In Mexico, convenience stores—known as tienditas de la esquina—are more than just quick stops. They’re essential hubs for groceries, bill payments, and community connections. These small-format retailers provide essential goods and services, especially in neighborhoods where supermarkets are scarce or  expensive. With extended hours, local trust, and a deep understanding of their clientele, convenience stores have become an integral part of Mexico’s cultural and economic landscape.

For businesses trying to reach these essential retailers, visibility is key. That’s where the partnership between dataplor and Linnda comes in. By combining dataplor’s global location intelligence with Linnda’s intuitive platform, companies now have the tools to find, assess, and act on insights related to Mexico’s vast independent convenience store market.

Beyond the Chains: A Fragmented Landscape 

When people think about convenience stores in Mexico, the first names that come to mind are OXXO and 7-Eleven. But beneath the surface of these high-profile brands lies a vast, fragmented ecosystem of independent retailers—and the numbers speak for themselves.

According to dataplor’s POI database, there are 179,755 convenience stores across Mexico. Surprisingly, 137,682 of them—over 76.6%—are independently owned and operated, not affiliated with any national or regional chain.

That means three out of every four convenience stores in Mexico fall under the radar of traditional data sources, which typically emphasize only major brands.

This fragmentation makes it difficult for brands, logistics providers, and retailers to truly understand market saturation, identify growth opportunities, or reach everyday consumers. Independent stores may not show up on search engines, location APIs, or basic mapping tools—making them invisible to many data platforms.

Why This Matters

• Consumer Access: Independent stores often serve as critical access points for groceries, prepaid mobile plans, and basic household goods in both urban and rural areas.
• Expansion Strategy: For businesses looking to expand product distribution or evaluate retail footprints, relying on chain data alone paints an incomplete picture.
• Data Visibility Gap: These “hidden” businesses and POIs are not just statistical blind spots—they’re missed opportunities.

That’s why dataplor’s approach to building and maintaining accurate POI data across all of Mexico’s municipalities, including remote, underserved, and informal areas, is a game-changer for companies that depend on accurate, real-world visibility into convenience stores and retail. 

Analysis Results: Independent Stores Dominate Even in Metro Hubs

To  demonstrate the depth of dataplor’s coverage, we conducted an in-depth analysis of convenience store distribution across several of Mexico’s largest metropolitan areas. The results confirmed a clear trend: independent convenience stores dominate the landscape, even in highly urbanized regions.

By leveraging dataplor’s robust location intelligence, we identified tens of thousands of active convenience stores across cities like Guadalajara, León, and the greater Mexico City metro area. Within each, a significant majority are independently owned and operated, reinforcing the importance of comprehensive POI coverage that extends beyond national chains. These findings not only underscore the depth and accuracy of dataplor’s dataset, but also highlight the critical need for visibility into the “hidden majority” of retail outlets that serve as vital economic and cultural hubs in their communities.

The Solution: dataplor + Linnda for Smarter CPG Distribution

As this analysis shows, even in Mexico’s most densely populated and economically dynamic metro areas, independent convenience stores far outnumber their chain counterparts. These small, often informal retailers are essential to the daily lives of millions, yet they remain largely invisible to conventional data providers.

That’s where dataplor makes the difference. With meticulously verified POI data spanning every municipality in Mexico, dataplor brings clarity to the fragmented retail landscape, unlocking insights that are critical for market expansion, competitive analysis, and strategic planning. In a country where over three-quarters of convenience stores are independently owned, having visibility into the full ecosystem isn’t just helpful—it’s essential.

Through our strategic partnership with Linnda, these insights are now more accessible and actionable than ever. Linnda’s powerful platform transforms dataplor’s verified location data into dynamic, easy-to-use insights that help CPG wholesalers, distributors, and field teams make smarter, faster decisions.

Whether it’s optimizing sales routes, identifying untapped independent stores, or pinpointing high-potential clusters by municipality, Linnda enables users to visualize and activate dataplor’s comprehensive dataset directly within their workflows. For companies selling into Mexico’s fragmented and hyperlocal retail ecosystem, this partnership eliminates guesswork and empowers precision.

With dataplor + Linnda, CPG teams can bridge the gap between store coverage and sales execution, expanding their footprint with confidence.

To learn more, contact us today at contact@dataplor.com or jose@linnda.co.

Foot traffic data is no longer just a North American product, it’s a global imperative. As businesses expand into new markets and adapt to shifting consumer behaviors worldwide, the need for precise, GDPR-compliant, privacy-first mobility data has never been more urgent.

