There has never been a better time to capitalize on mobile marketing. As of this year, 86% of the global population uses a smartphone—a whopping 6.92 billion people. In the United States alone, Americans spend an average of nearly five and half hours per day on their mobile devices. 

Advertisers poured $336 billion into mobile ads last year, feeding a booming industry and buying access to an unprecedented level of consumer targeting. To realize the potential impact of mobile ads, siphoning location data from individual devices and their proximity to points of interest (POI) in the outside world is an essential requirement. In fact, location data underpins the entire mobile marketing machine. 

For brands who are looking to reach highly targeted audiences on a global scale, we’ll explore different forms of mobile advertising and the role location data plays in making them all possible. In particular, we’ll focus on the location data-driven mechanisms of geofencing marketing, covering its benefits and use cases for mobile advertisers.

What is geofencing marketing?

Mobile advertising offers targeting on a granular level by displaying advertisements on a consumer’s smartphone or other personal devices. Operating on data extracted from a consumer’s mobile device, this form of marketing allows advertisers to connect with their target audience based on signals that include a consumer’s behavior and geographic location. This individualized targeting ensures that advertisers are reaching the right people and optimizing their ad spend.

There are myriad ways to reach consumers on their mobile devices, including display, interstitial, native, and video ads. Depending on the app, consumers may also be served in-app advertisements. However, location-driven advertising takes mobile ad impact a step further. Geospatial insights enable companies to deploy geotargeting, geofencing, and even geo-conquesting campaigns that can attract new customers and boost return on ad spend (ROAS). 

Geotargeting allows advertisers to reach consumers based on the location of their mobile device. This targeting occurs on a high level, such as the device’s city, zip code, or IP address. It is a more general approach to location-based advertising that helps advertisers target consumers within a specific market. It’s important to understand that geotargeting and geofencing are not the same.

Geofencing advertising is an approach to mobile marketing that is confined to spatial boundaries in the physical world, placing an invisible perimeter around a specific point of interest (POI) and serving ads on devices within it. Similarly, geo-conquesting uses spatial boundaries around a competitor’s location to target devices—which belong to customers—within a given perimeter. 

In the case of geofencing marketing, POI data is critical. POI is a specific category of location data that reveals information about physical places, including stores, restaurants, and landmarks. This helps advertisers build footprints for their target audience, identifying POI that are relevant to their brand or product and running ad campaigns nearby. 

How geofencing benefits advertisers and brands

Advertisers benefit from geofencing by delivering messages to the consumers they want to reach, based on that consumer’s proximity to a physical place. For example, a CPG brand could use geofencing to serve ads to shoppers in a grocery store. This ensures that ad spend is being dedicated to consumers who have a greater likelihood to convert. 

Given the current state of the economy, some advertisers may need to run campaigns to offload excess inventory. A fashion retailer may decide to run a geofencing campaign within the spatial boundaries of their store, giving a discount or limited offer to customers in real-time and helping to sell the overstocked product. 

Additionally, geofencing can help advertisers outperform competitors by way of geo-conquesting, which applies the principles of geofencing to a competitor’s physical location. Through geo-conquesting, brands can serve ads to potential customers whose devices are seen in proximity to a competitor’s space in hopes of winning their business with tantalizing promotions. 

How to make the most of geofencing

If Popeyes Louisiana Chicken, an American quick-service restaurant (QSR) chain, decided to run a series of geofencing advertising campaigns in southeast Asia, gathering location intelligence would be an essential first step. This includes POI that its target customers might frequent—for example, a shopping center in Jakarta, Indonesia—as well as competing QSR locations in the larger region. 

However, knowing where these complementary and competing POI are located would not complete the puzzle for Popeyes. The QSR chain would also be interested in evaluating activity around these POIs over time, helping them understand which geofenced areas to prioritize for ad spend.

By gathering this location intelligence, Popeyes increases the likelihood that their geofencing advertising campaign will yield the desired results—generating new or repeat customers, and even luring customers away from their competitors. 

Let dataplor unlock tailored data and advertising 

While geofencing appears at the surface to be a no-brainer marketing strategy, its success hinges on the quality of the location data informing it. This is especially true for international markets, where POI data is notoriously inaccurate, and for companies who rely on open source data, which is susceptible to errors and outdated information.

