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Location³

A data-driven framework for global QSR expansion

From Intuition to Evidence

“Location, location, location.” For decades, this phrase was the mantra of retailers and restaurateurs. Simple to repeat, harder to act on. But behind the simplicity of the slogan hides one of the most complex business challenges: deciding not just where to be, but how to make that decision.

In the QSR world, expansion choices have too often rested on instinct, tradition, or the most obvious metric — headcount. If the population was big, the thinking went, the market must be right. Sometimes the hunch held. More often, the risks only surfaced after millions had been sunk.

The margin for error is shrinking. With rents climbing, inflation squeezing margins, and competitors crowding the map, a single misjudgment on location can be costly. Choosing the wrong market risks an entire strategy; choosing the wrong site risks the store itself before it has a chance to succeed.That is why leading QSR brands are moving away from gut feel. They are treating location as a structured, evidence-based process. And when you look at it that way, the old mantra takes on a sharper meaning: location not once, but three times — country, region, street.

The Three Levels of Decisions

These three levels are interconnected. Misjudge the country, and the smartest street pick won’t matter. Miss the details at street level, and a promising country entry fizzles. Treating them as a unified framework helps leaders align strategy with execution.

Location 1 – Country

At a global pizza chain with more than a thousand locations, the marketing lead is reviewing a shortlist of potential new markets. Turkey has moved high on the list, and she spreads the report across the table.

“Eighty million people, a growing economy, a major metropolitan hub in Istanbul,” she says. “On scale alone, this looks compelling. But we know scale isn’t everything. Let’s test this properly.” The analyst nods and adds context. “Exactly. A headcount doesn’t equal a customer base. What matters is how often people eat out, and whether pizza is part of that dining culture.”

On a notepad he sketches three indicators:

  • Industry density — how developed the restaurant and café culture really is.
  • Segment share — the slice of that culture currently claimed by pizza.
  • Growth trajectory — whether that slice is rising or stagnating.

The numbers reframe the picture. Turkey’s dining-out culture is vibrant, but pizza barely registers: about 2 percent of sales, compared with 9 percent in mature markets.

The marketing lead studies the chart. “So the segment is small, but it’s growing — and underrepresented.”

“That’s not a weakness, it’s open space. Turkey isn’t just large — it leaves plenty of room for growth in the category where we already play,” said the analyst.

Location 2 – Region/City

With the country validated, the team faces the next challenge: Where inside Turkey should we begin? The marketing lead circles Istanbul twice on the map. “It’s massive. Ankara is the capital. Izmir is on the rise. Shouldn’t we just follow population size again?”

The analyst, sitting across the table, opens his laptop. “Population is a signal, yes, but it’s only the surface. What we really need to see is where the dining-out culture is strongest, and how much of that culture pizza has already claimed.”

“Put them together,” the analyst says, “and every province falls into one of four boxes:”

  1. High density, high share – developed, but highly competitive.
  2. High density, low share – strong dining culture, but pizza underrepresented — high-potential ground for us.
  3. Low density, high share – small markets where pizza is already squeezed in.
  4. Low density, low share – low priority for now.

The western seaboard and tourist regions light up in the high-potential quadrant: places where people eat out often, but pizza is hardly present. Istanbul, by contrast, is clearly high/high: undeniable scale, but also saturated with rivals.

This tells us not just where people live, but where they actually eat — and whether pizza is part of that habit

If we want early wins, we should look at the high-potential regions: they’re developed enough to sustain us, but still open enough for us to stand out.”For the team, the analysis sharpened the shortlist. Istanbul remained the country’s undeniable hub, but its maturity and saturation raised the barrier to entry. By contrast, Izmir combined a vibrant dining culture with very low category penetration, signaling both headroom and manageable competitive pressure. As a result, Izmir was chosen as the pilot city — large enough to matter, open enough to learn, and representative enough to guide further expansion.

Location 3 – Street/Neighborhood

With Turkey validated and Izmir shortlisted, the final question is sharper: Which specific site inside the city deserves investment?

