The dataplor team is proud to announce the launch of its mobility product, which enables businesses to understand how people interact with specific locations. By combining dataplor’s extensive point-of-interest (POI) data with footfall counts, companies can utilize actionable location intelligence. This data gives organizations a competitive edge by highlighting real-world consumer behaviors.

The Problem with Existing Data Sources

Many businesses rely on demographic or static data that fails to capture consumers’ dynamic behavior. In-house data collection can be costly and inconsistent and may not include in-depth foot traffic data that delivers better insights. 

dataplor’s mobility product tackles these issues by showcasing:

• Market Potential: Ascertain a location’s popularity and activity patterns.
• Actionable Insights: Assess economic trends, evolving customer interests, and competitors’ performance.
• Changing Patterns: Develop data-driven forecasts and action plans for untapped markets.

These insights empower businesses to uncover key learnings beyond merely a location, including how individuals and customers engage with a specific place.

What Sets dataplor’s Mobility Product Apart

dataplor’s mobility product operates on a foundation of 3.9 trillion movement data points. Behind its comprehensive location intelligence and in-depth insight offerings, dataplor also upholds strict privacy standards and secure data practices.

Comprehensive Coverage

dataplor delivers monthly refreshed and strategic mobility data to ensure businesses always have the most relevant information. Currently, dataplor’s mobility product covers urban and rural areas in the United States, Mexico, and Canada, with plans to expand coverage to 40 countries by late 2025. dataplor enables businesses to streamline operations with a single vendor for high-quality, global POI data coverage and location intelligence.

Granular Insights

Rather than relying on broad demographic data, dataplor’s mobility data offers precise information down to a specific POI. This level of detail creates deeper and more impactful use cases for companies across industries.

Privacy-First Approach

Privacy is a top priority for dataplor. Our data is aggregated, anonymized, and fully GDPR-compliant, without collecting or using any personally identifiable information (Pll). This ensures ethical and secure data practices.

How Industries Can Leverage Foot Traffic Data

Businesses can optimize their decision-making using dataplor’s mobility data paired with the most comprehensive POI data for the U.S., Mexico and Canada. Industries that can benefit from these insights include:

• Retail: Identify optimal locations for new stores and customize inventory using foot traffic patterns.
• Consumer Packaged Goods: Track consumer interactions with retail outlets to inform product placement and promotions.
• Marketing: Enhance targeting strategies by knowing where and when consumers are active.
• Real Estate: Evaluate market trends and property performance to guide investments and developments.
• Urban Planning and City Governments: Optimize public spaces, transportation systems, and resource allocation to meet community needs.
• Quick-Service Restaurants: Identify optimal locations, evaluate existing location performance, and analyze customer behavior. 

dataplor recently analyzed foot traffic data for major fast-food restaurants across the United States, delivering valuable insights into customer movement and restaurant performance. 

Foot Traffic Insights in the Fast-Food Industry

By understanding foot traffic patterns, fast-food chains can enhance their market presence and customer engagement. Adjusting for the number of restaurant locations, dataplor found the following foot traffic trends in our analysis:

• Wendy’s was the most popular nationally, appearing in the “Top 5” in foot traffic 51 times, followed by Raising Cane’s at 39.
• In the Southeast, Wendy’s, McDonald’s, and Subway tied for the most ubiquitous, based on how many times a given restaurant ranked in the “Top 5” for the total number of stores in a state.
• In-N-Out Burger achieved the top ranking for foot traffic in five states in the West but is tied for fourth place overall for foot traffic in the region.
• In the Southwest, In-N-Out Burger was most likely to be ranked first for foot traffic in a given state, while Raising Cane’s took that title in the Northeast.

Restaurants can utilize this kind of data to identify optimal areas to open new locations, evaluate the performance of existing sites, and tailor menu offerings and promotions based on customer behavior. The fast-food chain analysis is just one example of how businesses can leverage dataplor’s insights to optimize customer interactions.

Take the First Step Toward Smarter Growth

dataplor’s mobility product revolutionizes businesses’ understanding of consumer behavior. By showcasing market potential, revealing actionable insights, and supporting data-driven forecasts, it enables companies to make smarter decisions and optimize their growth against competitors. 

Interested in leveraging mobility data for location intelligence? Learn what it is and how other businesses are using it in our webinar on February 26, from 10:00 AM – 10:30 AM PST.

Are you interested in evaluating dataplor’s location intelligence? We offer free data samples so you can confidently choose the right data provider.

Discover how scarcity and regional loyalty drive America’s favorite fast-food brands.

Americans love fast food, but how can we know which offerings are really the most popular? At dataplor, we know it’s the numbers that unlock deep insights. We recently put this to the test by analyzing foot traffic trends among America’s most popular fast-food chains, as part of the launch of our new mobility product. 

Combining extensive point-of-interest (POI) data with footfall counts, our location intelligence product equips businesses with deep insights into consumer interactions with specific locations. The mobility product gives businesses information to help optimize their decision-making using its foundation of 3.9 trillion movement data points.

Our analysis was centered on three questions: 

• Based on how often a restaurant is ranked in the “Top 5” in foot traffic in a given state, which brands seem to be the most popular?
• Based on how often a restaurant is ranked in the “Top 5” for the total number of stores in a given state, which brands are the most ubiquitous?
• Based on how often the restaurant is ranked first for foot traffic in a given state, which brands are the most well-loved?

The results showcased surprising results, answering the question, “Do more locations always equal greater customer loyalty and increased foot traffic?”

Nationwide, Bigger Does Not Always Mean Better

On the national scale, Wendy’s led as the most popular chain in terms of foot traffic, followed by Raising Cane’s, Chick-fil-A, Five Guys, and McDonald’s. McDonald’s and Subway tied as the most widespread chains overall, with Burger King, Wendy’s, Dairy Queen, and Sonic Drive-In rounding out the list. Only two of those most common restaurants (Wendy’s and McDonald’s) are also present in the top five for most foot traffic, suggesting that being everywhere doesn’t mean you’re going to be everyone’s top choice.

So, which brands are winning hearts and stomachs across the nation?

Scarcity may make the stomach grow hungrier. Wendy’s and Raising Cane’s took the top two spots for “most likely to be ranked first for foot traffic in a state” nationwide, followed by In-N-Out Burger, a tie between Chick-fil-A and Culver’s for fourth, and Five Guys in fifth. Yet looking at those brands that rank first in foot traffic in at least one state, only Wendy’s is in the top five nationally for the most locations.

