Big Data hyperlocal data IoT Tech

The Increasing Need for Hyperlocal Data Collection

hyperlocal data collection

The ability to collect and harness big data has transformed businesses worldwide. This process, which is continually improved by data scientists and companies that heavily invest in big data, has allowed for dramatic changes to numerous industries. The benefits of using big data include improved processes, data-driven business decisions, and better resource allocation. Here is the increasing need for hyperlocal data collection.

While conversation often surrounds how to use big data, the use of hyperlocal data has also gained attention.

Hyperlocal data refers to a more niche version of local data. A zip code, for example, is an example of local data, but a street address is hyperlocal data. It’s more specific and tends to surround a very particular, defined geographic area. This data is more difficult to collect, but its uses in business are growing.

Hyperlocal data benefits businesses

There are more obvious uses for hyperlocal data for businesses that rely on Google Maps or location-based services. A food delivery company, for example, would benefit from having more addresses and exact locations of restaurants in a particular area because they can then offer customers more unique choices, gaining an edge over their competition.

Google Maps itself also benefits from this data because the company can offer more accurate, up-to-date information to users, including directions and nearby locations.

Both marketers and advertisers use hyperlocal data to hone in on local customers. Near-me searches have risen in popularity, and marketers are capitalizing on these searches to get customers into local stores and restaurants.

Instead of focusing on a potential customer that may come to the area later, these campaigns focus on customers that are already in the vicinity. Of course, marketers must also focus on strong Google My Business listings and SEO to beat out the competition fighting for the top spots on search engines.

Hyperlocal data has a place in a traditional business or finance setting as well. A company applying for a loan may overstate its value. Hyperlocal data can capture accurate information such as credit cards accepted, hours of operation, number of employees, etc. All of this information is necessary for financial institutions that want an accurate portrayal of a business. However, there are far more uses for hyperlocal data than just this.

Hyperlocal data and Covid-19

With the world battling a pandemic, many have turned to hyperlocal data to track the spread of Covid-19. By mapping out global cases, experts have been attempting to take a worldwide view of how the virus has spread and its impact on businesses.

More importantly, they want to look at areas that have begun to flatten the curve so that other affected areas can mimic their efforts. Of course, none of this is possible without hyperlocal data that tracks infected populations. This data will play a key role in both curbing the spread and creating lessons to draw from in the future.

Hyperlocal and IoT use cases

What is particularly interesting is how hyperlocal data can benefit the Internet of Things. With improved mobile technology, people are constantly creating data. Now, more than ever, people are sharing this data for the benefit of others. Take traffic reports, for example. There are apps where users can report accidents, and delays, which helps others traveling in the vicinity.

The report is given to a GPS application, which can then reroute drivers to avoid sitting in long delays. It’s even expected that self-reporting will soon become unnecessary as AI will become sophisticated enough to collect hyperlocal data without user input.

Connected cars have grown in popularity and will soon play a substantial role in hyperlocal data collection and distribution. Equipped with smart sensors, this type of car could report weather information to a cloud service, which could then alert others in the area.

If there is a severe storm or ice on the road, other travelers would know about it, assuming they are in connected vehicles themselves. Hyperlocal data can power IoT simply by offering larger amounts of accurate data.

Hyperlocal data moving forward

The challenge of data collection, particularly in emerging markets, is one hindrance to this movement. While data is readily available in developed cities, data in underdeveloped locations is not as easily accessible. This data, however, is growing in its value as more global companies seek to enter these markets.

There are solutions to this problem of gathering data in underdeveloped markets, and big brands are starting to vie for this data as it directly impacts expansion plans.

Image Credit: Anna Shvets; Pexels

The post The Increasing Need for Hyperlocal Data Collection appeared first on ReadWrite.

Data and Security IoT location intelligence Smart Cities

How Location Intelligence Will Create Even Smarter Cities

location intelligence smart cities

Location intelligence has gained much attention lately, especially as more businesses harness the power of this technology. Location intelligence builds on geographical information systems (GIS) tools, and its definition goes beyond the analysis of geospatial or geographic information. Here is how location intelligence will create even smarter cities.