The marketing lead spreads the map across the table. “Five options,” she says. “Two by the waterfront, one in a residential district, one near the mall, one by the university. Each has an argument. The waterfront promises visibility, the mall offers steady traffic, the university brings youth. But which of these factors really translates into sales?”

The analyst overlays a heatmap of food traffic. Bright clusters flare across the city grid. “Look here,” he points out. “Three of our candidates fall inside these high-consumption clusters; two lie far outside. Raw visibility isn’t enough — what matters is where people actually go to eat.”

The marketer leans forward. “So it’s not about how many people pass by, but how much of that movement is food-related.” “That’s the idea,” the analyst replies.

The heatmap analysis divided Izmir’s food traffic into five clusters. The top 20% — the “red zone” — was then broken into four sub-segments, exposing the five most valuable micro-territories.

When the team overlaid competitor locations, the pattern was clear: nearly every major player was already inside these clusters. McDonald’s had 100% of its stores there, Burger King 87%, Domino’s 77%. The leaders were betting heavily on the same high-intensity zones — and Realytics confirmed that two of the client’s proposed sites fell right inside them.

“Some chains deliberately place stores near anchors like McDonald’s or Burger King because those brands guarantee stable flows. Others prefer to stay apart to avoid fighting for the same wallet. Either way, knowing who your neighbors are is part of the revenue equation.”

Co-location isn’t automatically good or bad — it is a strategic choice. What matters is that the patterns are now visible, making the trade-offs easier to evaluate

Finally, the analyst layers in purchasing power: average check size multiplied by traffic volume. “This is where intuition often fails,” he says. “One waterfront site looks attractive on footfall alone, but spend there is low — plenty of people, little margin. By contrast, the mall site combines decent traffic with higher spend per visit. That mix makes it far more valuable than it first appeared.”

The team studies the ranked list. Two sites emerge as strong investments. One is suitable for a cautious pilot. Two are better dropped for now. Street-level analytics prove why evidence matters most where money meets the pavement.

Principles of Data-Driven Decisions

The Izmir case shows a larger truth: strong decisions rest on principles, not impressions.

Combine layers

Demographics without traffic mislead. Traffic without competitor context overstates opportunity. Spending power only matters when paired with footfall. Real insight comes from stacking these layers, not from leaning on one.

Move from comparison to prediction

Early on, we compare: country vs. country, street vs. street. As data grows, we forecast: how will this site perform tomorrow compared with the portfolio?

Scale beats intuition

Field visits and gut feeling still add color, but they cannot match the reach and speed of scalable models. Data doesn’t replace judgment; it anchors it.

From Framework to Practice

Looked at separately, the three levels may feel like isolated steps. Seen together, they form a pipeline of choices.

At the strategic level, leaders determine if the fundamentals of a market make entry worthwhile. In the middle, the team filters those opportunities into a shortlist of regions. At the bottom, strategy turns into tangible commitments — leases signed, stores opened, capital at work.

Each layer asks a different question, draws on different evidence, and shields against a different kind of risk. Sequenced in this way, ambition doesn’t scatter — it flows. Expansion becomes not a gamble, but a process that can be managed, tested, and repeated.

Applied systematically, these principles turn “location, location, location” from a slogan into a method

Rethinking “Location, Location, Location”

For decades, the phrase was repeated more than explained. Geography seemed to be everything, yet no one said how to choose.

Today, the mantra survives, but its meaning has shifted. Country, region, street — each one a decision, each one a risk, each one a discipline of its own.

The lesson for leaders is blunt. Instinct has a place. But instinct alone is too costly. Expansion can be structured, tested, and repeated — a process that turns ambition into measurable results.

“Location, location, location” still matters. And now it matters because we finally have the tools to make each location the right one.