Regional Favorites Roundup

Southeast

Mirroring national trends, Wendy’s led in foot traffic in the Southeast, followed by McDonald’s, Raising Cane’s, Chick-fil-A, and then a tie between Five Guys and Culver’s. And once again, being ubiquitous doesn’t necessarily translate to popularity, with Subway, Burger King, Sonic, and Dairy Queen all appearing on the list for most common stores, yet absent from the top foot traffic rankings.

West

Perhaps unsurprisingly, regional favorite In-N-Out Burger secured a number-one ranking in five Western states for having the highest foot traffic—despite not cracking the top five for total number of stores in any state in the region. Taking a broader view of brands that achieved a top five ranking for foot traffic in at least one Western state, In-N-Out ties for fourth place with fellow burger joint Five Guys, with the top spots belonging to Wendy’s, Chick-fil-A, and Raising Cane’s.

Southwest

Maintaining its western dominance, In-N-Out also stood out as a beloved chain in the Southwest region. It once again achieved the most first-place rankings for foot traffic in a given state, taking the top honor in two of the four states in the region. Interestingly, the list of brands to make the top five for foot traffic in at least one state in the Southwest were: Wendy’s, Raising Cane’s, McDonald’s, Five Guys, In-n-Out, Culver’s, Chick-fil-A, and Freddy’s Frozen Custard and Steakburgers; yet of these, only Wendy’s and McDonald’s ever make the top five for total number of stores in at least one state.

Northeast

Five Guys, founded in Washington, D.C., and Jersey Mikes, native to the Jersey Shore, demonstrated a strong presence in the area close to their origins, ranking second and third in the region in terms of the number of times they crack the top five for total number of stores in a given state. When it comes to overall popularity, Wendy’s, Chick-fil-A, and Five Guys took the top three spots for stores most likely to rank in the top five for foot traffic. But Raising Cane’s emerged as perhaps the most well-loved restaurant, taking the top spot for foot traffic in a whopping six states in the Northeast.

Midwest

Wisconsin-born Culver’s excelled in its home region, showing up in the top five for both number of locations and foot traffic. It’s the second-most likely brand, behind Wendy’s, to be in the top five for foot traffic for states in the region, snagging the number one overall spot for popularity in one state (Ohio).

How Mobility Insights Can Drive Smarter Business Decisions

The fast-food study uncovered compelling patterns regarding consumer behavior that highlight what genuinely resonates with customers.

• The Scarcity Factor: Chains like Raising Cane’s and In-N-Out demonstrate how there’s not always a correlation between a restaurant’s footprint and popularity. Even with a smaller geographic footprint, these restaurants showcased high foot traffic, suggesting strong customer loyalty.
• The Power of Regional Loyalty: Local favorites took hold in their home regions. Culver’s, rooted in the Midwest, Five Guys, with origins in the Northeast, and In-n-Out in the West all indicate how regional ties help brands outperform more prominent competitors.
• Popularity Isn’t Always About Numbers: A larger presence doesn’t always translate to greater popularity. Consumers often prioritize regional connection and brand identity over convenience or location count.

dataplor’s mobility product offers actionable data for businesses across industries. This fast-food analysis revealed how businesses can use location intelligence to optimize marketing strategies with tailored campaigns for regional preferences, identify gaps in high-loyalty regions to explore new markets, and understand consumer behavior to inform store placement and product offerings.

Learn more about our mobility product and how your business could benefit from these insights in our mobility release announcement.

In today’s rapidly evolving business environment, understanding customer behavior and preferences is no longer a luxury, but a necessity. According to Forbes, 80% of all data contains a geospatial component, making location analytics and business intelligence crucial for businesses to gain insights into customer patterns.

Source: Forbes

Businesses are not only competing on the products and services they offer, but also on their ability to optimize customer experiences based on data-driven insights.

The rise of location analytics is transforming how you engage with your target markets, providing real-time insights into customer preferences, demographics, and spatial patterns.

Location analytics empowers you to uncover hidden trends using geospatial data and POI data, enabling data-driven decision-making. With dataplor’s comprehensive POI datasets, you can now dive deeper into market demographics, identify new opportunities, and gain actionable insights for planning marketing strategies, site selection, and resource allocation.

In this article, we’ll review how POI data and location analytics can unlock valuable insights into your target market. We’ll cover the key benefits of location-based data, steps to effectively leverage location intelligence, and real-world case studies showcasing its success.

What is Location Analytics?

It is the process of analyzing geospatial data to gain a deeper understanding of customer behavior, preferences, and patterns related to physical locations. By using location data combined with advanced GIS (Geographic Information System) technologies, you can gain valuable insights into how your target audience interacts with different geographical areas.

These analytics solutions can help you make informed decisions about where to expand, how to tailor your market strategies, and which locations offer the best opportunities for growth. Additionally, analytics platforms offer integrations with various business tools to streamline data-driven decision-making.

How It Works

Location analytics leverages Point-of-Interest (POI) data, which contains detailed information about specific places, such as retail stores, landmarks, and service providers. 

With POI data, you can uncover trends by analyzing the spatial relationships between locations, identifying high-potential areas for growth, and understanding the demographic makeup of different regions. This can help you optimize your marketing campaigns and strategically decide on site selection and resource allocation.

For example, spatial analytics and visualization tools can help you map out how different locations impact profitability, allowing you to make more data-driven decisions about your marketing strategies. Whether you’re identifying prime areas for new store locations or assessing proximity to competitors, location analytics provides the tools you’ll need to succeed in today’s competitive market.

Benefits of Location Analytics

Location analytics can offer a powerful set of tools to make strategic decisions. By analyzing geospatial data and leveraging location intelligence, you can improve operational efficiency. These functionalities can help you fine-tune your business intelligence and make informed decisions. 

Here are some key benefits:

1. Spot New Market Opportunities

Using spatial analysis tools, you can uncover high-potential target markets. By identifying new locations with the right geographical data, you can increase the chances of success for your business initiatives.

Boston Consulting Group reports that retail and e-commerce businesses reported an 11% to 15% increase in average online cart size by utilizing location intelligence to deliver more personalized and timely promotions. Additionally, these companies were able to reduce last-mile delivery costs by 3% to 4% through the use of geospatial data to optimize logistics and delivery routes.