To meet this demand, dataplor is expanding its mobility product globally, bringing timely, POI-level foot traffic insights to countries around the world. From major retail hubs to high-growth emerging markets, companies can now access the same caliber of mobility intelligence internationally that they’ve come to rely on in the U.S., Canada, and Mexico.

What is Global Mobility Data and Why Now?

Mobility data, also known as foot traffic data, measures when and how many people visit a specific place. Combined with dataplor’s point-of-interest (POI) data, this reveals where consumers go, how often, when, and in what context. For multinational businesses, this type of intelligence is foundational to making strategic decisions around expansion, marketing, investment, and operations.

Global enterprises have long grappled with fragmented and incomplete location intelligence solutions, with many providers offering only partial visibility or overlooking emerging markets entirely. Even when data is available, it often lacks the precision needed to tie foot traffic to specific points of interest, limiting its usefulness. Compounding these issues are growing privacy concerns, as many existing solutions fail to meet compliance standards like GDPR or rely on opaque data collection practices.

dataplor’s global mobility product directly addresses these gaps, offering monthly, GDPR-compliant data across both developed and underserved regions, with precise attribution down to individual POIs. What sets our solution apart is its ability to deliver:

• Granular POI-Level Tracking: Understand exactly which store, venue, or site is being visited, not just general zones or districts.
• Expanded Global Reach: Access mobility insights in regions that were previously underserved, including key growth markets.
• Monthly Updates: Stay current with data that’s refreshed every month, rather than relying on outdated quarterly snapshots.
• Privacy-First Design: Our data is anonymized, aggregated, and compliant with all relevant global privacy regulations.

Combining POI and mobility data, dataplor eliminates the need for patchwork solutions, giving global enterprises a unified, dependable source for location intelligence.

Global Applications, Real-World Impact

The use cases for mobility data are expanding, and industries worldwide can tap into dataplor’s insights to power smarter decisions:

Retailers and quick-service restaurants can pinpoint high-traffic areas, evaluate market potential, and strategically expand into new regions. Consumer packaged goods companies can optimize distribution by targeting stores with proven footfall. Tourism boards and hospitality groups can analyze visitor patterns through major attractions and travel corridors, fine-tuning everything from marketing to operations.

Meanwhile, city planners and infrastructure leaders can use real-world movement data to design more efficient, accessible urban spaces. Real estate professionals, from developers to investors, can assess property value and neighborhood potential through the lens of actual consumer activity.

The World is Moving. We’re Tracking It

As global connectivity deepens, businesses need more than static maps and quarterly reports. They need a consistent, ethical, and scalable way to understand real-world human movement, no matter the market.

Powered by anonymized mobile location signals, verified POI data, and a privacy-first foundation that meets global standards like GDPR, dataplor’s global mobility product delivers the clarity and confidence today’s businesses demand.

Whether you’re optimizing a retail footprint in Southeast Asia, tracking tourism patterns across Europe, or assessing real estate opportunities in Latin America, dataplor provides the insights to help you move forward.

Want to see what global foot traffic looks like in action? Explore our latest tourist attraction report or request a sample to get started.

After years of closed borders and empty landmarks, the world is moving again. From the base of the Great Pyramid to the halls of the Louvre, tourism foot traffic is not only back, it’s shifting in ways that tell us more than just where travelers are going. It reveals how global tourism is evolving.

At dataplor, we use numbers to surface patterns, uncover behaviors, and guide more intelligent decision-making. That’s why we’ve built a foot traffic product rooted in trillions of movement data points. With this latest global tourism dataset, we’ve uncovered meaningful patterns, anomalies, and shifts that define the return of tourism from 2021 through 2024, and point to what 2025 will bring.

The Data That Tells the Story

In 2021, as travel bans slowly lifted, tourism began to crawl back. Places like the Louvre saw modest foot traffic (roughly 2.8 million visitors that year), while open-air icons like the Sydney Opera House and Tokyo Disneyland hovered around 6 million.

By 2022, the Colosseum in Rome saw foot traffic soar from over 1.5 million in 2021 to over 9 million, a year-over-year (YoY) growth of over 400%. The Taj Mahal, Christ the Redeemer, and Petra, all constrained by access and local policy, showed mild YoY growth of less than 50%. But the full comeback didn’t arrive until 2023, when global travel surged past many pre-pandemic benchmarks. Tokyo Disney saw an estimated 13+ million visits based on aggregated mobility patterns. The Sydney Opera House hosted over 10 million. The Great Pyramid at Giza crossed 7 million, reclaiming its place among the most-visited heritage sites in the world.

