

Rating11/20

Consistency7/10

NamingAll five restaurants publish under the bare brand name with no location qualifier.
VarianceMore than half a star between the best and worst restaurant.

Brand B

67/100Fair

6restaurants

2,170reviews

362per restaurant

4.44★rating

3defects

Review density22/35

Listing integrity27/35

Rating13/20

Consistency5/10

NamingAll six restaurants publish under the bare brand name with no town qualifier.
VarianceClose to a star between the best and worst restaurant.
Thin volumeOne restaurant carries barely two dozen reviews against a network median in the hundreds.

#10

Brand D

56/100Weak

6restaurants

1,119reviews

186per restaurant

4.25★rating

2defects

Review density18/35

Listing integrity22/35

Rating9/20

Consistency8/10

NamingAll six shops publish under the bare brand name with no town qualifier, including three in one metropolitan area.
Opening hoursOne shop publishes weekend closure and an early weekday close while five siblings open seven days, with nothing on the listing explaining the difference.

What you take from this depends entirely on which side of the table you sit on.

Next, Part NineWhat to do about it

Part Nine

What to do about it

Two audiences should read this differently.

For marketing and brand

You cannot prevent bad reviews. You can only dilute them. The table in Part Seven is the whole commercial argument: the same three complaints do twenty-five times more damage to a thin location, and the repair cost is identical either way. Dilution only works if it is already running when the bad month arrives.
Listings decay. They are not fixed once. Profiles get merged, the public suggests edits Google accepts, staff change hours, new locations arrive unclaimed. Everything in this report is a snapshot of an estate that drifts, which is why monitoring beats a one-off cleanup.
Every new location starts at zero and stays exposed for months. That is the top row of the Part Seven table, on a site you have just spent heavily to open — and it recurs with every opening rather than being solved once.
Your average conceals your worst location. Nobody sees location-level variance by watching a brand number, and the gaps we found in this study are wide enough to matter.
Your restaurants are competing with each other. Identical listing names in one metro means your own locations cannibalising the same searches. This is the single cheapest fix in this report and almost nobody in the category has made it.
You have already won the hard part. At a thousand reviews a location, your customers are engaged. The failure is structural, not relational — which means it is fixable without changing anything about how you operate.
Hours that contradict the network read as unreliability. A customer does not know your business-district site closes early for a good reason. They read it as a brand that might not be open.
Your brand average hides your worst location. One brand here has a thirteenfold internal review gap. At these volumes that is a real signal, and the average erases it.
These defects are invisible from inside. Nobody on your team searches for their own restaurant at seven on a Thursday.

For the executive team and expansion

This is a recurring exposure, not a project. A cleanup fixes today's estate. It does not stop profiles drifting, does not protect the next opening, and does not tell you which location slipped last month. Whoever signs off on a one-off fix should understand what it does and does not buy.
Thin locations are fragile in a way the average hides. Part Seven quantifies it: three bad reviews move a thin location twenty-five times more than a rich one, and cost the same twenty-seven five-star reviews to repair either way.
Nobody in the org chart owns it. Listing and review data sits across marketing, operations and whoever opens new sites. In most organisations that means no owner, no dashboard, and attention only after a complaint reaches somebody senior.
Every opening starts invisible, and that is a payback problem. A new restaurant begins at zero reviews beside siblings with thousands, losing local placement for months on a unit you have just funded. In a growth chain this recurs with every opening.
Clustering multiplies the cost of undifferentiated listings. Four restaurants in one metro is a sound property decision. Four identically-named listings in one metro is a separate and avoidable one.
Nobody owns listing construction. In an emerging chain the first restaurants get their profiles created by whoever opened them, and nobody goes back. By restaurant thirty there is no standard to enforce.
Location-level demand is currently unmeasurable. With identical listings and shared contact routes you cannot attribute search demand to a restaurant, which removes a number you would otherwise want in a site-performance review.
It is cheap and externally verifiable. One of very few marketing problems with a hard before-and-after that any customer, franchisee or competitor can check.

If any of the 10 scorecards looked uncomfortably familiar, there is a straightforward way to find out.

Next, Part TenWhich brand are you

Part Ten

Which brand are you

We will tell you. Privately, and at no cost.

The letters are not in rank order, and that is on purpose.

Brands in this study are anonymised. We hold a private key mapping each letter to its brand, along with a verification code that appears nowhere in this document.

Email us from a company domain and we will confirm your letter, quote your verification code back to you, and send the full underlying detail for your estate — every restaurant, every defect, named and specific. No charge, no meeting required, and we will not add you to anything.

audit@amplispot.com
Subject: QLPI 2026 — [your brand name]

We will not confirm any other brand's identity to you, and we will not confirm yours to anyone else. If you believe a defect we recorded is wrong, tell us — corrections are published in the next edition with the correction noted.