2. Outpace Competitors

Location analytics provides insights into competitor locations and operations. By understanding the proximity of competitors and the surrounding locations, you can position yourself strategically and differentiate your offerings.

3. Make Smarter Decisions with Data

Location data forms the backbone of data-driven decision-making. Whether it’s optimizing site selection or effectively allocating resources, you can use location analytics to ensure that every move is backed by data, improving both operational efficiency and profitability.

Understanding Areas of Interest with POI Data

What is POI Data?

Point-of-Interest (POI) data is a comprehensive tool that includes detailed information about various physical locations such as restaurants, stores, landmarks, and more. Each POI represents a specific location that holds value to businesses or consumers.

By using data visualization tools and interactive analytics platforms, you can visualize segmentation of customer groups to make more data-driven decisions.

This data contains essential attributes such as geographical coordinates, demographic information, business hours, and categories (such as retail, healthcare, or entertainment).

POI data can help you empower your business in several impactful ways:

1. Identify Local Patterns

You can analyze POI data to detect trends in specific locations, such as retail centers or popular landmarks. These insights help you optimize your location strategy by understanding local market trends and consumer behavior.

2. Find High-Value Markets

Using location-based insights, you can identify areas with a high concentration of foot traffic. This allows you to focus your efforts on new locations that offer strong potential for growth and profitability.

3. Understand Competitor Landscape

By examining POI data, you can analyze competitor proximity and identify complementary businesses nearby. This insight helps craft strategies that differentiate your offerings and increase your competitiveness.

4. Uncover Hidden Customer Trends

With POI data, you can reveal hidden trends in customer preferences and behaviors across various regions. These insights let you tailor your marketing campaigns to specific customer needs, optimizing both engagement and success in key markets.

Putting Location Analytics into Action

By harnessing geospatial data and powerful location intelligence tools, you can make strategic decisions that drive growth and profitability. These functionalities are crucial for managing business data efficiently and improving overall business intelligence.

To unlock the potential of location analytics, follow these simple steps using POI data.

1. Define Your Audience and Focus Areas

Start by clearly defining your target audience and identifying areas of interest where they are most likely to be found. Understanding your customer’s demographic profile and geographic preferences allows you to focus on locations with the greatest potential.

2. Dive into POI Data

Access POI datasets to explore a wealth of location-based insights. These datasets provide valuable information about various locations, including restaurants, landmarks, and retail stores, helping you pinpoint critical opportunities.

3. Analyze Customer Behavior

Use location analytics tools to analyze customer behavior near POIs. By visualizing spatial relationships, you can detect trends, track patterns, and understand how your customers interact with certain areas to obtain detailed information for strategic planning.

4. Study Your Competitive Landscape

Analyze your competitor’s proximity and complementary businesses with POI data to craft a strategy that sets you apart. Knowing where your competitors are and who you can partner up with allows you to tailor your approach to maximize competitive advantage.

5. Make Smarter Business Decisions

Leverage the insights gained from POI data to make data-driven decisions for marketing campaigns, site selection, and resource allocation. This approach lets you optimize your operations, maximize profitability, and ensure you’re targeting the right customers in the right places.

Case Studies & Success Stories

dataplor’s POI data and location analytics have empowered various companies in different industries to achieve remarkable success. We’ll explore some use cases that illustrate how these organizations have leveraged our geospatial data to tackle challenges, implement effective solutions, and discover new growth opportunities.

1. FLO^®: Expanding EV Charging Coverage

FLO^®, a leading electric vehicle (EV) charging network across North America, faced challenges with outdated and inconsistent data, particularly in bilingual regions. 

By switching to dataplor’s POI data, FLO^® was able to increase its dataset by 65% in benchmark areas, which allowed them to identify previously overlooked opportunities. 

With dataplor’s accurate and regularly updated POI data, FLO^® was able to refine their machine-learning models to predict charger utilization, enhance their sales team’s ability to target potential hosts for charges, and strategically place EV chargers in high-demand areas. This led to a significant improvement in the accuracy of their predictions and increased growth across their network.

2. Wolt: Boosting Market Expansion

Wolt, a food delivery service operating in 27 countries, sought to enhance its market understanding and optimize its internal operations. 

By integrating dataplor’s POI data, they strengthened their selection insights and identified untapped merchant opportunities.

This resulted in a 40% market expansion in certain markets, surpassing their initial projections. Wolt also utilized dataplor’s POI data to streamline operations and improve their CRM systems, helping them allocate resources more effectively and grow their customer base.

3. Yeme Tech: Building Walkable Communities

Yeme Tech focused on community enhancement, faced challenges with unreliable and costly open-source data for its geospatial platform. 

By integrating dataplor’s POI data, they created a 15-minute walkable fulfillment benchmarking tool. This tool enabled them to provide valuable insights into walkability and sustainability in urban areas.
dataplor’s accurate and comprehensive POI data allowed Yeme Tech to make informed decisions, improve community engagement, and scale its platform globally with confidence.

Source: dataplor

Empower Your Business with dataplor’s POI Data

In today’s fast-paced business landscape, location analytics and POI data are crucial tools for understanding target markets and making informed decisions. By leveraging geospatial data and insights from dataplor’s POI data, you can identify high-potential areas, optimize your marketing strategies, and make data-driven choices for site selection and resource allocation.

Whether you’re looking to expand into new markets or gain a deeper understanding of your audience, location intelligence helps you to stay competitive and grow strategically.

Explore our comprehensive data solutions and discover how they can transform your business. By harnessing our rich datasets and location-based insights, you can make informed decisions that drive growth and profitability.

MANHATTAN BEACH, Calif. — Dec 18, 2024

dataplor, the leading global geospatial data company specializing in Point of Interest (POI) data, is excited to announce it has joined the Esri Partner Network (EPN) as a Bronze partner. Esri is the global market leader in geographic information system (GIS) software, location intelligence, and mapping. This collaboration aims to provide customers with enriched geospatial insights, combining the strengths of both companies to empower businesses with advanced tools for strategic decision-making worldwide.

Retailers, CPG brands, financial institutions, tech companies, and third-party logistics providers rely on dataplor for comprehensive and precise POI data to assess competitive landscapes, select new sites, and identify markets ripe for expansion. The EPN partnership with Esri will further empower these users with sophisticated location intelligence, enabling them to unlock deeper insights into market trends, investment opportunities, and risk mitigation strategies across various geographies and timeframes.