Circling back to Popeyes’ plans to run geofencing campaigns in southeast Asia, low-quality location data could result in thousands, if not millions, of dollars in wasted ad spend. For example, If Popeyes thinks it is targeting a series of American retail brands who share common customers with the QSR chain, but those physical retail stores shut down months ago, Popeyes is paying a hefty price tag to target data that doesn’t exist.

Fortunately, there is a solution for brands who want to shore up their investment in geofencing and mobile marketing. dataplor serves as a global location intelligence partner, using polygons that are more in tune with client demand and tailored to customer needs. These polygons are drawn using dataplor’s proprietary AI and machine learning approach, making them both scalable and competitively priced.

Additionally, dataplor offers the most accurate international POI data on the market, positioning the platform as the only industry player that can provide truly global polygons for geofencing and geo-conquesting campaigns.

Yeme Tech’s Community Platform is a powerful application that utilizes spatially mapped Human, Asset, and Activity data to provide profound local insights into communities. By leveraging this information, Yeme Tech empowers developers, community stakeholders, and others to take action toward creating positive social impact through enhanced interaction, engagement, and cohesion. Yeme Tech’s platform not only provides valuable information about the places around us, but also facilitates new ideas to improve our communities.

Yeme Tech relies on having the most accurate geospatial data to support its platform’s functionality and users. Prior to using dataplor for its location intelligence needs, the company had relied on open-source data and Google Places for their Point Of Interest (POI) data. However, these sources proved unreliable and costly, making it difficult to analyze the data and grow the platform into new areas.

The Challenges with Google Places and Open-Sourced POI Data

Yeme Tech faced several challenges with the open-source data they were using previously. The data was unstructured, decentralized, and complicated, requiring a lot of legwork to compile and analyze. Additionally, there was a considerable margin of error associated with validation and replicability for other projects and locations. This made it nearly impossible for Yeme Tech to provide their customers with accurate analysis and develop its community enhancement platform.

Yeme Tech then turned to Google Places as an alternative data source. However, this approach was not scalable due to the very high and unpredictable costs. The updates provided by Google Places were not recurring which made it difficult to grow into new areas. This resulted in Yeme Tech spending a considerable amount of time scraping multiple sources and compiling data in a usable format.

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The Solution: dataplor’s POI Data

To overcome these challenges, Yeme Tech needed a data provider that could offer accurate, comprehensive, and up-to-date global data to support their mission of creating walkable and sustainable cities. After extensive research and trials, Yeme Tech chose dataplor as its data provider.

dataplor’s expertise and support were one of the key factors in Yeme Tech’s decision to choose them as their data provider. dataplor’s proven strategies for collecting and verifying data gave Yeme Tech confidence that they could continue developing their community enhancement platform with reliable and up-to-date information. Additionally, dataplor’s breadth and depth of data allowed Yeme Tech to plan for future scalability.

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The Benefits of dataplor’s POI Data

Using dataplor’s POI data, Yeme Tech has been able to integrate valuable insights into its platform. dataplor’s POI data has allowed Yeme Tech to advance their work of creating a 15-minute Walkable Fulfillment benchmarking tool. They have also used dataplor’s POI data in a series of consultancy projects, leading to transformational insights related to community engagement consultation analysis and business emissions, among others.

Alejandro Quinto, Head of Innovation at Yeme Tech described their experience with dataplor stating “In creating a profound new Community Enhancement Tool, we recognised the importance of accurate, place-based asset data to our entire proposition. The quality, detail and format of this was critical to achieving our objective of a globally significant and market-leading platform. It has been fantastic working with dataplor as their culture of exploration led to a co-creation approach being developed. Their expertise and resources allowed us to be able to create valuable metrics in order to gather valuable insights and make informed decisions based on accurate and up-to-date information. Their commitment to quality and support has been essential in ensuring the success of our data-driven proposition.”

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One of the standout features of dataplor’s POI data is the asset categorization that identifies the different attributes of the POIs, enabling Yeme Tech to sort through the data easily. Additionally, Yeme Tech appreciates flexible approach to licensing.

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Looking Forward

Yeme Tech is a leader in community enhancement for cities and governments, and dataplor is excited to support their mission to expand into new areas throughout the globe. Yeme Tech plans to continue using dataplor to support their upcoming initiatives for developing a comprehensive and standardized social benchmarking tool capable of empowering citizens and businesses to take a bottom-up approach in leading social transformation of communities.