Beyond the Peaks: What the Footprints Reveal

In 2024, travel demand has accelerated into the spring months. Compared to 2023, global foot traffic at top tourist sites rose by more than 11% in March alone, reflecting a growing preference for earlier trips, driven by favorable pricing and a desire to avoid peak summer crowds.

Meanwhile, the traditional summer hotspots remain dominant. The Colosseum continues to see over 1 million visitors in July and August alone. But even here, we see emerging constraints: extreme heat, labor strikes, and local policy interventions are reshaping not just when people travel, but how destinations manage that demand.

In Rome, for example, the introduction of the “Moon over the Colosseum” night tours in 2023 successfully redirected some tourist traffic to evening hours, helping to spread out demand and slightly boost October’s overall visitation. In Peru, a 23-day rail protest in early 2023 reduced Machu Picchu’s annual traffic by nearly 150,000, a reminder of how even short-term disruptions can erase months of tourism volume.

A New Tourism Calendar

Tourism is increasingly shaped by micro-events, some celebratory, some disruptive. And dataplor’s data captures these trends, offering timely visibility into shifting travel patterns.

• The Sydney Opera House marked its 50th anniversary with a yearlong celebration that began in October 2022 and concluded in October 2023, drawing a rare peak in visitor numbers during Australia’s typically quieter months.
• Strikes in Paris reduced March 2023 traffic at the Louvre.
• Across all sites in our dataset, October and December 2024 each saw more than 5.4 million visits, surpassing June. The trend points to extended holiday travel and growing interest in off-peak experiences driven by cooler weather, cultural events, and pricing advantages.

Whether driven by weather, politics, or pop culture, these moments ripple outward, impacting bookings, campaigns, and even regional economies.

What 2025 Might Look Like

Using four years of consistent seasonal benchmarks and trends, dataplor projects a continued shift toward earlier travel planning and spring surges.

Based on recent trends, 2025’s most visited sites are expected to mirror past performance, with the top five being:

• Tokyo Disneyland
• Sydney Opera House
• The Colosseum
• Great Pyramid at Giza
• The Louvre

These landmarks show durable interest, seasonal consistency, and the ability to absorb disruptions. Meanwhile, sites like Petra and Machu Picchu, though smaller in raw volume, continue to show strong seasonality tied to weather and limited access, with peak demand condensing around narrow windows.

Another variable shaping 2025 tourism trends may come from beyond the travel industry itself. Trade tensions, shifting visa policies, and regional tariffs, especially involving China, the U.S., and the EU, could reshape cross-border travel flows. We’ve already seen how government actions directly affect tourism patterns: in Peru, anti-government protests in early 2023 led to the closure of Machu Picchu for nearly a month, resulting in a measurable drop in foot traffic. In France, nationwide strikes over pension reform triggered a temporary decline in March visitation to the Louvre. While dataplor doesn’t predict policy, our foot traffic data shows how quickly decisions at the top, whether diplomatic or domestic, can ripple through global movement. As 2025 approaches, we’ll be watching how geopolitics continue to shape where the world travels.

Why This Matters

Tourism isn’t just a consumer preference; it’s an infrastructure challenge, an economic driver, and a cultural signal. Cities, brands, and agencies all depend on accurate, timely data to make high-stakes decisions about pricing, staffing, events, and policy.

dataplor’s foot traffic product delivers:

• Verified POI-level insights across continents
• Month-over-month comparisons for multi-year analysis
• Granular visibility into seasonal and disruption-based shifts

From managing overflow crowds in Rome to launching early spring promotions in Peru, our data equips decision-makers with the tools to adapt in real time, and stay ahead of what’s next.

dataplor’s mobility insights illuminate that story, helping you respond to today and plan for tomorrow. Want to learn more about how our global foot traffic product can inform your business strategy? Reach out for a mobility sample.

Did you know that almost 85% of retail sales still happen in-store despite the rise of e-commerce? 

There’s no question that foot traffic analysis is key to businesses planning expansion. Understanding how people move through and interact with physical spaces gives you powerful insights that can make or break a new location’s success.

So what is foot traffic, you might ask?

Foot traffic refers to the number of customers who enter a specific location over a given time period. By collecting and analyzing this data, you can gain valuable insights into customer behavior, peak hours, and potential revenue opportunities. This is critical when identifying potential expansion locations and minimizing risk.