With a global network of 3,000 partners, Esri’s EPN partners help customers around the world utilize the benefits of ArcGIS software and location intelligence. For over 50 years, Esri partners have supported users with business solutions, implementation services, and dynamic content by leveraging GIS technology across every industry.

“The partnership with Esri represents a significant step forward in our mission to provide the most accurate and actionable geospatial data available,” said Geoff Michener, founder and CEO of dataplor. “Combining Esri’s ArcGIS software with dataplor’s high-quality POI data offers businesses unparalleled insight into where to focus their efforts and investments to achieve sustainable growth.”

dataplor is distinguished in the geospatial data sector by its exclusive focus on POI data and its rigorous data verification processes. While much location data is plagued by inaccuracies from unreliable open-source data and inconsistent records, dataplor employs advanced machine learning algorithms, AI-driven call bots for local business validation, and local human experts to resolve data ambiguities.

In the past year, dataplor has expanded its database to over 350 million POIs across more than 250 countries and territories, offering unmatched global coverage. Leading Fortune 500 companies, real estate investors, financial institutions, insurers, and local communities leverage dataplor’s data to identify strategic opportunities, mitigate risks, and drive success. By partnering with Esri, dataplor will further enhance its ability to provide businesses with powerful location intelligence solutions to optimize their market strategies.

Contact media@dataplor.com for more information.

Foot traffic data, also known as mobility data, shows how many people visit a specific place. This includes retail stores, fast-food restaurants, and many other public areas. The data collected gives businesses valuable insights into the number of people that visit a location and when. It plays a significant role in helping businesses uncover visitation patterns, tailor marketing efforts, and improve customer experiences.

The growing role of data analytics has changed how foot traffic data is measured. Originally, basic counting methods and turnstiles collected footfall data. But, with the rise of powerful tools like AI and machine learning, businesses can now track movements and analyze visitation patterns. This blog will explore recent foot traffic trends, their impact on industries, and how businesses can use these insights for more informed decisions.

How Foot Traffic Data Complements Location Data

Foot traffic and Point-of-Interest (POI) location data work together to provide a full picture of business landscapes. Foot traffic data provides information about consumer behavior, such as how many people visit a location and when. In contrast, POI data provides comprehensive details about locations, including their names, categories, hours of operation, and geographic coordinates.

When combined, these datasets offer businesses many advantages. For example, a retailer can use POI data to find nearby competitors and foot traffic data to see how often consumers visit them. These insights help businesses make better decisions about locations, marketing, and inventory, driving more visitors and boosting sales.

The Rise of Foot Traffic Analysis

Foot traffic analytics have grown significantly over the years. While early methods relied on manual counters and basic systems, businesses today use AI-enabled sensors, Wi-Fi tracking, and computer vision to monitor and measure foot traffic. These advancements have enhanced the accuracy and quality of demographic data, allowing businesses to gain deeper insights.

Key Industries Using Foot Traffic Data

1. Retail

The retail industry uses foot traffic data to understand shopper behavior, improve store layouts, and measure marketing effectiveness. Store locations with high foot traffic counts often suggest higher revenue and brand visibility.

• Return of In-Store Shopping: Following the pandemic, many shoppers are returning to in-store shopping. Recent reports expect in-store foot traffic to surpass pre-pandemic levels by 2025.
• Seasonal Trends: Consumer visitation data shows significant spikes during seasonal periods, giving stores prime opportunities for targeted marketing.

2. Commercial Real Estate

For investors and property managers, foot traffic data helps determine property value and smart investment opportunities. Understanding these traffic patterns allows for better planning and targeting.

• Development Planning: Real estate developers lean on foot traffic data to determine the scope of potential projects. This is important for ensuring there is high ROI.

3. QSR (Quick Service Restaurants)

Restaurant foot traffic data helps QSRs pinpoint ideal locations for expansion and refine operational strategies. Insights on a specific location can also help determine optimal staffing and inventory levels.

• Customer Decision-Making: High visitation amplifies the convenience of fast food in consumer decision-making. This data enables QSRs to enhance customer convenience and plan operations efficiently.
• Trends in Orders and Delivery: Food delivery has largely replaced in-restaurant dining with mobile and drive-thru orders. QSR businesses can analyze this data to streamline their services.
• Operational Efficiency: Brands like McDonald’s use foot traffic data to predict busy seasons, ensuring necessary staffing and inventory levels.

4. CPG (Consumer Packaged Goods)

CPG brands benefit from analyzing foot traffic to identify stores with high visit counts. Knowing the locations that attract the most visitors helps CPG companies decide where to place their products for the most impact.

• Retailer Performance: Foot traffic data enables CPG companies to pinpoint frequently visited retail stores, allowing them to collaborate with retailers on optimal product placement and promotions. By focusing on popular locations, brands can better address stocking and distribution efforts, driving brand visibility and increasing sales.
• Comprehensive Competitor Analysis: Gathering insights about foot traffic at nearby competitors allows your business to identify opportunities for site selection and areas for improvement.

Factors Behind Foot Traffic Data Collection

By leveraging foot traffic data, businesses gain valuable insights into consumer patterns, operational efficiency, and market trends. Understanding the factors that drive this data collection helps businesses adapt to changing environments and make informed decisions.

1. Consumer Behavior: Analyzing how consumers interact with physical store locations is crucial for businesses that are looking to provide high quality experiences.
2. Urban Development: The growth of urban areas increases visitation, emphasizing the need to analyze foot traffic.
3. Technological Growth: The rise of loT devices, artificial intelligence, and machine learning has made footfall data more comprehensive.

Key Foot Traffic Insights

Consumer Behavior and Shopping Patterns

Foot traffic data offers valuable insights into consumer trends and shopping patterns. By analyzing visitation data, businesses can identify the busiest locations and understand how these patterns affect sales. This also allows businesses to align staffing and inventory in high-traffic locations, improving the overall customer experience.

Seasonal and Trend-Driven Shifts

Seasonal trends can also have a significant impact on foot traffic patterns. During holidays, back-to-school seasons, and events like the 2024 Paris Olympics, businesses can adjust their efforts to accommodate more visitors.

Leveraging Foot Traffic Data for Business Success

Optimizing Store Inventory

Businesses across various industries can leverage foot traffic to optimize inventory planning. By identifying high-traffic locations, businesses can allocate inventory to the stores that see the most visitors, aligning stock levels with consumer demand. For example, a grocery store chain may stock popular products in stores with higher foot traffic to increase visibility and sales potential.