1000 N. West Street, Suite 1200Wilmington, Delaware, 19801, USA

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Cookie Policy

Privacy Policy

Products

Insights

Our data

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Log in

Become a partner

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Realytics

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Case Studies

Location³

A data-driven framework for global QSR expansion

From Intuition to Evidence

“Location, location, location.” For decades, this phrase was the mantra of retailers and restaurateurs. Simple to repeat, harder to act on. But behind the simplicity of the slogan hides one of the most complex business challenges: deciding not just where to be, but how to make that decision.

In the QSR world, expansion choices have too often rested on instinct, tradition, or the most obvious metric — headcount. If the population was big, the thinking went, the market must be right. Sometimes the hunch held. More often, the risks only surfaced after millions had been sunk.

The margin for error is shrinking. With rents climbing, inflation squeezing margins, and competitors crowding the map, a single misjudgment on location can be costly. Choosing the wrong market risks an entire strategy; choosing the wrong site risks the store itself before it has a chance to succeed.That is why leading QSR brands are moving away from gut feel. They are treating location as a structured, evidence-based process. And when you look at it that way, the old mantra takes on a sharper meaning: location not once, but three times — country, region, street.

The Three Levels of Decisions

These three levels are interconnected. Misjudge the country, and the smartest street pick won’t matter. Miss the details at street level, and a promising country entry fizzles. Treating them as a unified framework helps leaders align strategy with execution.

Location 1 – Country

At a global pizza chain with more than a thousand locations, the marketing lead is reviewing a shortlist of potential new markets. Turkey has moved high on the list, and she spreads the report across the table.

“Eighty million people, a growing economy, a major metropolitan hub in Istanbul,” she says. “On scale alone, this looks compelling. But we know scale isn’t everything. Let’s test this properly.” The analyst nods and adds context. “Exactly. A headcount doesn’t equal a customer base. What matters is how often people eat out, and whether pizza is part of that dining culture.”

On a notepad he sketches three indicators:

  • Industry density — how developed the restaurant and café culture really is.
  • Segment share — the slice of that culture currently claimed by pizza.
  • Growth trajectory — whether that slice is rising or stagnating.

The numbers reframe the picture. Turkey’s dining-out culture is vibrant, but pizza barely registers: about 2 percent of sales, compared with 9 percent in mature markets.

The marketing lead studies the chart. “So the segment is small, but it’s growing — and underrepresented.”

“That’s not a weakness, it’s open space. Turkey isn’t just large — it leaves plenty of room for growth in the category where we already play,” said the analyst.

Location 2 – Region/City

With the country validated, the team faces the next challenge: Where inside Turkey should we begin? The marketing lead circles Istanbul twice on the map. “It’s massive. Ankara is the capital. Izmir is on the rise. Shouldn’t we just follow population size again?”

The analyst, sitting across the table, opens his laptop. “Population is a signal, yes, but it’s only the surface. What we really need to see is where the dining-out culture is strongest, and how much of that culture pizza has already claimed.”

“Put them together,” the analyst says, “and every province falls into one of four boxes:”

  1. High density, high share – developed, but highly competitive.
  2. High density, low share – strong dining culture, but pizza underrepresented — high-potential ground for us.
  3. Low density, high share – small markets where pizza is already squeezed in.
  4. Low density, low share – low priority for now.

The western seaboard and tourist regions light up in the high-potential quadrant: places where people eat out often, but pizza is hardly present. Istanbul, by contrast, is clearly high/high: undeniable scale, but also saturated with rivals.

This tells us not just where people live, but where they actually eat — and whether pizza is part of that habit

If we want early wins, we should look at the high-potential regions: they’re developed enough to sustain us, but still open enough for us to stand out.”For the team, the analysis sharpened the shortlist. Istanbul remained the country’s undeniable hub, but its maturity and saturation raised the barrier to entry. By contrast, Izmir combined a vibrant dining culture with very low category penetration, signaling both headroom and manageable competitive pressure. As a result, Izmir was chosen as the pilot city — large enough to matter, open enough to learn, and representative enough to guide further expansion.

Location 3 – Street/Neighborhood

With Turkey validated and Izmir shortlisted, the final question is sharper: Which specific site inside the city deserves investment?