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Yeme Tech’s partnership with dataplor has enabled them to provide consistent, accurate, and thorough insights into places globally. dataplor’s POI data has given Yeme Tech the confidence to develop their community enhancement platform with reliable and up-to-date information. dataplor’s expertise and support, combined with their comprehensive and cost-effective data coverage, have made them the ideal partner for Yeme Tech’s mission to create walkable and sustainable cities.

dataplor Partners with StateBook to Provide Comprehensive Economic and Location Data for Every US Community

dataplor, the top global geospatial data company specializing in points of interest, and StateBook, the leading provider of comprehensive, visualized economic market insights in the United States, are partnering to provide their customers with even more powerful location intelligence. 

Retailers, CPG brands, financial institutions, tech companies, third-party logistics providers, and more rely on dataplor to understand where competitors and complementary businesses are located, select new sites, and identify markets ripe for expansion. Thanks to the StateBook partnership, dataplor will provide more users with tailored datasets that unlock insights into strategic investment, project viability, and risk mitigation across multiple geography levels and over time.  

The partnership with dataplor enables StateBook to add best-in-class POI data to its existing complement of  32 billion data points, enabling its customers to access insights and trends around the nation’s workforce, wage rates, industries, infrastructure, taxes, demographics, and more. 

“The partnership with dataplor equips our customers with the deepest, most accurate geospatial view of US markets available,”

said Calandra Cruickshank, founder and CEO of StateBook,  adding that StateBook also recently added real-time mobility insights from cell phones to its arsenal of data, along with risk, resilience, and impact data. StateBook’s customers span real estate investors and developers, Fortune 500 companies, government agencies, insurance companies, and other technology companies. 

“We’re excited to formally kick off our partnership with StateBook,” said Geoff Michener, dataplor CEO and co-founder. “POI data has never been more relevant to growth as businesses across verticals aim to identify the surest possible paths to expansion in a tough macroeconomic environment. With dataplor’s POI data and StateBook’s socioeconomic data insights, brick-and-mortar businesses will be able to confidently select the sites where they are most likely to grow.”

dataplor sets itself apart from other geospatial data companies through its exclusive focus on POI data and its industry-leading data verification process. Much location data is inaccurate, owing to poor open-source data verification methods and differing records across sources. dataplor employs machine learning to deduplicate records, AI call bots to confirm local business information, and local human experts to provide clarity in ambiguous cases. 

Over the past year, dataplor has grown to cover more than 100 million POIs in over 200 countries and territories. Its coverage of POIs in the US is second to none. 

As the leading provider of trusted socio-economic data for location intelligence, StateBook enables its customers to gain information advantage with actionable insights. Fortune 500 companies, real estate investors, banks, insurance companies, and communities use StateBook data to identify the most strategic opportunities for investment, reduce risk, increase resiliency and optimize for success. StateBook also licenses its data to enable technology companies to deliver timely, flexible, intuitive market data to their customers.

For companies that want to scale globally, having the right data is crucial. But inaccurate insights often come with a hefty price tag. Years ago, for example, IBM estimated that bad data was costing businesses upwards of $3 trillion per year. A more recent study by Gartner reports that companies lose around $12.9 million annually due to flawed analytics.

These figures are a wake-up call for organizations looking to cash in on location data. While these datasets provide global insights about consumer buying habits, market trends, and competitor activity, they’re often inaccurate—particularly on the international level.

To harness the power of geospatial data at scale, it’s important to have records that are updated regularly. Unfortunately, it’s difficult to find data providers that do so. Let’s dive into how and when location data providers tend to update their datasets, the benefits of data that’s updated in near real-time, and how dataplor provides its customers with just that.

How and when do location data providers update their records?

While inexpensive or free open-source location data may seem like a good deal for companies upfront, the cost of using inaccurate, biased, or outdated data sources can be astronomical. The US Census Bureau, for example, runs the census only once every 10 years. Similarly, open-source data source OpenStreetMap has succumbed to corporate bias in its data. These issues create significant risk for companies who are using these sources to make critical business decisions.