Targeted Marketing & Promotions

Foot traffic insights help businesses improve marketing by using strategies like geo-targeted ads and personalized outreach. By understanding popular visiting times, companies can plan promotional events for maximum impact. Real-time, high-quality foot traffic data also contributes to staffing and operational efficiency. It does this by helping businesses predict peak times, cut costs, and enhance the customer’s experience.

Site Selection Strategies

Consumer visitation data supports location strategy and site selection. This allows businesses to identify high-density areas for potential store openings. It also helps pinpoint areas with high growth potential. For example, a coffee shop may use foot traffic data to open new locations near busy transit hubs.

Privacy & Ethical Considerations

When collecting and using this data, it is important for businesses to respect the privacy of consumers. Some key ethical considerations include:

• Anonymization: Verifying that data is collected in a way that doesn’t reveal consumers’ personal information is key.
• Compliance: Adhering to privacy regulations such as the General Data Protection Regulation (GDPR) is essential to maintaining consumer trust. This also safeguards visitor’s personal and identifiable information. By prioritizing these compliance measures, businesses can responsibly use foot traffic data while respecting privacy.

The Future of Foot Traffic Analytics

The landscape of foot traffic analytics is evolving, driven by advancements in technology and the constant demands of businesses. Emerging trends will continue to shape how foot traffic data is collected, analyzed, and applied across various industries.

Artificial Intelligence & Machine Learning

It’s no surprise that artificial intelligence and machine learning have completely transformed how foot traffic data is collected. These technologies allow businesses to predict future visitation data and draw patterns with reliable accuracy. AI tools analyze past visitation data, weather, and events to help businesses optimize operations. These predictive measures help businesses to stay ahead of consumer trends, giving them a competitive advantage.

Virtual Reality

As digital and physical spaces collide, foot traffic data will contribute to hybrid environments. With the rise of virtual reality, businesses can track virtual foot traffic and compare it to real world footfall. The combination of these data sources can provide a comprehensive view of customer behavior.

Smart Cities

In smart cities, foot traffic data will be key for planning and improvement. Smart city planners can analyze movement and busy areas to improve transportation initiatives and allocate resources better. It can also help make strategic decisions around safety and designing efficient spaces. This data provides the high levels of insight needed to build sustainable, smart cities.

Start Leveraging Foot Traffic Data for Business Insights

Understanding a geographic area’s foot traffic pattern is no longer a choice for businesses; it is a strategic necessity. By studying patterns and leveraging insights from mobility data, businesses can optimize operations, improve customer experiences, and drive profits.

Foot traffic data helps businesses understand when and where customers engage, enabling better decisions around store placement, staffing and stocking logistics, marketing efforts, and more. Whether you’re a retailer, investor, property manager, QSR owner, or CPG brand, utilizing foot traffic data can help you stay ahead of the competition.

Want to learn more about how location data can impact your business?

You can learn more about our resources here. Partner with dataplor today and experience all the benefits on a real-time basis!

Geospatial intelligence, or (GEOINT) refers to the integration of geographic information and technology—such as satellite imagery, remote sensing, and Geographic Information Systems (GIS)—to derive insights from spatial data. GEOINT captures data from the Earth’s surface to support decision-making across various industries. 

Originally used by the intelligence community, including the U.S. military and national security agencies, GEOINT now plays a vital role in helping businesses worldwide to make informed decisions, ranging from disaster response to market entry.

The National Geospatial-Intelligence Agency (NGA) was initially known for delivering intelligence products and analysis through aerial imagery and mapping services. However, with the rise of big data, geospatial intelligence has expanded beyond its traditional use. Today, many industries leverage geospatial data to turn complex data into actionable insights, transforming business practices and decision-making.

The geospatial analytics market is expected to reach $141.9 billion by 2028, making GEOINT a key focus for businesses worldwide.

This article covers the basics of geospatial intelligence, its sources and applications, and how businesses are using it to stay ahead. We’ll also explore how dataplor fits into the geospatial arena and how you can benefit from our solutions. 

What is Geospatial Intelligence?

Geospatial intelligence is the combination of geographic data, spatial analysis, and information management to produce insights.      

These insights are used by decision-makers worldwide to understand and respond to complex situations, from national security to business strategy.

Here are some of the main components of geospatial data: 

1. Geographic Data: The foundation of GEOINT is geographic data, which is information about the Earth’s surface and its features. This data is gathered through various means, such as satellite imagery, aerial photography, remote sensing, and even social media check-ins, providing a rich, multi-dimensional view of any area.
   
2. Spatial Analysis: Once geographic data is collected, spatial analysis processes it to uncover patterns, trends, and relationships. Using mathematical and statistical techniques, spatial analysis reveals how different geographic elements interact. This approach is applied in areas such as identifying the best locations for business expansion, imagery intelligence, and analyzing environmental changes.
   
3. Information Management: Geospatial intelligence involves managing large volumes  of data. Information management systems organize, store, and process GEOINT data to ensure it is accurate, accessible, and actionable. High-resolution datasets, mapping software, and cloud-based tools also allow analysts to interpret information quickly and provide real-time insights to decision-makers.

However, it’s important to understand the difference between geospatial intelligence and Geographic Information Systems. Although they are closely related, GEOINT and GIS serve different purposes. 

• GIS is a tool for collecting, storing, and visualizing geographic data, often in the form of maps or layered visual representations. 
• Geospatial intelligence, on the other hand, takes GIS data and applies spatial analysis and information management techniques to generate insights for strategic decision-making. 

In essence, while GIS is a system for handling geographic data, GEOINT is the analysis and intelligence derived from that data.

The Benefits of Geospatial Intelligence

GEOINT gives you valuable insights to change how you approach strategy, operations, and risk management in your business. 

By combining geographic data, spatial analysis, and information management, GEOINT enables informed decision-making based on real-world, location-specific information.

Here are the main advantages:

1. Better Decision Making: GEOINT gives you high-resolution, data-driven insights into market conditions, customer behavior, and operational performance across geographic areas. You can use these insights to choose the best locations for new store locations, evaluate supply chain logistics, and allocate resources where they’ll have the most impact.
   
2. Better Operational Efficiency: GEOINT helps optimize routes, plan resource allocation, and anticipate customer demand based on geographic patterns. For logistics and supply chain companies, this often translates to reducing fuel costs and delivery times. In utilities or telecommunications, it supports coordinating infrastructure repairs and upgrades based on location-specific needs.
   
