Realytics for multi-location operators

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Every question your COO, your CMO, your CFO or your board would ask about the estate — answered from consumer signal, with the basis shown, in the format you need.

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The same answer, in the format the moment needs — a chart in chat for a quick call, a written report for the regional review, a board-ready deck for Monday.

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The operator's blind spot

Your POS sees inside each store. We read the market around every one.

The decisions that matter — where to step in, where to price, where to open — turn on what's happening outside your four walls. Your own data stops at your own tills. And a estate-wide average quietly hides where it's actually breaking.

Your POS & BI

What happened inside the store.

Your transactions, your tickets, your own four walls — judged against a estate average. So a unit beating a tough street looks broken, a coaster on a hot street looks fine, and you act on the wrong ones.

Realytics

What's happening on the street.

Every unit read against the rivals its customers actually also weigh — consumer traffic, consumer opinions, prices and price perception — so a dip reads as the unit or the street, and the average stops hiding the break.

The store or the street

When a unit dips, see at a glance whether it's the unit or the whole local market — before you cut staff at a store that was actually winning its block.

Execution or product

See whether the drag is service, crowding, price-tag clarity and the bill, or the product itself — the difference between a fix you ship this quarter and a longer play.

The average that lies

A #1 national score can hide a 12-point collapse in one city. Read every unit on its own street, so the headline number stops pointing you the wrong way.

What you can ask

One analyst. Every job on the estate.

Pick the job in front of you. The same consumer signal around your units answers all of them — from the slipping store to the next site to the board deck.

Run the estate

Which units are slipping, where do I step in first, and is it the store or the street?

Store or street

Rank your locations, separate the store from its market

Every location scored on consumer experience and its trend, read against its own street — so you act on the units that are losing, not the ones in a tough market.

Execution vs product

See what's actually behind the dip

Whether the drag sits in service, speed, crowding, price-tag clarity and the bill, or in the product — so the fix list is right before it reaches the P&L.

Brand consistency

Find where the promise isn't being delivered

Where standards are consistent and where they're not, unit by unit and sub-brand by sub-brand — and which units tend to move first when something's wrong.

Win each local market

How do we stand market by market — against the rivals our customers actually also weigh?

True local set

Benchmark against the real competitors, not a list you guessed

Each unit compared to the rivals its consumers actually also engage with, declared up front — not a national average that buries the local picture.

Demand leakage

See where you're losing trade to the place across the street

Where customers split demand between you and a same-category rival nearby — the crowd quietly drifting, and to whom.

Perception by market

Read where the brand lands differently, city by city

Perception moves by market. See where the gap to the field is widest — often the biggest, most competitive city, where most of your units sit.

Price with the market

Are we priced right against our real local set — and is the value landing in the consumer's verdict?

Price & value perception

See where you sit over or under your true local rivals

By category, and whether a premium is landing in the consumer opinion or quietly costing you trade — the price-and-value verdict in your customers' own words.

Prices & average check

The money signals, read from the market

For food and drink, the prices on the menu read to the dish and the average check by daypart — so you see where a unit sits in its local price band, not just in your own books.

The acceptable band

Find the price a local market will actually accept

Where "too cheap" and "too expensive" meet in consumer language across a trade area — the headroom to move, by market.

Grow the estate

Where do we open next, which markets look like our winners, and will a new unit cannibalise one we run?

Next market, ranked

Rank trade areas by real local demand

A catchment's share of category activity against its share of population — and the whitespace where demand out-runs the units serving it. (A trade area is the local catchment a unit draws from.)

Look-alikes

Find the markets that resemble your top performers

Catchments that match your strongest units on demand, competition and consumer profile — so a new build starts from the pattern that already works.

Cannibalisation

Pressure-test a new site before you sign

How much a new unit would cross-shop an existing one, from cross-visitation and shared consumer mentions — so growth adds trade instead of moving it across the street.

Read every industry, find the pain

Six industries. Every time, the national average sent them the wrong way.

