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.

In today’s competitive business landscape, understanding your competitors’ strategies and predicting their next move offers a significant advantage. This practice, known as competitive intelligence, involves gathering and analyzing data to uncover insights into the strengths, weaknesses, and potential business strategies of your direct competitors. 

Competitive intelligence has become an essential tool in today’s market, enabling businesses to make informed decisions and develop strategic plans to outpace both direct and indirect competitors. A thorough competitive intelligence analysis provides actionable insights that empower  sales, product, and marketing teams to refine their strategies and stay ahead.

In this article, we’ll cover the fundamentals of competitive intelligence, ethical data sources, and how to integrate competitive intelligence into your broader business strategy. Additionally, we’ll explore emerging trends in competitive intelligence to help sharpen your competitive insights.

Foundations of Competitive Intelligence

Competitive intelligence involves systematically gathering, analyzing, and applying data to anticipate competitors’ strategies. This process helps identify new market opportunities, reduce risks, and craft well-informed strategies that give you a competitive edge.

Effectively leveraging competitive intelligence is key to driving growth and staying ahead in the market. 

Leveraging Location Data in Competitive Intelligence

Location data is a valuable resource for businesses looking to enhance their competitive strategies. By utilizing these insights, companies can identify trends, optimize operations, and make more informed decisions. Whether it’s understanding competitors’ strategies or improving operational efficiency, location data offers a deeper understanding of the market and uncovers new opportunities for growth.


Here are some specific ways location data can contribute to competitive intelligence:

1. Market Penetration and Expansion:

• Identify Untapped Markets: Discover regions where your competitors have a limited presence or are underserved.
• Optimize Store Locations: Analyze competitor store locations to determine the best areas for expanding your own retail footprint.
• Assess Market Saturation: Determine the level of competition in specific markets to avoid oversaturation.

2. Supply Chain Optimization:

• Evaluate Supplier Locations: Assess the geographic distribution of your competitors’ suppliers to identify potential sourcing opportunities.
• Optimize Logistics Routes: Analyze transportation patterns to optimize your supply chain and reduce costs.

3. Risk Mitigation:

• Monitor Competitor Expansion: Track your competitors’ geographic expansion plans to identify potential threats to your market share.
• Assess Natural Disaster Risks: Evaluate the location of your facilities and supply chains in relation to natural disaster zones.

Future Trends in Competitive Intelligence

The competitive landscape is evolving rapidly due to constant technological advancements. To stay ahead, businesses must harness the power of real-time data and predictive analytics. dataplor’s ability to provide accurate and timely location data offers a unique advantage in this area.

• Real-Time Insights and Predictive Analytics: By using location data, businesses can create predictive models that forecast future trends, such as where customers are moving, where competitors are expanding, and new opportunities in the market.
• Interactive Dashboards: Location data can be used to create interactive dashboards that visualize complex data, helping decision-makers identify trends, anomalies, and opportunities.
• Geospatial Analysis: Businesses can use location data to conduct in-depth geospatial analysis, visualizing customer distribution, analyzing competitor market share, and identifying optimal locations for expansion or marketing campaigns.

As businesses strive to gain a competitive edge, real-time location data will continue to play a pivotal role. dataplor’s offerings provide the foundation for businesses to leverage this valuable asset. By harnessing the power of real-time insights, predictive analytics, and enhanced visualization, companies can make informed decisions, anticipate market trends, and stay ahead of the competition.

Partner with dataplor for Cutting-Edge Competitive Intelligence

In today’s dynamic business environment, leveraging competitive intelligence is essential for making informed strategic decisions. Accurate location data can be the competitive intel needed to help you stay ahead of your rivals.

dataplor provides comprehensive location data to enhance your business’s competitive intelligence capabilities. By utilizing our expertise, you can gain a clearer view of your competitors’ strategies and stay ahead in the market.

Get in touch with us today to explore how our advanced competitive intelligence can drive your success.

When Saturday Night Live recently poked fun at Spirit Halloween for taking over vacant stores, the retailer responded with a clever clapback: “We are great at raising things back from the dead.” While the joke got laughs, it highlighted a real trend. As traditional retailers close their doors, Spirit Halloween is leading the way in transforming empty storefronts into seasonal pop-up success stories. And in 2024, their presence is more significant than ever, signaling a shift in how retail space is used.

At dataplor, we’ve analyzed the data behind Spirit Halloween’s location strategy, and it’s clear that this seasonal takeover is tapping into a larger economic trend.