3. More Market Understanding: Geospatial data provides a 360-degree view of your market, revealing demographic trends, spending patterns, and competitor locations. With this data, you can tailor your marketing campaigns, identify high-potential markets, and personalize customer experiences based on location-specific characteristics.
   
4. Risk Management: Geospatial intelligence helps you identify and manage risks related to natural disasters, market volatility, and security threats. Using tools like remote sensing and satellite images, you can anticipate weather-related disruptions, assess regional stability, plan for contingencies, and protect your assets and workforce.

For industries where location knowledge is crucial—such as retail, real estate, logistics, and finance—geospatial intelligence gives you a competitive edge by turning geographic information into a strategic advantage.

The Role of Location Data in Geospatial Intelligence

It’s no surprise that reliable location data is the foundation of geospatial intelligence. 

The value of GEOINT lies in the accuracy, depth, and relevance of the geospatial data, which turns raw location information into actionable insights for decision-making.

By providing real-time, location-specific data, you can make strategic decisions based on a comprehensive understanding of geographic and spatial factors.

Geographic Features

Geographic features like terrain, elevation, water bodies, and infrastructure form the foundational layer of geospatial intelligence. 

This data, sourced from tools like GIS, helps businesses and analysts visualize physical environments and gain a deeper understanding of the geographical context surrounding operational areas.

Remote Sensing Imagery

Remote sensing imagery captured from satellite or aerial platforms provides an up-to-date, high-resolution view of specific locations. 

You can also obtain intelligence and insights across various sectors, from urban planning to crop health to disaster impact. 

Remote sensing helps businesses track changes over time, which is invaluable for industries such as real estate, agriculture, and national security.

Location Data

Location data from devices, social media, and GPS allows businesses to analyze real-time customer behavior, movement patterns, and population density. 

By using location-based insights, businesses can personalize marketing, optimize site selection, and refine customer engagement strategies based on where their target audience lives, works, and spends time.

These three types of geospatial data collectively enhance the overall geospatial intelligence picture, providing valuable context, insights, and the ability to predict future trends. 

By combining these data types, you can make GEOINT a powerful tool for location-specific decision-making.

Empower Your Organization with dataplor’s Geospatial Data

Whether through open source or other means, geospatial intelligence (GEOINT) is a valuable asset for businesses looking to incorporate location-based insights into their strategic decision-making, operational efficiency, and market understanding. 

In today’s data-driven world, where precise and actionable information is more crucial than ever, the importance of quality geospatial data continues to grow.

dataplor’s geospatial data solutions help organizations to maximize the value of  GEOINT, offering high-resolution, real-time insights tailored to their business needs. From site selection to customer engagement, decision-makers can rely on dataplor’s solutions and tools to stay informed and ahead of the competition.

Ready to elevate your organization with cutting-edge geospatial intelligence? 

Explore dataplor’s data solutions and see how we can support your growth. 

Reach out today for a consultation or request a data set sample to experience the dataplor advantage firsthand.

OpenStreetMap.org (OSM) is a collaborative, open-source project that provides a global, editable map of the world, much like a Wiki database. 

With millions of volunteer OpenStreetMap contributors, OSM data is free and widely used for mapping and geographic analysis across various industries. This data is especially useful for non-profits and federal governments requiring geospatial data for general planning where approximate locations suffice.  

Managed by the OpenStreetMap Foundation (OSMF), OSM’s nonprofit structure ensures data remains open and accessible on the official website, with contributions from individual mappers and larger organizations.

Despite being free, OpenStreetMap data can have gaps in accuracy, consistency, and completeness. This is where premium data providers like dataplor, with higher quality datasets, play a key role by offering up-to-date accurate location data, seamless integrations, and continuous data accuracy verification. 

Understanding the true cost of “free” data in the online ecosystem is essential for making informed decisions about geospatial needs.

In this article, we’ll look at OSM’s offerings, the limitations of open-source data, and the added value dataplor brings to businesses in need of high-quality geospatial insights.

Why Location Data Matters

Location data is a valuable asset for businesses. It provides insights into customer behavior, optimizes operational logistics, and facilitates strategic planning. 

With accurate location data, businesses can make data-driven decisions that lead to better customer experiences, targeted marketing, and optimized supply chains.

From site selection to real-time asset tracking, high-quality geospatial data helps businesses stay agile and responsive in a competitive market. 

Investing in reliable, detailed location data can greatly enhance a company’s ability to achieve its strategic goals and adapt to changing market conditions.

Drawbacks of OSM

Are you wondering why not to opt for OSM? Here are some areas where it falls short.

Data Discrepancy

In the past, there have been instances where contributors have manipulated OSM data to serve their own interests. For example, during the Pokémon Go craze, changes to OSM data were made to influence in-game locations, impacting the user experience. Intentionally altering the data like this can compromise the reliability of OSM for business operations that rely on consistent and unbiased data.

Inconsistent Data Quality

One of OpenStreetMap’s most significant drawbacks is the variability in data accuracy and completeness across regions. 

Since volunteers contribute to OSM, the data quality can vary, often resulting in outdated or incorrect information. 

In areas with fewer contributors, the data may contain gaps, which can be problematic for business operations that require up-to-date, reliable information.

Relying on inconsistent or inaccurate data can lead to significant financial losses, potentially costing your business hundreds or even thousands of dollars in profitability. 

Limited Attribution Data

OSM provides basic geography but often lacks business details like opening hours, phone numbers, or online reviews. 

This limited attribute data can prevent businesses from profiling, engaging with local markets, and gaining customer insights and outreach strategies for commercial use.

Time-Consuming Data Processing

Using OSM data for commercial purposes can require significant effort.

Data cleaning, validation, and enrichment are often necessary, as raw OSM data may not meet the quality standards or specific criteria businesses need. 

This additional processing adds time and cost, making OSM less suitable for businesses looking for a ready-to-use data solution.

Lack of Real-Time Updates

OSM data doesn’t have the frequent real-time updates businesses need to stay current. 

In rapidly changing environments like cities or expanding regions, this delay can result in outdated maps with minimal overlay data, impacting decisions for activities such as delivery routing, customer service, and local marketing.

Advantages of dataplor’s Comprehensive Data

While OSM is an open-source option, businesses often need higher quality, more detailed, and up-to-date location data to stay ahead of the competition. One of our most common FAQs is how dataplor can provide this advantage. 