These are real Realytics reads, anonymized. Different industries, one recurring pattern: the brand-level or national read gave the wrong answer — and reading at street level overturned it.

Coffee · a national coffee chain · ~17,000 US units

Your fiercest rival isn't another coffee chain. It's a burger chain — and it changes by city.

A Burger Chain, Not A Coffee One Rival Set Flips City To City 28% vs 78% — Door, Not Cup

A national coffee chain wanted to know which units were slipping — and benchmarked them against the obvious coffee rivals. Read against the brands its own customers actually also weigh, that comp set is wrong in nearly every market. Across eight of its biggest US metros, the #1 also-weighed brand is a fast-food chain — not a coffee one. In four of those metros (its Sun Belt cities) no coffee chain reaches the top tier of consideration at all. In Chicago the burger chain sits at 15.7% against the nearest coffee rival's 10.3%. In Los Angeles, Houston, Phoenix and Dallas the top eight also-weighed brands are all fast food — zero coffee chains present. Then the inversion: in the chain's own home metro, the rivals aren't chains at all — they're local independent coffee shops. The competitive set isn't just wider. It's a different shape in every city.

The finding

The instinct

One comp set, everywhere

Build a national rival list — the named coffee chains — and benchmark every unit against it. If a store is slipping, you know which competitor is taking the occasion.

The signal

The comp set is wrong, city by city

In Sun Belt metros, no coffee chain appears in the top consideration tier — the real rivals are burger and QSR chains. In the home metro, the rivals are local independent roasters with no national chain presence. And across all markets, the drag is in the door not the cup: wait, order accuracy and drive-thru read 28% positive against 78% for the core coffee.

By the numbers

50 pts

operations vs core coffee — the drag is the door, not the cup

15.7%

burger chain vs nearest coffee rival in Chicago

4 of 8

Sun Belt metros with no coffee chain in the top rival set

~17,000

US units, each scored against its own local rivals

The lesson

Your comp set is built by the city, not the org chart — so score every door against the brands its own customers actually weigh, market by market.

Hospitality · a global hotel operator · Gulf resort market

Your asset is fine. The hotel 210 metres away is taking the trade — at your front desk.

210m: The Rival Next Door 6× The Opinion Volume Lost At The Door, Not The Room

We put a Gulf resort operator's flagship property next to the rival it can see from its own lobby — 210 metres down the same beach. The neighbour carries six times the consumer-opinion volume and a 95.5% positive share against the operator's 81.8% — a 13.7-point gap on tens of thousands of opinions. Read it dimension by dimension and the picture flips: on the physical asset the operator is at parity or ahead. The entire gap points to the welcome — to the moment a guest arrives at the door. You're not losing on the building. You're losing the door, to the resort across the street.

The finding

The product — competitive

The room holds its own

On the physical asset — the room, the facilities, the beach — the operator's property reads at parity or ahead of the rival next door. The asset is not the problem. The sub-brand estate spans a 17-point range (72–89), but the building itself is not bleeding trade.

The leakage — a single moment

The welcome is the gap

The rival 210 metres away carries a consistently strong signal at the front desk — and the operator's own property does not. That single dimension, on the one rival guests can see from the lobby, accounts for the entire gap. It only shows up when you read this property against the specific rival its own guests also weigh — one experience dimension at a time, not the brand-wide average.

By the numbers

−14 pts

same beach, 210 m apart — the building is parity, the door is the drag

6×

rival's consumer-opinion volume, same beach

81.8%

operator's positive-opinion share

72–89

positive-opinion share range, sub-brand estate

The lesson

A growing estate doesn't tell you which door is bleeding trade to the property next door. Read each asset against its own local rivals — experience dimension by dimension — and the fix becomes obvious.

Specialty retail · a global sportswear leader · ~2,500 stores

Same outlet format. Beloved in one country, broken in the next.