The marketing lead spreads the map across the table. “Five options,” she says. “Two by the waterfront, one in a residential district, one near the mall, one by the university. Each has an argument. The waterfront promises visibility, the mall offers steady traffic, the university brings youth. But which of these factors really translates into sales?”

The analyst overlays a heatmap of food traffic. Bright clusters flare across the city grid. “Look here,” he points out. “Three of our candidates fall inside these high-consumption clusters; two lie far outside. Raw visibility isn’t enough — what matters is where people actually go to eat.”

The marketer leans forward. “So it’s not about how many people pass by, but how much of that movement is food-related.” “That’s the idea,” the analyst replies.

The heatmap analysis divided Izmir’s food traffic into five clusters. The top 20% — the “red zone” — was then broken into four sub-segments, exposing the five most valuable micro-territories.

When the team overlaid competitor locations, the pattern was clear: nearly every major player was already inside these clusters. McDonald’s had 100% of its stores there, Burger King 87%, Domino’s 77%. The leaders were betting heavily on the same high-intensity zones — and Realytics confirmed that two of the client’s proposed sites fell right inside them.

“Some chains deliberately place stores near anchors like McDonald’s or Burger King because those brands guarantee stable flows. Others prefer to stay apart to avoid fighting for the same wallet. Either way, knowing who your neighbors are is part of the revenue equation.”

Co-location isn’t automatically good or bad — it is a strategic choice. What matters is that the patterns are now visible, making the trade-offs easier to evaluate

Finally, the analyst layers in purchasing power: average check size multiplied by traffic volume. “This is where intuition often fails,” he says. “One waterfront site looks attractive on footfall alone, but spend there is low — plenty of people, little margin. By contrast, the mall site combines decent traffic with higher spend per visit. That mix makes it far more valuable than it first appeared.”

The team studies the ranked list. Two sites emerge as strong investments. One is suitable for a cautious pilot. Two are better dropped for now. Street-level analytics prove why evidence matters most where money meets the pavement.

Principles of Data-Driven Decisions

The Izmir case shows a larger truth: strong decisions rest on principles, not impressions.

Combine layers

Demographics without traffic mislead. Traffic without competitor context overstates opportunity. Spending power only matters when paired with footfall. Real insight comes from stacking these layers, not from leaning on one.

Move from comparison to prediction

Early on, we compare: country vs. country, street vs. street. As data grows, we forecast: how will this site perform tomorrow compared with the portfolio?

Scale beats intuition

Field visits and gut feeling still add color, but they cannot match the reach and speed of scalable models. Data doesn’t replace judgment; it anchors it.

From Framework to Practice

Looked at separately, the three levels may feel like isolated steps. Seen together, they form a pipeline of choices.

At the strategic level, leaders determine if the fundamentals of a market make entry worthwhile. In the middle, the team filters those opportunities into a shortlist of regions. At the bottom, strategy turns into tangible commitments — leases signed, stores opened, capital at work.

Each layer asks a different question, draws on different evidence, and shields against a different kind of risk. Sequenced in this way, ambition doesn’t scatter — it flows. Expansion becomes not a gamble, but a process that can be managed, tested, and repeated.

Applied systematically, these principles turn “location, location, location” from a slogan into a method

Rethinking “Location, Location, Location”

For decades, the phrase was repeated more than explained. Geography seemed to be everything, yet no one said how to choose.

Today, the mantra survives, but its meaning has shifted. Country, region, street — each one a decision, each one a risk, each one a discipline of its own.

The lesson for leaders is blunt. Instinct has a place. But instinct alone is too costly. Expansion can be structured, tested, and repeated — a process that turns ambition into measurable results.

“Location, location, location” still matters. And now it matters because we finally have the tools to make each location the right one.