Retail Giants Turned Haunted Locations

The wave of store closures from well-known retail brands has created opportunities for temporary businesses to occupy high-visibility, high-traffic spaces. In 2024, the top five former tenants of Spirit Halloween locations include:

• Bed Bath & Beyond: 77 locations
• Rite Aid: 66 locations
• Tuesday Morning: 59 locations
• Sears: 54 locations
• CVS: 39 locations

Together, these five brands account for approximately 13% of all current Spirit Halloween locations. What’s striking is that four of these brands—Bed Bath & Beyond, Rite Aid, Tuesday Morning, and Sears—have filed for bankruptcy within the past six years. Their closures have left prime retail spaces available for companies like Spirit Halloween to move into.

Pop-Up Retail and the Changing Face of Commercial Real Estate

Spirit Halloween’s ability to quickly occupy these retail spaces, whether they were once big-box stores like Sears or smaller specialty shops like Zia Records, showcases the agility of the pop-up retail model. The chain strategically targets locations with a population of 35,000+ within a 3-5 mile radius and a daily traffic count of at least 25,000 cars. Flexibility is a core strength, allowing Spirit Halloween to occupy spaces ranging from 5,000 to 50,000 square feet—ensuring they can adapt to a variety of store sizes while maximizing visibility and foot traffic. As traditional retailers shutter their doors, leaving ghostly remnants of empty storefronts, seasonal brands like Spirit Halloween swoop in, using short-term leases to resurrect these spaces from the retail graveyard.

dataplor’s Look Inside Spirit Halloween’s Haunting:

1. Vacancy as Opportunity:
   Spirit Halloween has made a business of moving into spaces left by major retailers. Our analysis of current location data shows that Bed Bath & Beyond stores alone account for 77 locations. As vacancy rates fall and new commercial space becomes scarcer, the demand for these spaces is only increasing.
2. Suburban Appeal:
   Many of the brands that previously occupied Spirit Halloween locations, such as Rite Aid and Bed Bath & Beyond, were heavily focused on suburban retail spaces. As suburban populations grow and remote work trends continue, these areas become more attractive for retailers, making them ideal for Spirit Halloween’s pop-up stores.
3. Temporary but Strategic:
   Pop-up stores like Spirit Halloween can take advantage of short-term leases to operate during peak seasons without the burden of long-term commitments. This strategy allows them to maximize profitability while minimizing overhead, especially in high-demand locations.

Will There Be a Future With More Pop-Up Stores and Fewer Traditional Stores?

As the retail landscape continues to evolve, the rise of pop-up stores like Spirit Halloween may signal a broader shift away from traditional brick-and-mortar retail models. While Spirit Halloween has traditionally focused on the spooky season, recent developments suggest that this model could extend well beyond Halloween.

Enter Spirit Christmas.

Spirit Halloween’s parent company, Spencer Gifts, is expanding the concept into the winter holidays. For the first time, Spirit will be converting some of its Halloween stores into Spirit Christmas locations. These holiday-themed pop-ups will take over retail spaces across the Northeast, offering decorations, stocking stuffers, gifts, and even Santa photo ops. With locations planned in states like New Jersey, Connecticut, New York, Massachusetts, and Pennsylvania, this move demonstrates the growing viability of the pop-up model across different retail seasons.

Given that the National Retail Federation (NRF) forecasts $11.6 billion in spending on Halloween costumes, decorations, and other items, it’s clear that the haunted holiday is a significant business. However, the winter holidays are an even bigger opportunity, with $964 billion spent in the U.S. last year alone.

As traditional retail giants continue to close stores or file for bankruptcy, the pop-up model—exemplified by Spirit Halloween—offers a glimpse into the future of retail. Consumers still crave physical shopping experiences, particularly for seasonal or specialty items, and retailers like Spirit Halloween and Spirit Christmas have shown that they can meet this demand cost-effectively and flexibly.

For real estate investors and lessors, this presents an opportunity to fill vacant spaces with temporary tenants who drive foot traffic and create buzz. Meanwhile, for retailers, the pop-up model provides a way to engage customers directly, offering immersive experiences that are difficult to replicate online.

In the coming years, we may see more retailers adopting this flexible approach, especially as e-commerce grows and the demand for traditional, permanent retail spaces decreases. Whether for Halloween, Christmas, or any other seasonal event, the ability to set up shop quickly, sell to a targeted audience, and move on could become the new normal.

At dataplor, we provide the insights businesses need to navigate this changing landscape. By tracking trends in location data, vacancy rates, and market opportunities, we help retailers and investors make informed decisions about capitalizing on the growing demand for flexible retail solutions. Whether you want to understand the latest trends or inform the future business locations, dataplor has the data-driven insights you need to succeed in a rapidly evolving market. Contact us and see how we can help your business haunt the most profitable locations year-round.