Same Format, 5× Apart Crowding & Checkout, Not Product US: 2.3 Praises Per Complaint

We read the same off-price outlet format across the estate, country by country. In the US it delights — 2.3 positive consumer opinions for every negative one. In Spain and France the identical format runs net-negative, more than two complaints per praise — on the same merchandise. The blended channel average hid a five-fold execution gap. The drag isn't the channel and it isn't the product. It's the floor: crowding, checkout, and staffing in two specific markets that a regional manager can act on this quarter.

The finding

The format & the product — intact

US outlets run at 2.3:1 positive

The off-price outlet channel is not the problem. In the US it is the highest-sentiment format in the estate. Product and stock read as the mildest negative theme even in the weakest markets. Consumer advocacy for the brand itself leads the field.

Southern Europe execution — the break

Spain and France run below 0.5:1

The identical outlet format scores net-negative in Spain (0.43 positive per negative) and France (0.47). The gap is not merchandise — product sentiment is mild in both. It is crowding and checkout (near -1.0 in both markets) then staff and service. Germany and the UK run the same format at 1.0:1 and 0.9:1 and hold. The break is Southern Europe, not the channel and not the continent.

By the numbers

5×

US outlet vs Spain and France — same format, five-fold consumer-opinion gap

2.3:1

US outlet consumer opinions — highest in the estate

0.4:1

Spain and France outlets — net-negative on identical merchandise

−1

crowding and checkout drag in French outlets, not the product

The lesson

The channel isn't the culprit — two markets are. Read the same format across every region, and the fix writes itself: route the regional manager to Spain and France, hand them the German outlet playbook.

Grocery · a national grocery chain · cross-metro estate

Your toughest rival isn't a supermarket. It's the dollar store.

#1 Rival Is A Dollar Store But The Flow Runs 2-To-1 Your Way You're The Trade-Up, Not The Leak

A national grocery chain asked which rivals were taking its trade. It benchmarked against other supermarkets — the obvious set. When we read which chains its own shoppers actually also visit, the #1 cross-shopped store wasn't a grocery rival at all: it was a dollar store, drawing more of the chain's customers than any supermarket on the list. That reads like an alarm — until you measure the same two stores the other way. For every shopper of yours who also stops at that dollar store, roughly two of its shoppers also come to you — you're its single most cross-shopped chain, ahead of every other grocer it shares. On the value-floor split you're the one pulling traffic in, not bleeding it out. None of it appears in a POS, because both halves of the trip happen in stores the operator never thought to count.

The finding

The benchmark you run

Supermarkets vs. supermarkets

The competitive map covers the nearest grocery rivals — the same format, the same category. That's the set the brand monitors, the set it promotes against. It misses where the basket actually splits.

Where the basket actually goes — and which way it nets

A dollar store leads the list — but the traffic nets your way

In metro after metro the single most cross-shopped chain among the grocer's own customers is a dollar store — above every supermarket competitor, above the premium banners. It shows up as "indirect" in the category map, so the operator never benchmarks against it. But read the same pair both directions and the alarm flips: the discounter sends back roughly twice the shoppers it draws (its customers' #1 cross-shopped chain is the full-price grocer, ahead of every other supermarket). The split is real and structural — it replicates across three metros — and on net you're the trade-up destination, not the one losing the basket.

By the numbers

2×

net cross-traffic with the #1 dollar-store rival — flows back your way

grocer: dollar-store shoppers' top cross-visit

3 metros

markets where the inbound flow runs your way

The lesson

The chain splitting your basket isn't in your competitive set — and the headline can mislead you twice. Read who your shoppers also visit, then read it the other way: the direction the traffic actually nets tells you whether to defend or to convert.

Retail banking · a national branch estate · 160 branches

One bank, one city — one branch scores 67, the one down the street scores 0.

Same Brand, 0 To 67 No Branch Lives At The Average Triage By Door, Not By Banner

We read one bank's entire branch estate, door by door, on the consumer opinions its own customers leave. The brand average is about 26% positive. No branch actually lives there: a third of branches with signal are all-negative while a fifth score 40 or above — and the extremes sit in the same cities, sometimes streets apart. In one city: a branch at 67, and one at 0. The average is a ghost. The fix is a ranked list of specific doors.