While governments provide a valuable public service by gathering and publishing data about their constituents, the slow-moving wheels of bureaucracy simply cannot meet the needs of fast-moving, rapidly growing companies today—at best, these providers update their data every 90 days. Relying on location data from public providers is an unreliable route for businesses. 

On the other hand, openly-sourced data can be updated in real-time by “volunteer” contributors. However, exclusively collecting user-generated location data leaves these sources vulnerable to inaccurate and biased information—especially in international markets. In tech, the expression “garbage in, garbage out” refers to the reciprocity of input and output: if flawed information goes in, then the natural result is that flawed data will come out.

This doesn’t mean that open-source data providers can’t fix inaccuracies and adjust for bias. They can—but it isn’t a quick process. These providers tend to update faulty data manually, which proves a timely and labor-intensive effort that, again, cannot keep pace with the demand of fast-growing companies. Coupled with the potential for a significant loss on investment based on low-quality data, companies should not lean on open-source data providers to make important decisions.  

What are the benefits of data updated in near real-time?

Companies need to strike a balance between the frequency of location data updates and the quality of that output. This can be achieved through the use of location data that is updated in near real-time, made possible by a geospatial data provider that offers both comprehensive collection and rigorous verification processes.

When armed with location data that is updated in near real-time, businesses can unlock accurate competitive intelligence about customers and competitors, make smarter site selections, and develop targeted marketing. The key is point of interest (POI) data.

A POI is any physical site that might be of interest to individuals, companies, and decision makers, including brick-and-mortar stores, restaurants, and malls, but also national parks, monuments, and other landmarks. POI data helps companies see a clear picture of the market landscape in the area they’re targeting.

For example, Chik-fil-A is investing $1B into market expansion in Europe and Asia. Each market is unique by country, region, and city, and Chik-fil-A needs up-to-date, accurate location intelligence to evaluate competitors and market opportunities, as well as make decisions about site selection. 

Let’s say that, as Chik-fil-A homes in on expansion plans in Spain, the company believes that the Catalonia region and, specifically, the city of Barcelona will be a strong market for a QSR location. The expansion team knows that buildings designed by architect Antoni Gaudí draw large numbers of international tourists. 

The team wants to choose a nearby site that will bring in the most business. However, they need to evaluate the presence of competing QSRs and their proximity to the POIs that Chik-fil-A is targeting. The team can’t learn about the footprint of their competitors through 10-Ks, as no company publicly shares its sales data, nor about how those competitor QSRs are growing over time. Location data, however, makes it possible to compare similar—and highly accurate—location datasets over time, allowing the team to estimate how many people are visiting a competing location each month. This intelligence paints a picture of the QSR market landscape in Barcelona and enables Chik-fil-A to be more strategic about site selection.

Additionally, POI data has beneficial applications for Chik-fil-A’s marketing team. By discovering areas with tourist attractions, shopping, and other relevant landmarks, Chik-fil-A can better identify opportunities for out of home (OOH) advertising, such as billboards or digital signage, as well as geo-targeted digital advertising. Location data helps the marketing team carve out geographic sections of Barcelona where their advertising could be most effective. 

What makes dataplor’s process and product so unique?

Opening new QSR locations in multiple international markets is a large and expensive feat. Companies like Chik-fil-A can’t afford to hedge a billion-dollar bet on location data that is low-quality, out of date, or flatly incorrect. Because international location data is notoriously unreliable, companies should partner with a trusted geospatial data provider to get the insights they need and increase their odds for success. 

dataplor’s enterprise-level approach excels beyond industry standards, factoring in the needs of rapidly growing companies and the demand for high-quality, verified location data. dataplor’s data collection and enhancement processes are based on a machine learning observation system, which actively monitors records to detect changes to a business’ physical address, hours of operation, phone number, website, and more. 

Additionally, dataplor is the only geospatial company that specializes in international markets, employing a global network of human validators in more than 200+ countries and territories. Using best-in-class tech to optimize global data collection and enhancement, and leveraging humans for last-mile verification, dataplor offers the most accurate and up-to-date location intelligence on the market.

If you’re ready to scale your business globally, find out how you can use location data to ensure your success in international markets. Contact us today at contact@dataplor.com.