In today’s environment, location data plays a pivotal role in shaping industry strategies and driving decision-making. By leveraging location data, companies can uncover new opportunities, streamline operations, and rapidly navigate complex global markets.

Location data is critical not only for chief data officers, geospatial data scientists, and global growth officers, but also for a wide range of professionals across various industries. According to a MarketsandMarkets report, the global location analytics market is projected to grow from $20.6 billion in 2023 to $38.5 billion by 2028, driven by the increasing adoption of location intelligence among leading Fortune 500 companies.

In this article, we will examine the role of location data in business strategy, the rising significance of this data among industry leaders, and how top companies are leveraging our services to unlock new markets for global growth.

What is Location Data?

Location data is geographic information that pinpoints the physical location of a place, person, or object on earth. It can help businesses decide where to expand, optimize operations, or target specific markets.

Location-based data is gathered through multiple methods and incorporates a range of metrics: machine learning, advanced image recognition, artificial intelligence, large language models, and global human validators.         

With dataplor, businesses can get the spatial data they need to drive their strategic decision-making.      

Tools and Technologies for Visualizing Location Data

Managing and analyzing location data requires advanced spatial analytics tools and Geographic Information Systems (GIS). These tools are designed to process vast amounts of geographic data, transforming raw data into actionable insights that strengthen business decisions.Spatial analytics tools like Esri and CARTO are well known for their capabilities in location data visualization.

Source: Esri

Caption: The above is a visual representation of dataplor’s data on Esri’s platform.

Esri’s ArcGIS offers an entire suite of tools for location information, mapping, spatial analysis and data visualization. Businesses can integrate multiple data sources, analyze geographic trends and points of interest (POI), and make real-world decisions based on spatial patterns.  

Source: CARTO

Caption: The above is a visual representation of dataplor’s data on CARTO’s platform.

CARTO offers robust location intelligence solutions that enable users to visualize and analyze spatial data effortlessly. Their cloud-based platform supports real-time data processing, making it ideal for businesses that require up-to-date insights.

Applications Across Industries

Location intelligence is a powerful asset across many industries, offering a range of use cases.

From retail to telecommunications, companies leverage this data to gain a competitive edge, make informed decisions, and unlock new opportunities. Here’s how various sectors use different types of location data to achieve success.

Retail

For retailers, location data is key to site selection. By analyzing demographic and geographic data, companies can identify prime locations for new stores that maximize profitability and effectively reach their target audience. 

For example, by understanding their local competition, retailers can position themselves in high-demand areas to outpace their competitors and increase revenue.

Third-Party Logistics (3PL) 

In third-party logistics, location data can help optimize route planning and delivery times. Companies like Uber use this data to streamline last-mile fulfillment, ensure on-time deliveries, and reduce operational costs. 

Accurate location data allows logistics providers to plan the most efficient routes, reduce fuel consumption, and improve overall service levels while boosting revenue.

Real Estate

Real estate companies use location data to make better investment decisions. By analyzing property values, surrounding amenities, and future development plans, they can find high-potential areas to invest in. 

This data also helps assess a location’s risk factors so companies can make informed decisions that yield long-term returns.

Telecommunications

Location data is key to network expansion and optimization in the telecom industry. Companies use this data to find areas of high demand for services, allowing them to reach new audiences and provide coverage. 

By analyzing geographic trends, these companies can place cell towers and other infrastructure in the right places to maximize service quality and customer satisfaction.

Enhancing Business Operations and Customer Experience

Location data is key to business operations and customer experience. By using this data, companies can refine processes, better target customers, and gain a competitive edge.

Here’s how:

• Improving Business Operations: One major advantage of location data is its ability to optimize supply chains. Businesses can use this data to identify the most efficient delivery routes, helping to cut down on both delivery times and costs. For example, a company can analyze geographic constraints to ensure timely deliveries and minimize disruptions. This level of precision in supply chain management means better resource allocation and higher operational efficiency.    
  
• Competitive Intelligence: In today’s competitive landscape, understanding where your competitors operate and how they perform is essential. Location data gives insights into competitor activity, helping businesses identify market gaps and capitalize on them. By analyzing the locations of competing stores, companies can strategically position themselves in underserved areas, capture market share, and attract new customers.
  
• Operational Enhancements and Customer Experience: The advantages of location data extend beyond internal operations. Ride-sharing companies like Uber use location data to optimize driver routes, ensuring timely and efficient service for customers. Similarly, food delivery services use this data to connect customers with nearby restaurants, resulting in quicker deliveries and a better dining experience.