The finding

The brand signal — strong foundations

The people are the constant

Staff dedication 89%, friendliness 87%, patience 84%; location convenience 95%. The front line earns real goodwill at every branch. That makes the variance impossible to explain away as a people problem.

The estate spread — bimodal, not a bell curve

The average describes zero branches

13 of 41 branches with signal are all-negative (0% positive). 9 score 40 or above. The worst and best branches sit in the same cities — the street is identical; the execution isn't. Reachability is where they break: phone responsiveness 1%, customer-service 3%, appointment system 4%, queue management 8%.

By the numbers

67pt

top branch vs a floor of 0 — same brand, same city, streets apart

32%

branches with signal that are all-negative

phone responsiveness — the estate's lowest reachability score

branches scoring 40 or above — top fifth of the estate

The lesson

The sector average and your own NPS dashboard both hide this. You only see the triage list — which exact doors to walk into this quarter — when you read the whole estate from outside, branch by branch.

Pharmacy · a national drugstore chain · four US metros

The same store rating is a market lead in one city and a deficit in the next.

Leader +6 vs Laggard −16 Same Score, Opposite Standing Read The Street, Not The Score

A national drugstore chain read its own store ratings and saw a uniform national picture. Read each store against the pharmacies actually around it and the same score means opposite things. In Phoenix the chain's ~43% positive consumer opinion beats the local pharmacy field by six points — it is the market leader. In Chicago a ~33% trails the local field by sixteen — the laggard. And a healthy-looking ~42% in Los Angeles is only par. Same brand, same playbook; a national average that sits about six points behind the field hides a 22-point swing in competitive standing. The rating tells you nothing until you read the street.

The finding

The national scoreboard

One number, looks uniform

On its own consumer-opinion share the chain reads a flat ~35% positive nationally — about six points behind the local pharmacy field overall. Head office sees one middling line and triages every market the same way.

The local read

Leader, par, or laggard — by metro

Scored against each metro's own pharmacy field on the same yardstick, the standing flips: Phoenix +6 (ahead of the street), Houston and Los Angeles within ~3 points (par), Chicago −16 (behind). The metro where the absolute score looks healthiest (LA, ~42) is only level; the leader and the laggard are both invisible in the average.

By the numbers

22 pts

competitive-standing swing across four US metros — same brand, same window

+6 pts

Phoenix ahead of its local pharmacy field

−16 pts

Chicago trailing its local pharmacy field

~35%

chain's national consumer-opinion share vs ~41% local field

The lesson

A store's rating is meaningless on its own — the same number is a win in one market and a loss in another. Score every store against its local field, never the national average.

The data behind every answer

Every unit, every rival, every street.

One current view of the market around your locations — consumer traffic, consumer opinions, prices and price perception — matched onto every business, refreshed weekly, and benchmarked.

288M

locations mapped — your units, and every rival on their streets.

11.5B+

consumer signals across commerce

4.36M

menus read to the dish, with prices

3,313

categories — every consumer-facing industry

252

countries & territories

Weeklyrefreshed, since 2020

Priceconsumer price & value perception, plus menu prices & average check

Every industryfrom cafés to clinics to bank branches

Public business information and aggregated, anonymous consumer signal — never personal data, GDPR and CCPA compliant, with role-based access and an audit trail on every answer. See the data coverage →

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Your on-demand analyst.

Realytics for operators — every location, every market, one clear read. Answers in about 60 seconds what a consultant answers in a quarter.

Essential

For growing operators. 11–50 locations.

⁦ALL 16,258 ($198)⁩/seat·mo

75,000 credits / mo

Cross-industry data, no limits
Consumer traffic + consumer opinions on every block
Refreshed weekly — ask anytime
Reports & decks, on-brand

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