In this article, we’ll review how foot traffic data drives expansion decisions, key considerations when analyzing foot traffic, and how dataplor’s comprehensive location intelligence can power your expansion strategy.

Foot Traffic Analysis for Expansion: Key Considerations

Before investing in a new location, understanding the existing foot traffic within that area is a must. Proper foot traffic analysis combines several key considerations to give you the full picture.

Identifying High-Traffic Areas

When analyzing foot traffic, volume alone isn’t enough. Businesses need to evaluate the quality of foot traffic and how it matches their target audience. 

For example, a luxury retailer might want areas with fewer but higher spending visitors over areas with high volume but lower spend.

To find high-traffic areas that match your business needs, consider:

• Daily and hourly foot traffic variations
• Seasonal patterns and trends
• Dwell time and engagement levels

Analyzing Nearby Businesses

Understanding the business ecosystem around potential expansion locations gives critical context to foot traffic data. 

A restaurant might benefit from being near entertainment venues that generate evening foot traffic. A coffee shop might thrive near office buildings with morning commuters.

When analyzing foot traffic around existing businesses, consider:

• Complementary businesses that drive shared customers
• Competitive density and positioning
• Anchor tenants that generate significant foot traffic
• Businesses with similar target audience

Evaluating Accessibility and Infrastructure

Even high foot traffic areas can underperform if they’re hard to reach. 

Foot traffic and location data about transportation options, parking availability, and pedestrian-friendly features give you critical context for foot traffic trends.

When evaluating accessibility through foot traffic data:

• Analyze how pedestrians naturally flow through an area
• Examine public transport proximity and usage
• Assess vehicle traffic patterns and parking availability
• Consider pedestrian infrastructure quality and safety

Stores on pedestrian-friendly streets often see more foot traffic than similar stores on car-dominated or traffic-heavy streets.

Leveraging Foot Traffic Data for Strategic Expansion Decisions

Now that you have a good understanding of the foot traffic considerations, here’s how you can apply the data collected to inform your expansion decisions and marketing efforts.

Market Gap Analysis

Analyzing foot traffic patterns reveals where people go—but also where they don’t go, and why.

By analyzing foot traffic across broader areas, you can find underserved markets with potential and gain valuable insights on the physical location worth considering.

For example, a retailer might use foot traffic data to find areas with high foot traffic but limited shopping options in their category. This gap is an opportunity to enter a market with established foot traffic and less competition with a better understanding of customer behavior.

Market gap analysis using foot traffic data should:

• Compare foot traffic density to existing service density
• Find areas where customers travel further for services
• Measure foot traffic leakage to other areas
• Assess campaign performance using store visits as a metric 

Competitor Analysis

Understanding how competitors perform at their locations is like an undiscovered gold mine for your expansion plans. By analyzing foot traffic at competitor locations, you can find models to copy and opportunities to differentiate.

Effective competitor analysis through foot traffic data involves:

• Comparing foot traffic volumes across competitor locations
• Analyzing peak hours and seasonal trends
• Evaluating customer engagement and dwell time
• Identifying underperforming competitor locations

Site Selection

The ultimate application of foot traffic analysis is to find locations for new stores or facilities. 

By combining foot traffic data with other location intelligence, you can calculate foot traffic potential and project performance for specific sites.

Effective site selection using foot traffic data should:

• Analyze historical foot traffic trends in the area
• Compare site performance to successful existing locations
• Project foot traffic based on nearby development plans
• Evaluate the impact of nearby store locations on each other

Combining Data Sources for a Holistic View

Foot traffic data is most powerful when combined with other data sources, like Point of Interest (POI) data, to get a complete picture.

For example, understanding foot traffic peaks around lunchtime near a cluster of office buildings differs from foot traffic at night near entertainment venues.

When combining foot traffic data with POI data, you can:

• Find which business types drive foot traffic in an area
• Understand the relationship between business mix and visitor patterns
• See symbiotic relationships between certain business types
• Project how new developments will impact existing foot traffic patterns
  

Internal business data takes foot traffic analysis to the next level. By comparing foot traffic trends to store performance metrics, you can find your ideal foot traffic profile and target similar patterns in expansion locations.

For instance, a quick-service restaurant chain might find that locations with steady foot traffic all day perform better than those with big peaks and troughs, even if the total foot traffic is the same. This would guide them to locations with more consistent traffic patterns.