AI-Powered Performance& Consumer Analyticsfor Offline Business

Reality Analytics, Inc. © 2025 

1000 N. West Street, Suite 1200Wilmington, Delaware, 19801, USA

Terms of Service

Cookie Policy

Privacy Policy

Products

Insights

Our data

Pricing

About us

Log in

Become a partner

Become a client

Realytics

/

Resources

/

Case Studies

Location³

A data-driven framework for global QSR expansion

From Intuition to Evidence

“Location, location, location.” For decades, this phrase was the mantra of retailers and restaurateurs. Simple to repeat, harder to act on. But behind the simplicity of the slogan hides one of the most complex business challenges: deciding not just where to be, but how to make that decision.

In the QSR world, expansion choices have too often rested on instinct, tradition, or the most obvious metric — headcount. If the population was big, the thinking went, the market must be right. Sometimes the hunch held. More often, the risks only surfaced after millions had been sunk.

The margin for error is shrinking. With rents climbing, inflation squeezing margins, and competitors crowding the map, a single misjudgment on location can be costly. Choosing the wrong market risks an entire strategy; choosing the wrong site risks the store itself before it has a chance to succeed.That is why leading QSR brands are moving away from gut feel. They are treating location as a structured, evidence-based process. And when you look at it that way, the old mantra takes on a sharper meaning: location not once, but three times — country, region, street.

The Three Levels of Decisions

These three levels are interconnected. Misjudge the country, and the smartest street pick won’t matter. Miss the details at street level, and a promising country entry fizzles. Treating them as a unified framework helps leaders align strategy with execution.

Location 1 – Country

At a global pizza chain with more than a thousand locations, the marketing lead is reviewing a shortlist of potential new markets. Turkey has moved high on the list, and she spreads the report across the table.

“Eighty million people, a growing economy, a major metropolitan hub in Istanbul,” she says. “On scale alone, this looks compelling. But we know scale isn’t everything. Let’s test this properly.” The analyst nods and adds context. “Exactly. A headcount doesn’t equal a customer base. What matters is how often people eat out, and whether pizza is part of that dining culture.”

On a notepad he sketches three indicators:

  • Industry density — how developed the restaurant and café culture really is.
  • Segment share — the slice of that culture currently claimed by pizza.
  • Growth trajectory — whether that slice is rising or stagnating.

The numbers reframe the picture. Turkey’s dining-out culture is vibrant, but pizza barely registers: about 2 percent of sales, compared with 9 percent in mature markets.

The marketing lead studies the chart. “So the segment is small, but it’s growing — and underrepresented.”

“That’s not a weakness, it’s open space. Turkey isn’t just large — it leaves plenty of room for growth in the category where we already play,” said the analyst.

Location 2 – Region/City

With the country validated, the team faces the next challenge: Where inside Turkey should we begin? The marketing lead circles Istanbul twice on the map. “It’s massive. Ankara is the capital. Izmir is on the rise. Shouldn’t we just follow population size again?”

The analyst, sitting across the table, opens his laptop. “Population is a signal, yes, but it’s only the surface. What we really need to see is where the dining-out culture is strongest, and how much of that culture pizza has already claimed.”

“Put them together,” the analyst says, “and every province falls into one of four boxes:”

  1. High density, high share – developed, but highly competitive.
  2. High density, low share – strong dining culture, but pizza underrepresented — high-potential ground for us.
  3. Low density, high share – small markets where pizza is already squeezed in.
  4. Low density, low share – low priority for now.

The western seaboard and tourist regions light up in the high-potential quadrant: places where people eat out often, but pizza is hardly present. Istanbul, by contrast, is clearly high/high: undeniable scale, but also saturated with rivals.

This tells us not just where people live, but where they actually eat — and whether pizza is part of that habit

If we want early wins, we should look at the high-potential regions: they’re developed enough to sustain us, but still open enough for us to stand out.”For the team, the analysis sharpened the shortlist. Istanbul remained the country’s undeniable hub, but its maturity and saturation raised the barrier to entry. By contrast, Izmir combined a vibrant dining culture with very low category penetration, signaling both headroom and manageable competitive pressure. As a result, Izmir was chosen as the pilot city — large enough to matter, open enough to learn, and representative enough to guide further expansion.