Challenges and Solutions in Location Data Usage

As businesses opt in and rely on location data for decision making, they face several challenges that can impact the quality and reliability of the data. Understanding and addressing these challenges is key to using location data successfully.

Data Accuracy

One of the biggest challenges with location data is ensuring accuracy. Inaccurate or out-of-date data can lead to bad decisions and costly mistakes. 

While open source data such as OpenStreetMap (OSM) is attractive due to its low cost, the quality can vary significantly. This can result in issues like fabricated or wrong points of interest, missing data points, and outdated information.  

These inaccuracies can derail your business strategy, making reliable data essential for any organization.

Privacy

With more companies using location data, concerns around data privacy are growing. Organizations must navigate complex regulations and ethical considerations to ensure that the data they use respects individuals’ privacy rights. 

This means implementing robust data governance and adhering to GDPR regulations, which dictate how location data is collected, stored, and used.

Integration Complexity

Integrating location data from multiple sources is a big challenge. Different data sets can use different formats, schemas, and standards, so combining and analyzing the data is challenging. This complexity prevents organizations from getting a complete view of their operations and market.

OSM Data vs. Paid Data

Open source data sources like OSM offer but often lack consistency and timeliness. If you buy location data from dataplor, these challenges are solved. Paid data providers ensure accuracy, quality, and up-to-date information through advanced technology and rigorous quality control measures. 

For example, dataplor’s proprietary machine learning algorithms and human validation processes ensure that the data is precise, current, and reliable.

How dataplor Solves These Challenges

dataplor offers real-time, globally scaled location data that solves businesses’ biggest challenges. The data we provide is accurate, current, and validated by local experts to meet the highest standards.

By combining technology with human expertise, dataplor provides a robust solution that helps organizations overcome the challenges of using location data to confidently make informed data-driven decisions.

Fuel Data-Driven Decision Making with dataplor

When used effectively, location datasets can unlock new opportunities, optimize operations, and drive long-term growth. 

Using accurate, real-time location data, companies can make informed decisions that improve customer experiences, streamline logistics, and get ahead of the competition. Integrating location data into your business can offer significant advantages, from finding the best retail locations to optimizing supply chains.

Working with dataplor gives you location intelligence solutions tailored to your needs. With a focus on data accuracy and quality, dataplor provides your business with the necessary tools to navigate complex markets and make impactful decisions

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Technology is transforming the way companies are growing, especially through the use of location intelligence. At dataplor, we empower many of the world’s largest companies by delivering real-time, accurate location data. This valuable geographic information can be used to fuel advanced technologies and data systems across a number of industries.

By integrating diverse data sources into their business intelligence systems, companies can elevate their location analytics and data visualization capabilities. This enriched business data enables more effective marketing campaigns and resource optimization, ultimately leading to better decisions across the board.

What is Location Intelligence?

Location intelligence is gained by analyzing geospatial data collected from various sources like GIS, satellite imaging, drones, census reports, and more. While this process can be time-consuming and complex, dataplor simplifies it by streamlining the data collection and delivering relevant point-of-interest data directly to your business. With this information in hand, your data analysis team can easily identify marketing and retail opportunities as well as new possibilities across various industries.

Applications of Location Intelligence Solutions

Location data holds the key to unlocking smarter business strategies across various sectors, including retail, healthcare, real estate, insurance, and more. This data-driven approach facilitates informed decision-making and maximizes revenue through several use cases:

• Mapping: Location intelligence enables GIS and other spatial data technologies to create intuitive dashboards and visualizations, helping to identify patterns and potential relationships within and between locations.
• Site Selection: Insights from geographic data allow organizations to assess the pros and cons of potential real estate locations, optimizing their site selection for competitive advantage.
• Competitor Investigation: Gain a deep understanding of the competition to identify market opportunities and areas to target.
• Supply Chain Optimization: Use location data to optimize logistics, distribution, and inventory management.
• Risk Assessment: Identify potential risks by considering factors like ROI forecasting and fraud prevention.
• Customer Segmentation: Customize product promotions and offerings tailored to consumer demand based on location data. 
• Real Estate Valuation: Determine property values based on location-specific factors like proximity to amenities, schools, and transportation.
• Urban Planning: Forecast which areas are most likely to see substantial growth, and predict the best areas for development.

Comprehensive Location Insights From dataplor

As a leading provider of global location intelligence, dataplor utilizes advanced machine learning, image recognition, and artificial intelligence technologies to examine vast arrays of data across more than 250 million locations in over 200 countries and territories. This commitment to quality ensures that you can make well-informed, data-driven business decisions. Our international team of analysts and human validators leverage their local experience and language fluency to maintain high data accuracy, reduce errors, and identify duplicates in real-time.