Mobility location data adds another layer of insight to help you understand the customer’s journey before and after visiting a location. This data shows traffic patterns across the wider area, not just at the storefront.

dataplor’s POI Data: Fueling Expansion Strategies

dataplor’s location intelligence has the data you need to make informed growth decisions. 

With coverage across over 250 countries and territories, dataplor provides high-quality data on millions of points of interest worldwide.

What sets dataplor apart is our focus on data accuracy and depth. While many providers offer basic location data, dataplor provides:

• Verified and up-to-date information on millions of locations
• Comprehensive business attributes (hours, categories, contact info)
• Global coverage with consistent data schema
• Privacy-compliant mobility data
• Customizable data solutions for your business needs

This dataset allows you to use foot traffic data for growth planning. For example, a retail business expanding internationally can use dataplor’s POI data with foot traffic analysis to:

• Identify promising markets based on competitive density
• Analyze foot traffic around similar businesses
• Evaluate site accessibility and infrastructure
• Understand local consumer behavior and preferences

By combining dataplor’s POI data with foot traffic insights, your business has a powerful tool to identify trends and promote growth planning. This minimizes risk and maximizes success in new markets.

Expand Your Horizons with Foot Traffic Data

Foot traffic analytics has moved from manual counting to advanced data science that drives business decisions. By tracking foot traffic data across a broader geographical area and targeted locations, you can identify opportunities, reduce risk, and optimize your growth strategy.

The best growth strategies combine data sources—foot traffic patterns, POI data, demographic data, and internal business metrics—to give a complete view of potential locations. 

This goes beyond mere gut feel and into data-driven decision-making for maximum success. With dataplor’s global POI data and location intelligence, you can expand into new markets with confidence.

Ready to power your strategy with location data? Contact dataplor today to find out how our location intelligence capabilities can boost your business and help you find the perfect location for continued growth.

Retail success goes beyond having a great product. It also relies on getting customers through the door. But how do retailers track foot traffic trends, identify patterns, and measure foot traffic in a way that drives insights? 

The answer is foot traffic analytics, a data-driven approach to understanding customer behavior in physical locations.

Foot traffic analysis is the process of examining external, aggregated foot traffic data to see how many visitors visit a specific location and how these patterns change over time. This data helps businesses optimize marketing, site selection, and the overall customer experience.

Studies show that over 80% of retail transactions still happen in physical stores, so it’s crucial to track foot traffic and analyze patterns. 

In this guide, we’ll look at the importance of foot traffic analytics, how businesses can use it to grow, and what to consider when choosing a foot traffic data provider like dataplor.

The Retail Landscape: Challenges and Opportunities

The retail world is undergoing a seismic shift. Traditional brick-and-mortar stores are battling on multiple fronts:

• Unprecedented competition from e-commerce
• Rapidly changing consumer behavior
• Economic uncertainty
• Technological disruption

Today, physical stores must compete not only with one another but also with digital marketplaces offering unmatched convenience and personalization.

Challenges for retailers include:

• Changing Consumer Behavior: Shoppers no longer visit stores just to transact. They expect unique in-store experiences, seamless online-to-offline integration, and personalization. Retailers need foot traffic data to understand customer behavior and adjust their strategy accordingly.
  
• Site Selection and Expansion Risks: Choosing the wrong retail location can be costly. Retailers need to analyze foot traffic patterns and demographic data to ensure they invest in the best locations that attract more visitors.
  
• Competition and Market Saturation: With so many businesses vying for the same customers, understanding competitive foot traffic trends is key. Tracking foot traffic near competitor locations can give insights into market gaps and opportunities.

Retailers who use location intelligence and external foot traffic analytics can get a competitive edge by:

• Identifying ideal locations for new retail stores
• Refining marketing campaigns based on real-time traffic data
• Configuring store layouts to get more customer visits
• Using foot traffic patterns to improve operations

The Importance of Foot Traffic Analytics for Retailers

Foot traffic analysis is more than just counting how many visitors walk into a store. It gives a complete view of customer movement and engagement so businesses can make data-driven decisions.

Types of foot traffic data include:

• Aggregated Pedestrian Counts: Measures overall foot traffic trends in and around a specific location.
• Competitor Foot Traffic Data: Helps businesses understand consumer behavior at rival locations.
• Trends Over Time: This includes tracking seasonal fluctuations, marketing campaign impact, and long-term visitation trends.

Why do retailers need this data?

• High foot traffic = more customers. Footfall data helps businesses predict revenue.
• Consistent traffic = loyal customers. Patterns show brand loyalty and customer engagement.
• Sudden traffic changes = market shifts. A decline in foot traffic can mean an economic downturn or poor marketing efforts.