Location 3 – Street/Neighborhood

With Turkey validated and Izmir shortlisted, the final question is sharper: Which specific site inside the city deserves investment?

The marketing lead spreads the map across the table. “Five options,” she says. “Two by the waterfront, one in a residential district, one near the mall, one by the university. Each has an argument. The waterfront promises visibility, the mall offers steady traffic, the university brings youth. But which of these factors really translates into sales?”

The analyst overlays a heatmap of food traffic. Bright clusters flare across the city grid. “Look here,” he points out. “Three of our candidates fall inside these high-consumption clusters; two lie far outside. Raw visibility isn’t enough — what matters is where people actually go to eat.”

The marketer leans forward. “So it’s not about how many people pass by, but how much of that movement is food-related.” “That’s the idea,” the analyst replies.

The heatmap analysis divided Izmir’s food traffic into five clusters. The top 20% — the “red zone” — was then broken into four sub-segments, exposing the five most valuable micro-territories.

When the team overlaid competitor locations, the pattern was clear: nearly every major player was already inside these clusters. McDonald’s had 100% of its stores there, Burger King 87%, Domino’s 77%. The leaders were betting heavily on the same high-intensity zones — and Realytics confirmed that two of the client’s proposed sites fell right inside them.

“Some chains deliberately place stores near anchors like McDonald’s or Burger King because those brands guarantee stable flows. Others prefer to stay apart to avoid fighting for the same wallet. Either way, knowing who your neighbors are is part of the revenue equation.”

Co-location isn’t automatically good or bad — it is a strategic choice. What matters is that the patterns are now visible, making the trade-offs easier to evaluate

Finally, the analyst layers in purchasing power: average check size multiplied by traffic volume. “This is where intuition often fails,” he says. “One waterfront site looks attractive on footfall alone, but spend there is low — plenty of people, little margin. By contrast, the mall site combines decent traffic with higher spend per visit. That mix makes it far more valuable than it first appeared.”

The team studies the ranked list. Two sites emerge as strong investments. One is suitable for a cautious pilot. Two are better dropped for now. Street-level analytics prove why evidence matters most where money meets the pavement.

Principles of Data-Driven Decisions

The Izmir case shows a larger truth: strong decisions rest on principles, not impressions.

Combine layers

Demographics without traffic mislead. Traffic without competitor context overstates opportunity. Spending power only matters when paired with footfall. Real insight comes from stacking these layers, not from leaning on one.

Move from comparison to prediction

Early on, we compare: country vs. country, street vs. street. As data grows, we forecast: how will this site perform tomorrow compared with the portfolio?

Scale beats intuition

Field visits and gut feeling still add color, but they cannot match the reach and speed of scalable models. Data doesn’t replace judgment; it anchors it.

From Framework to Practice

Looked at separately, the three levels may feel like isolated steps. Seen together, they form a pipeline of choices.

At the strategic level, leaders determine if the fundamentals of a market make entry worthwhile. In the middle, the team filters those opportunities into a shortlist of regions. At the bottom, strategy turns into tangible commitments — leases signed, stores opened, capital at work.

Each layer asks a different question, draws on different evidence, and shields against a different kind of risk. Sequenced in this way, ambition doesn’t scatter — it flows. Expansion becomes not a gamble, but a process that can be managed, tested, and repeated.

Applied systematically, these principles turn “location, location, location” from a slogan into a method

Rethinking “Location, Location, Location”

For decades, the phrase was repeated more than explained. Geography seemed to be everything, yet no one said how to choose.

Today, the mantra survives, but its meaning has shifted. Country, region, street — each one a decision, each one a risk, each one a discipline of its own.

The lesson for leaders is blunt. Instinct has a place. But instinct alone is too costly. Expansion can be structured, tested, and repeated — a process that turns ambition into measurable results.

“Location, location, location” still matters. And now it matters because we finally have the tools to make each location the right one.