Unprecedented Access to Over 200 Million POIs in 200 Countries & Territories for Comprehensive Places Data

dataplor, the leading provider of Point of Interest (POI) data for enterprises worldwide, has announced its latest expansion, with coverage now extending to over 200 million POIs across 200 countries and territories. This is the most extensive coverage offered by any provider in the industry.

dataplor’s success lies in its multi-step data collection and verification process. By working with local experts to vet geospatial data, the firm closes gaps in machine errors with boots-on-the-ground verification. dataplor’s frequent and dynamic updates enable users to gain improved visibility into poorly mapped business geographies that are not accessible through other providers. 

Empower Your Data-Driven Decisions with Accurate Location Intelligence at a Global Scale

Accurate and comprehensive POI data is essential for organizations seeking to expand their business operations in developing markets. This data allows businesses to make informed decisions about site selection, optimize their operations, tailor their marketing strategies to specific audiences, and identify opportunities for expansion in new markets.

Tracking places attributes such as the location, open close status, operating hours, classification, dwell times, and more, dataplor paints a picture of hyperlocal markets to reveal broader trends. POI data can uncover holes in local brick-and-mortar economies, highlighting regions where retailers or consumer packaged goods companies can increase sales and marketing efforts. POI data also reveals which chains and brands are growing or receding in certain areas, painting a clear picture of global competitive intelligence.

dataplor is putting businesses on the map in international markets and lighting the way for companies looking to establish themselves abroad. The world’s largest tech, CPG, and financial services companies rely on dataplor to understand global markets by processing comprehensive data, which leads to a better understanding of the target area and enables more effective market analysis.

Sustainable Expansion with Uncompromised Data Quality: dataplor’s Strategy for Continuous Growth

With its comprehensive coverage and meticulous upkeep, dataplor is set to continue growing while maintaining its position as the industry leader in POI data. The company plans to extend its coverage by 20% by the end of 2023, ensuring accuracy across all locations with the support of an expanding team. dataplor’s commitment to maintaining accurate information in diverse markets is evident in its success, with the world’s largest tech, consumer packaged goods, and financial services companies relying on its data for global growth strategies.

Location data is one of the most powerful tools businesses can use to gain insights into customer behavior and make informed strategic decisions about logistics, site selection, advertising, growth opportunities, and efficiency. But location data can only make a difference when it’s accurate and on point. 

Poor-quality location data can lead to missed opportunities, wasted resources, and incorrect insights. In this post, we’ll discuss the three essential criteria to consider when evaluating location data quality, so that you can confidently use location data to drive your business forward.

✓ Credibility: How credible is the data you use? Location data can fail to meet this criteria in a number of ways, from data collected without proper consumer consent to data marred by collection devices or processes with technical issues. The key here is to know a) if the source of the data is credible and b) if the processes used to collect it are trustworthy.

✓ Quality: Are you using high-quality data? It’s vital to make sure that the data you use has high confidence scores, is free of duplications, and is up to date and accurate. 

✓ Usability and applicability: Are you confident assessing what your data can (and cannot) tell you? Do you know where and how to leverage it to drive growth? The essential point here is to identify where location data can boost your business and what the best practices are for evaluating what it’s telling you. 

Let’s take an in-depth look at each of these criteria and see how they can help your business leverage trustworthy and accurate location data.

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The importance of credible data

Data credibility is all about trustworthy sources and methods. For example, if data is not anonymized or protected appropriately, it may be compromised, leading to data breaches or misuse. Given this, how can you be sure that your data vendors are engaging in best practices by protecting consumers’ privacy and avoiding biased or cherry-picked datasets?

One way is to verify your data vendor’s privacy practices by ensuring that they are transparent about their collection sources and methods. For the datasets in question, have consumers been asked for their consent to be tracked? Some mobile apps, for example, may collect location data in the background without explicitly informing users or receiving their consent, potentially exposing sensitive information about their daily routines and behaviors and raising legal concerns. 

Moreover, data privacy can become a heated public issue that puts pressure on vendors. As consumers become increasingly aware of the potential risks and ethical concerns associated with location data, they are more likely to scrutinize the practices of location data vendors and demand greater transparency and accountability. This scrutiny, in turn, can lead to media attention and regulatory action. 

For these reasons, businesses should check that their data vendors employ ethical and transparent standards and engage in best practices to ensure that they have a data partner they can rely on. 