Reach Out to Our Experts for More Information

Partner with a provider committed to giving you a competitive edge. dataplor is your global partner in location intelligence, helping your business optimize customer experiences, improve supply chain functionality, and enhance financial services through our accurate Point-of-Interest (POI) data. Our industry-leading quality control procedures ensure you receive highly accurate and relevant location data that you can trust. Contact our experts to learn how our data can strengthen your business strategy and support data science initiatives, urban planning, CRM, IoT applications, pricing strategies, and more.

After months of debate and anticipation, California’s minimum wage law for fast food workers, signed into law in September 2023, officially took effect in April 2024. This significant policy change, which raised the minimum wage for fast food workers to $20 per hour, sparked widespread concern about its potential impact on the state’s Quick Service Restaurant (QSR) industry. With predictions of a wave of closures as restaurants struggled to manage the increased labor costs, the question on everyone’s mind was: what has actually happened since the law came into force?

By analyzing our Point-of-Interest (POI) data, we’ve uncovered a nuanced picture of the situation. Our findings not only shed light on the impact of the wage increase but also reveal the broader economic forces influencing the industry.

Initial Impact: September 2023

When the QSR minimum wage law was signed in September 2023, the data showed a notable decrease in dining POIs in California— nearly three times greater than what was observed in comparable states. Specifically, the monthly percent change of dining closures in California in September 2023 was 71%, while similar states experienced only a 25% increase in closures. This sharp decline immediately raised concerns, suggesting that the new law might be having a swift and adverse effect on the industry.

However, it’s essential to place this data in context. Fluctuations in closure rates were already occurring before September, pointing to other underlying factors influencing the QSR landscape in California. For example, in May 2023, we observed significant variations in closure rates, which may have been driven by broader economic pressures such as the Federal Reserve’s rapid rate hikes, negative net migration, and local economic challenges. These factors suggest that the QSR industry was already navigating a complex economic environment, making isolating the wage law’s impact challenging.

Post-Law Implementation: 2024 Trends

As the minimum wage law took full effect in April 2024, many expected another sharp increase in QSR closures. Indeed, our data confirms this expectation: closures in California surged by 80% from March 2024 to April 2024, a stark contrast to the same period in the previous year, where closures decreased by 80%. However, this trend was not isolated to California; comparable states across the country also experienced a rise in closures during this period. This parallel suggests that broader national economic conditions, rather than the wage law alone, played a significant role in driving these closures.

Looking beyond the immediate impact, the data reveals that by late 2024, closure rates in California have begun to align closely with those in peer states. This trend indicates that while the initial shock from the wage increase was real, it may have been absorbed or overshadowed by other factors over time. This alignment suggests that the wage law’s impact must be viewed within the larger context of national economic trends that have influenced the industry as a whole.

Broader Economic Context

National economic factors, such as rising inflation rates and shifts in labor market conditions, have likely compounded the challenges QSRs faced in California and nationwide. For instance, the monthly change in closures from January to March 2024 was 124%, compared to an 89% increase during the same period in 2023. These figures highlight the significant influence of broader economic pressures, which may have had a more substantial impact on closures than the wage law itself.

Our analysis also reveals similar trends in other states that did not implement a wage increase, reinforcing that the broader economic environment played a crucial role in shaping the outcomes we observed. When comparing data from wage-increase states to those without such changes, it becomes clear that macroeconomic forces likely had the most significant influence on closure rates across the board.

The data shows that while California’s QSR minimum wage law had an immediate impact on the industry, the broader economic environment played the most significant role in shaping the trends we observed. The patterns in California mirror those seen across the country, highlighting that macroeconomic factors were the primary drivers behind the changes in the QSR sector. Despite the initial shock of the wage increase, restaurant employment in California is only slightly worse than in comparable states over the entire year. This underscores the dominance of more significant economic trends in determining the industry’s trajectory.

Looking Ahead

As we continue to monitor the impact of wage policies on industries like QSRs, it will be crucial to consider these findings within the broader economic context. Future research should focus on analyzing the long-term effects of these policies, as well as the influence of technological changes and other factors that may shape the industry’s future. 

Our data-driven analysis underscores the importance of understanding the complex interplay between policy changes and macroeconomic forces, providing critical insights for the QSR industry and policymakers as they navigate these challenges. Staying informed with up-to-date data will be key to making sound, strategic decisions.

Are you interested in learning more? Contact dataplor to connect with our data experts today.