AI-Powered Performance& Consumer Analyticsfor Offline Business

Reality Analytics, Inc. © 2025 

1000 N. West Street, Suite 1200Wilmington, Delaware, 19801, USA

Terms of Service

Cookie Policy

Privacy Policy

Products

Insights

Our data

Pricing

About us

Log in

Become a partner

Become a client

Realytics

/

Insights

/

Case Studies

Location³

A data-driven framework for global QSR expansion

From Intuition to Evidence

“Location, location, location.” For decades, this phrase was the mantra of retailers and restaurateurs. Simple to repeat, harder to act on. But behind the simplicity of the slogan hides one of the most complex business challenges: deciding not just where to be, but how to make that decision.

In the QSR world, expansion choices have too often rested on instinct, tradition, or the most obvious metric — headcount. If the population was big, the thinking went, the market must be right. Sometimes the hunch held. More often, the risks only surfaced after millions had been sunk.

The margin for error is shrinking. With rents climbing, inflation squeezing margins, and competitors crowding the map, a single misjudgment on location can be costly. Choosing the wrong market risks an entire strategy; choosing the wrong site risks the store itself before it has a chance to succeed.That is why leading QSR brands are moving away from gut feel. They are treating location as a structured, evidence-based process. And when you look at it that way, the old mantra takes on a sharper meaning: location not once, but three times — country, region, street.

The Three Levels of Decisions

These three levels are interconnected. Misjudge the country, and the smartest street pick won’t matter. Miss the details at street level, and a promising country entry fizzles. Treating them as a unified framework helps leaders align strategy with execution.

Location 1 – Country

At a global pizza chain with more than a thousand locations, the marketing lead is reviewing a shortlist of potential new markets. Turkey has moved high on the list, and she spreads the report across the table.

“Eighty million people, a growing economy, a major metropolitan hub in Istanbul,” she says. “On scale alone, this looks compelling. But we know scale isn’t everything. Let’s test this properly.” The analyst nods and adds context. “Exactly. A headcount doesn’t equal a customer base. What matters is how often people eat out, and whether pizza is part of that dining culture.”

On a notepad he sketches three indicators:

  • Industry density — how developed the restaurant and café culture really is.
  • Segment share — the slice of that culture currently claimed by pizza.
  • Growth trajectory — whether that slice is rising or stagnating.

The numbers reframe the picture. Turkey’s dining-out culture is vibrant, but pizza barely registers: about 2 percent of sales, compared with 9 percent in mature markets.

The marketing lead studies the chart. “So the segment is small, but it’s growing — and underrepresented.”

“That’s not a weakness, it’s open space. Turkey isn’t just large — it leaves plenty of room for growth in the category where we already play,” said the analyst.

Location 2 – Region/City

With the country validated, the team faces the next challenge: Where inside Turkey should we begin? The marketing lead circles Istanbul twice on the map. “It’s massive. Ankara is the capital. Izmir is on the rise. Shouldn’t we just follow population size again?”

The analyst, sitting across the table, opens his laptop. “Population is a signal, yes, but it’s only the surface. What we really need to see is where the dining-out culture is strongest, and how much of that culture pizza has already claimed.”

“Put them together,” the analyst says, “and every province falls into one of four boxes:”

  1. High density, high share – developed, but highly competitive.
  2. High density, low share – strong dining culture, but pizza underrepresented — high-potential ground for us.
  3. Low density, high share – small markets where pizza is already squeezed in.
  4. Low density, low share – low priority for now.

The western seaboard and tourist regions light up in the high-potential quadrant: places where people eat out often, but pizza is hardly present. Istanbul, by contrast, is clearly high/high: undeniable scale, but also saturated with rivals.

This tells us not just where people live, but where they actually eat — and whether pizza is part of that habit

If we want early wins, we should look at the high-potential regions: they’re developed enough to sustain us, but still open enough for us to stand out.”For the team, the analysis sharpened the shortlist. Istanbul remained the country’s undeniable hub, but its maturity and saturation raised the barrier to entry. By contrast, Izmir combined a vibrant dining culture with very low category penetration, signaling both headroom and manageable competitive pressure. As a result, Izmir was chosen as the pilot city — large enough to matter, open enough to learn, and representative enough to guide further expansion.