Here are some of the advantages of using premium data.

High Data Quality

dataplor’s data is known for its accuracy, completeness, and consistency. 

Regular updates ensure our datasets reflect real-world changes, minimize errors, and enhance the reliability of the insights. 

This high-quality data allows businesses to make confident decisions without worrying about data integrity.

Rich Attribute Data

Beyond the basic coordinates, dataplor’s datasets include extensive business details such as contact information, operating hours, and even online reviews. 

This attribute data allows businesses to profile and engage with local markets, providing deeper customer insights and allowing you to tailor your strategy to specific regions.

Easy Integration

dataplor simplifies the integration of location data into your existing business applications with a consistent global schema.

This ease of integration allows you to quickly implement data without lengthy development times, making it ideal for businesses that require fast and flexible solutions.

Real-Time Updates

dataplor provides real-time updates, ensuring the data reflects the latest changes on the ground.

This is essential for time-sensitive operations such as logistics, delivery, and regional marketing, where having up-to-date information is key to success.

Benefits of Comprehensive POI Data

Access to high-quality Point-of-Interest (POI) data gives businesses many strategic advantages, including the ability to optimize operations and make data-driven decisions that drive growth and profitability.

Increase Revenue

POI data helps identify locations for expansion and tailor marketing efforts to local needs. 

It allows you to understand potential customers’ preferences and target them more effectively, helping to grow your revenue accordingly.

Outpace Competitors

Having real-time POI data allows you to respond more quickly to market changes than your competition. 

With local insights, you can innovate based on changing demand, adjust to the industry ahead of the competition, and remain relevant to your customers—both online and at your  physical store locations.

Support Site Selection

Location data is key for retail, real estate, and many other industries. 

POI data gives an in-depth view of an area’s demographics, competitor presence, and infrastructure, allowing you to make more informed site selections and choose the right location to maximize profit.

Support Investment Decisions

For investors, knowing the geography of an asset is a huge advantage. 

POI data gives you insights into local economic conditions, infrastructure developments, and consumer behavior so you can make informed, low-risk decisions that align with your investment strategy.

Reach New Audiences

POI data shows you the untapped areas and customer bases that align with your growth plans. 

You can use this data to expand into new markets, reach a wider audience, and build customer loyalty in previously unreached areas.

Unlock the Power of Comprehensive Data with dataplor

Choosing the right geospatial data source can be a game-changer for businesses, especially when it comes to accuracy, reliability, and speed. 

While OSM data is free and community-driven, its limitations in consistency, depth, and real-time accuracy can pose challenges. In contrast, dataplor provides high-quality, commercially focused data sets designed for today’s competitive market.

Unlike OSM’s crowd-sourced model, dataplor continuously validates and enriches its data, providing robust POI insights, timely updates, and extensive attributes like business hours, contact details, and more. 

This is why dataplor is the preferred choice for decision-makers who can’t afford the inconsistencies of free data.

With dataplor on your side, you can: 

• Make decisions based on the latest information.
• Gain a competitive edge by fully understanding your operating environment.
• Skip the hassle of in-house data management and focus on strategy.

Transform your business strategy with dataplor’s high-quality geospatial data. 

Contact dataplor today to learn more about how comprehensive, accurate data can give your organization the edge it needs to succeed.

Start making data-driven decisions now with confidence. 

Partner with dataplor today and experience all the benefits in real-time!

The proposed $24.6 billion merger between grocery giants Kroger and Albertsons has already found itself under intense legal scrutiny, with trials recently concluding in both Washington state and Colorado. Set to make their rulings in mid-November, these states, along with a federal case, are weighing the merger’s potential impact on competition, consumer prices, and jobs.

In Washington, where nearly half of the state’s grocery market could be affected, Attorney General and Governor-Elect Bob Ferguson argues that the merger would stifle competition and raise prices, eliminating daily battles between Kroger and Albertsons stores over promotional pricing, product quality, and even store hours. Meanwhile, in Colorado, Attorney General Phil Weiser echoes these concerns, challenging the adequacy of Kroger and Albertsons’ proposed divestiture of 579 stores—a plan intended to maintain market competition.

While Kroger and Albertsons contend that the merger is essential to competing with Walmart’s market dominance, regulatory authorities, labor unions, and consumer advocacy groups remain skeptical. dataplor’s analysis of Point-of-Interest (POI) data offers insights into what this merger could mean for the future of grocery shopping and mergers in the U.S.

Where the Overlap Matters Most

With over 4,000 Albertsons locations across the U.S., our analysis reveals that 37% of grocery stores within a 5-mile radius of an Albertsons are Kroger-branded. As we expand the radius to 10 miles, Kroger’s share increases to 40%. These figures represent more than just proximity; they signify a potential consolidation that could fundamentally reshape competition and limit options for millions of shoppers. This overlap is particularly pronounced in states like Arizona, California, Colorado, Oregon, and Washington, where both chains have substantial footprints and where the greatest number of divestitures are planned if the merger goes through. 

Compounding this, 30.3% of Albertsons locations have Kroger as the only other major grocery competitor within 5 miles—excluding smaller bodegas and specialty stores. If the merger is approved, these stores would lose their only direct competitor, potentially leading to fewer choices, higher prices, and diminished market innovation for local consumers.

What’s at Stake for Consumers?

As legal battles unfold, the data tells a compelling story about what could change for consumers. Combined, Kroger and Albertsons would control 13-18% of U.S. grocery sales, depending on the metric used. This level of consolidation could reduce competition in markets where the two already have strong footholds, particularly in states with significant overlap. Critics, including the Federal Trade Commission (FTC), caution that removing this competitive tension would lead to higher prices, reduced consumer choice, and potential job losses.

If approved, the merger will redefine grocery shopping for millions. dataplor’s data-driven analysis sheds light on potential shifts in market dynamics and the impact on local competition. As we await court decisions that will determine the fate of this deal, understanding market concentration and geographic overlap has never been more critical for businesses navigating change.

Want to uncover the data-driven insights that power strategic decisions? Contact dataplor to explore how our expertise can guide your understanding of market dynamics and help you seize emerging opportunities.

The digital world is constantly developing and evolving, and in today’s competitive landscape, many businesses struggle with the challenges of limited data insights. Relying on raw data alone often leads to gaps in understanding customer preferences and missed opportunities in targeted marketing.