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The value of high-quality data

Credibility is about assessing the trustworthiness of the data source and its methods; data quality is about the caliber of the datasets themselves. Are there errors, duplications, or inaccuracies that can lead to problems down the road, like showing a distorted picture of a city or neighborhood? 

One area where quality can be a big issue is international location data. For example, consider the case of a QSR that is looking to expand from the U.S. to Mexico and turns to geospatial intelligence to inform its decision-making. As the QSR looks for sources of data, some important questions to ask include: does the data come with metadata, confidence scores, or similar indicators? Does it contain inaccuracies and need to be enhanced? For instance, when dataplor recently sampled INEGI records for Cancún, we found that 91% contained some form of inaccuracy. Only by catching these errors ahead of time could the QSR avoid wasting time and resources. 

While it’s possible for companies like the QSR to fix this data themselves, it’s usually more cost-effective to buy accurate data upfront. One way that dataplor ensures the accuracy of its international data is by using trained human validators with local expertise to work in tandem with its AI processes. Validators anticipate and catch issues like cultural differences in address structure or language variations like wordplay in business names. This real-time, on-the-ground feedback mechanism enables dataplor to identify duplications and errors, enhance their data, and offer clean and actionable datasets for business to use and realize results out of the gate. 

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The power of actionable data

Once you’ve established that your data is credible and high-quality, the final step is determining what you can — and cannot — do with it. It’s essential to have processes in place, and/or to work with a data services provider, who can help you understand what the data is actually telling you, so that you can leverage it for maximum effect. 

For example, let’s consider a retail company that is looking to expand its business internationally. They have access to data from their existing stores, but is this data of the appropriate scale? Are there enough data points to draw meaningful conclusions about consumer behavior and preferences in a new market? Additionally, consider whether the data provides global coverage. A business looking to start a new location in the Palermo neighborhood of Buenos Aires needs to be sure the datasets it’s using accurately reflect the area. The business can’t just rely on guesses about international locations based on more complete data in markets like the US and Canada that are easier to cover. 

Furthermore, companies need to be honest about their goals for using data. What do they hope to achieve with the data? Do they need additional datasets to complete their insight puzzle? For instance, a retail company might have point-of-interest (POI) data, but they may require additional mobility and demographic data to make optimal decisions about site selection for new stores. By understanding what the data can and cannot tell them, and what additional data they might require, companies can make better-informed decisions that facilitate growth at scale.

Location data is one of the most valuable tools a business can have to shape decision-making about the future, map the competition, and find or enhance pathways to growth. But much of the location data available for purchase is of poor quality and can be more damaging than helpful. By evaluating the credibility, quality, and actionability of location data, companies hoping to use it to grow can set themselves up to do just that.

dataPlor will join hundreds of the world’s top CPG brands, retailers, and technology providers at the 2023 Shoptalk Conference in Las Vegas, NV. Shoptalk, which will be held at Mandalay Bay from March 26–29, brings more than 10,000 industry professionals together to build relationships and learn about the most exciting innovations in retail.

While e-commerce continues to thrive after its explosive growth during the pandemic, in-person retail is still more deeply ingrained in day-to-day consumer life. According to research compiled by Zippia, nearly 40% of consumers make at least one in-store purchase per week, compared to 27% who make an online purchase. 

As brick-and-mortar shopping continues to dominate, dataPlor enables brands and retailers to create geo-targeted advertising experiences; discover beneficial brand-retail partnerships; conduct regional, national, and international site selection research; and gather competitive intelligence through the power of location data. 

Location data provides insight into consumer behavior, points of interest (POI), and market competition that both brands and retailers need to make critical business decisions and design high-ROI advertising campaigns. From a smaller, regional company to a top 10 international brand, location data can help any CPG or retail business grow at scale by enhancing market research, advertising, and expansion strategy. 

An apparel retailer would need precise location data to grow abroad, for example. They’d need to know where customers, competitors, and other supply chain partners are—and to gain this knowledge, they’d need international data that is comprehensive, accurate, and up to date. 

In this example, dataPlor’s POI data can provide a clear picture of both the client and their competitors’ presence in international markets, help them identify new distribution channels, and enable them to allocate resources to gain market share and decrease waste.

dataPlor would love to meet with Shoptalk attendees who are curious about using location data to scale their retail operations. Stop by dataplor’s booth #1719, or pick a time that works best for you to meet with us at Shoptalk.