Location 3 – Street/Neighborhood

With Turkey validated and Izmir shortlisted, the final question is sharper: Which specific site inside the city deserves investment?

The marketing lead spreads the map across the table. “Five options,” she says. “Two by the waterfront, one in a residential district, one near the mall, one by the university. Each has an argument. The waterfront promises visibility, the mall offers steady traffic, the university brings youth. But which of these factors really translates into sales?”

The analyst overlays a heatmap of food traffic. Bright clusters flare across the city grid. “Look here,” he points out. “Three of our candidates fall inside these high-consumption clusters; two lie far outside. Raw visibility isn’t enough — what matters is where people actually go to eat.”

The marketer leans forward. “So it’s not about how many people pass by, but how much of that movement is food-related.” “That’s the idea,” the analyst replies.

The heatmap analysis divided Izmir’s food traffic into five clusters. The top 20% — the “red zone” — was then broken into four sub-segments, exposing the five most valuable micro-territories.

When the team overlaid competitor locations, the pattern was clear: nearly every major player was already inside these clusters. McDonald’s had 100% of its stores there, Burger King 87%, Domino’s 77%. The leaders were betting heavily on the same high-intensity zones — and Realytics confirmed that two of the client’s proposed sites fell right inside them.

“Some chains deliberately place stores near anchors like McDonald’s or Burger King because those brands guarantee stable flows. Others prefer to stay apart to avoid fighting for the same wallet. Either way, knowing who your neighbors are is part of the revenue equation.”

Co-location isn’t automatically good or bad — it is a strategic choice. What matters is that the patterns are now visible, making the trade-offs easier to evaluate

Finally, the analyst layers in purchasing power: average check size multiplied by traffic volume. “This is where intuition often fails,” he says. “One waterfront site looks attractive on footfall alone, but spend there is low — plenty of people, little margin. By contrast, the mall site combines decent traffic with higher spend per visit. That mix makes it far more valuable than it first appeared.”

The team studies the ranked list. Two sites emerge as strong investments. One is suitable for a cautious pilot. Two are better dropped for now. Street-level analytics prove why evidence matters most where money meets the pavement.

Principles of Data-Driven Decisions

The Izmir case shows a larger truth: strong decisions rest on principles, not impressions.

Combine layers

Demographics without traffic mislead. Traffic without competitor context overstates opportunity. Spending power only matters when paired with footfall. Real insight comes from stacking these layers, not from leaning on one.

Move from comparison to prediction

Early on, we compare: country vs. country, street vs. street. As data grows, we forecast: how will this site perform tomorrow compared with the portfolio?

Scale beats intuition

Field visits and gut feeling still add color, but they cannot match the reach and speed of scalable models. Data doesn’t replace judgment; it anchors it.

From Framework to Practice

Looked at separately, the three levels may feel like isolated steps. Seen together, they form a pipeline of choices.

At the strategic level, leaders determine if the fundamentals of a market make entry worthwhile. In the middle, the team filters those opportunities into a shortlist of regions. At the bottom, strategy turns into tangible commitments — leases signed, stores opened, capital at work.

Each layer asks a different question, draws on different evidence, and shields against a different kind of risk. Sequenced in this way, ambition doesn’t scatter — it flows. Expansion becomes not a gamble, but a process that can be managed, tested, and repeated.

Applied systematically, these principles turn “location, location, location” from a slogan into a method

Rethinking “Location, Location, Location”

For decades, the phrase was repeated more than explained. Geography seemed to be everything, yet no one said how to choose.

Today, the mantra survives, but its meaning has shifted. Country, region, street — each one a decision, each one a risk, each one a discipline of its own.

The lesson for leaders is blunt. Instinct has a place. But instinct alone is too costly. Expansion can be structured, tested, and repeated — a process that turns ambition into measurable results.

“Location, location, location” still matters. And now it matters because we finally have the tools to make each location the right one.

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