Customer expectations evolve with time, making it vital to seek out deeper data insights from your existing data to maintain an edge. This is where data enrichment becomes essential, allowing you to enhance the quality of your datasets and make informed decisions that drive the growth of your business.

A recent study reveals that businesses investing in data enrichment experience a 20% improvement in their ability to understand customer behavior and preferences. This enhanced understanding can empower you to refine your marketing strategies, tailor your messages, and optimize the efforts of your sales teams, leading to positive and measurable results.

In this article, we’ll review the fundamentals of data enrichment, explore how dataplor’s POI data enhances the data enrichment process, and provide some real-world use cases and examples of how businesses have achieved success using enriched datasets.

What is Data Enrichment?

Data enrichment is the process of adding additional information to existing datasets to improve their quality, accuracy, and completeness. For instance, if you’re evaluating customer data, you may want to include elements such as appending external data or first-party data, contact data, or third-party data—such as demographic data, contact information, and firmographic data—to existing customer data. 

By enriching raw data with high-quality information from various data sources, you can turn incomplete or outdated data into actionable insights, improving the overall value of your data management and validation processes. Data cleansing tools can help you ensure that this enriched data is accurate and ready for use in making business decisions.

Here’s why data enrichment is important for your business:

1. Complete Market View

With data enrichment, you can achieve a complete view of your market by combining existing data with external data sources. This allows you to track competition, identify new opportunities, and validate business decisions.

Having enriched datasets allows you to analyze trends in real-time and make informed decisions based on comprehensive insights.

2. Better Customer Segmentation

Enriching customer profiles with demographic and firmographic data enables you to segment your audiences more precisely. This deeper understanding of customer needs and preferences allows for more effective targeted marketing efforts.

It ensures that your marketing teams can deliver personalized messages that resonate with distinct groups, improving the overall customer experience.

3. Optimized Marketing Campaigns

By enhancing CRM and marketing databases with high-quality data, you can optimize your marketing strategies. 

For instance, enriching customer data with insights from POI data allows you to craft campaigns that are more aligned with consumer preferences, ultimately boosting conversion rates and enhancing customer relationships.

4. Smarter, Data-Driven Decisions

With enriched datasets, you can make data-driven decisions based on comprehensive, quality data. This helps fine-tune sales efforts, improve workflows, and boost overall efficiency.

Having access to data enrichment tools like dataplor ensures that every piece of information is validated, accurate, and ready for action, providing a solid foundation for strategic decision-making.

How POI Data Supercharges Data Enrichment

POI (Point-of-Interest) data refers to detailed information about specific physical locations such as restaurants, retail stores, landmarks, and other notable places. This data offers insights into various locations, their operating details, and surrounding areas. With POI data, you can gain a deeper understanding of geographic contexts, which play a crucial role in targeted marketing and customer segmentation efforts.

POI data is a valuable source of information that enables you to enrich your current datasets with comprehensive details about surrounding locations. The result is a more detailed and holistic view of your customer’s environment.

POI data can be used to enrich existing data by adding valuable contextual information that offers you a statistical edge. Here’s how:

1. Business Longevity and Local Attractions

By integrating POI data with your customer data, you can gain insights into the longevity of businesses in a given area and nearby attractions that add value to the location.

Understanding which types of businesses have a long-standing presence—such as high-end retail stores or family restaurants—can help you craft targeted marketing messages and refine your outreach efforts. Utilizing these insights into established businesses and popular attractions can elevate your marketing strategies and boost conversion rates.

2. Competitor Proximity and Complementary Businesses

Understanding the proximity of competitors or complementary businesses around a given POI can help you tailor your sales and marketing strategies. 

For example, if a competitor is located nearby you can create lucrative offers to lure customers or offer complementary services that enhance your customer relationships. This information, combined with third-party data, enables informed decisions and allows you to stay ahead in competitive markets.

Incorporating POI data into your data enrichment process not only enhances the quality of your datasets but also gives you deeper insights into market trends, customer behavior, and local competition. This enriched data is particularly valuable if you’re focused on enhancing third-party logistics, helping you optimize delivery routes, and improving operational efficiency.

By leveraging this additional information, you can make smarter, data-driven decisions and optimize your sales teams and workflows accordingly.

Examples of Data Enrichment with POI Data (Use Cases)

To illustrate the impact of POI data on data enrichment, let’s explore some real-world examples from various industries. From optimizing site selection to enhancing marketing strategies, various businesses across different sectors have successfully leveraged enriched datasets to gain a competitive edge.

These use cases demonstrate how you can harness the power of POI data to make smarter decisions, improve operational efficiency, and unlock new growth opportunities.

1. Tensorflight: Optimizing Real Estate Site Selection

Tensorflight, a tech company specializing in property analytics for the insurance industry, turned to dataplor to enhance its real estate data for more accurate property evaluations. By integrating dataplor’s POI data with their proprietary models, they were able to improve the geocoding accuracy and refine building occupancy and tenant type classifications.

This enriched data helped Tensorflight provide insurers with more detailed property insights, ensuring that building replacement costs and occupancy risks were calculated with greater precision. The collaboration led to significant improvements in data-driven decision-making for property insurance, enabling more accurate real estate assessments.

2. IKEA: Streamlining Delivery for Better Customer Service

IKEA, known for its large-scale furniture retail operations, significantly improved its last-mile delivery efficiency by leveraging geospatial data and investing in advanced software to optimize delivery routes. 

Through route planning and monitoring of truckloads, IKEA Retail Denmark was able to pilot a program that reduced delivery times and operational costs. This focus on data-driven logistics resulted in streamlined processes and improved customer satisfaction by ensuring timely deliveries.

Empower Your Data Enrichment Journey with dataplor

In today’s data-driven and competitive world, staying ahead requires making timely, well-informed decisions. Data enrichment is no longer a luxury you can conveniently ignore; it has become a necessity for gaining a deeper understanding of your customers, optimizing market strategies, and driving operational efficiencies.

By enriching existing datasets with high-quality, accurate information, you can unlock the true potential of your business data. And that’s where our advanced and comprehensive POI data comes into play.

With our comprehensive location data, we provide you with the tools you need to stay competitive in your industry. Whether you’re enhancing customer profiles, improving decision-making, or optimizing workflows, dataplor’s POI data delivers valuable insights that can propel your business forward.

Request a sample to explore our POI data solutions and learn how our data enrichment services can take your business to new heights. 
Learn more about us and start your journey with dataplor to harness the power of data enrichment.