Strategic Applications: Turning Foot Traffic into Retail Advantage

Retailers should combine foot traffic data with demographic data, point of interest (POI) insights, and market data for the best advantage to their retail strategy.

• Optimizing Site Selection: Choosing the right store location is key to success. Analyzing foot traffic and mobility data can show which areas have high commercial potential and steady customer visits. Retailers can avoid costly leasing mistakes by identifying higher foot traffic zones.
  
• Hyperlocal Marketing: Retailers can use foot traffic data to tailor their marketing. By studying mobile location data, they can launch promotions when traffic is highest, boosting conversion rates.
  
• Competitive Intelligence: Using foot traffic analysis, retailers can see competitors’ performance. If a nearby store sees a spike in customer data, it may indicate a successful marketing campaign or product launch from which businesses can learn.
  
• Performance Evaluation: Measuring foot traffic data before and after an event, sale, or ad campaign provides valuable insights. Retailers can analyze foot traffic to adjust future marketing and operations.

Building a Holistic Retail Strategy

Retailers today face a complex landscape where estimating foot traffic isn’t enough. To stay competitive, they must combine accurate foot traffic analytics with a broader set of data-driven insights to create a retail strategy. 

By using multiple data sources—including POI data, sales performance metrics, and market trends—retailers can get a 360-degree view of customer behavior and optimize store operations.

Here’s how retailers can build a holistic retail strategy by understanding foot traffic so they can better target customers and gain valuable insights:

 1. Leveraging POI Data

A physical store doesn’t operate in isolation—its surroundings play a big role in driving customer visits. Point of interest (POI) data shows nearby businesses, attractions, transit stations, and landmarks that impact foot traffic trends.

How POI data helps: 

• High-Traffic Locations: Stores near restaurants, gyms, or shopping malls will have more foot traffic than standalone locations.
• Partnership and Collaboration: Knowing nearby businesses can help retailers explore cross-promotional opportunities (e.g. a clothing store offering discounts to gym members).
• Competitor Analysis: POI data helps retailers see how competitor locations impact consumer behavior and if opening a store near a competitor would be a wise decision.

2. Aligning Sales Data with Foot Traffic Trends

Tracking foot traffic patterns is valuable, but businesses must also correlate these numbers with sales performance. A location with high visitor numbers but low conversion rates may indicate issues with store layout, pricing, or product selection.

How aligning sales data helps: 

• Conversion Rate Optimization: By comparing foot traffic data with sales data, retailers can see what percentage of visitors buy and adjust their stores accordingly.
• Product Placement: If an area of the store has high foot traffic but low sales, product placement or in-store promotions may need to be adjusted.
• Traffic vs. Revenue Gaps: If a store has consistent foot traffic but declining sales, pricing, customer service, or inventory could likely be the issue.

 3. Benchmarking Against Market Trends and Competitors

External factors like economic trends, consumer spending habits, and competitor performance all impact success. To develop a holistic strategy, businesses must benchmark their foot traffic data against industry trends and competitor insights.

How benchmarking helps:  

• Seasonal Trends: Comparing year-over-year foot traffic data helps businesses plan for peak shopping periods, staffing, and inventory adjustments.
• Competitor Analysis: Monitoring foot traffic at competitor locations will show which stores are getting more customers and why.
• Adapting to Market Changes: If a new shopping mall opens nearby and diverts foot traffic, businesses can adjust their marketing strategy to retain customers.

Vetting the Right Foot Traffic Analytics Provider

Choosing the right foot traffic data provider is key. Retailers should consider:

• Data Reliability: How accurate and reliable is the foot traffic data?
• Geographic Coverage: Can the provider track specific locations on a global scale?
• Privacy Compliance: Does the data comply with data security laws?
• Customer Support: Can businesses get help interpreting location data?

A quality provider offers reliable, privacy-first foot traffic data that businesses can trust to make informed decisions.

Transform Your Retail Operations with Foot Traffic Analytics

By using foot traffic analytics, you can:

• Find the best places to expand in the physical world
• Refine marketing campaigns with traffic data
• Get a competitive edge by studying customer behavior
• Optimize store layouts and operations 
• Make strategic decisions with location intelligence

To succeed in today’s retail environment, you need to use foot traffic data to make better, data-driven decisions. 

Are you ready to get foot traffic data from a trusted provider to improve your store’s performance and success? Learn more about dataplor today, and contact us to start unlocking in-depth foot traffic insights.