Location Intelligence is the ability to visualize spatial data to identify and analyze relationships and trends.

The output of location intelligence is actionable insights that help both the public and private sectors to detect patterns and make strategic decisions.

Location intelligence comes from a multitude of sources, such as GPS systems, Internet of Things (IoT) data, and environmental and consumer sources. The technology is not one specific tool but rather the ability to use geospatial data to create business insights. As location intelligence grows in popularity, because its uses are multiplying, it has had an impact on an interesting global technological development: smart cities.

Location intelligence use cases.

Before diving into the implications of location intelligence on smart cities, it’s important to take a step back and look at where this technology has already made an impact.

The insurance industry.

The insurance industry has been leading the charge in the use of location intelligence. By knowing, with high accuracy, if a property is located in a flood, earthquake, or wildfire zone, insurance carriers can more draft accurate policies.

Furthermore, this technology allows carriers to take a more proactive, instead of reactive approach. Instead of simply paying out claims, these companies can help homeowners proactively protect their properties and mitigate risk by understanding the potential damage based on the area.

Financial institutions.

Financial institutions are also using location intelligence to improve fraud detection by better analyzing customer profiles. By matching customer locations and transactions, banks can better understand fraudulent behavior and avoid flagging normal activity.

Both finance companies and retail companies are also using location intelligence to send customers offers when they are near a specific store. Retail companies are taking this a step further by mapping customer behavior in-store to optimize store layout and inventory management.

As more and more industries harness the power of location intelligence, the public and the private sectors are also looking at this technology as a means to create better smart cities around the world.

Location intelligence growing smart cities.

The IESE Cities in Motion Index (CIMI) uses nine dimensions to measure the development of smart cities: human capital, social cohesion, economy, environment, governance, urban planning, international outreach, technology, and mobility and transportation.

The 2019 index (From the Business School at The University of Navarra) named London, New York, and Amsterdam as the smartest global cities based on these criteria, after reviewing 165 cities in 80 countries. Location intelligence plays a critical role in many of these nine dimensions, namely four key parts of any smart city.


Location intelligence can help with two parts related to the environment. First, natural disasters happen in large cities around the world, causing devastating consequences. From filing damage reports to opening lines of communication, location intelligence can help cities rebuild faster.

Second, location intelligence can help city developers better understand where to plan conservation projects and create green spaces around the city. The technology can also analyze air quality and measure the environmental impact a project will have during and after construction.

Urban planning

Location intelligence is crucial to 3D planning, which has become a considerable part of urban development. From the experimentation phase through construction, this technology helps make sure city planning improves the lives of those in the city and can also help to track and measure operational costs.


Technology powers almost every aspect of a smart city. According to IESE, (Media research, University of Navarra) technology, “is an aspect of society that improves the present quality of life, and its level of development or spread is an indicator of the quality of life achieved or the potential quality of life.

In addition, technological development is a dimension that allows cities to be sustainable over time and to maintain or extend the competitive advantages of their production system and the quality of employment.� Location intelligence clearly aids in this endeavor, as both individuals and cities can use this technology to improve smart city functionality.

Mobility and transport

Smart cities around the globe are revolutionizing transportation using location and mobile data to improve traffic and congestion and optimize travel. City planners are able to harness location data to figure out where traffic is the heaviest, when, and why. Using that information, they can then solve these transit problems with new construction or more modes of transport.

Challenges: Privacy and security.

Data collection happens constantly. From ride sharing apps to food delivery services, consumers are constantly giving out location-based data. While the benefit of this is more customized services, the challenge is consumers are more aware and concerned about how their data is used.

Not only has customer awareness increased, but restrictions such as GDPR have forced companies to be more transparent in personal data collection. Furthermore, as technology advances, so do hackers intent on infiltrating these systems. Security concerns are widespread across the industry, and breaches come with heightened consequences.

On the privacy side, more consumer awareness might end up helping improve location intelligence. Consumers taking control of their data means smart cities can rely more on first-party data, rather than third-party aggregators who may not provide the most accurate data.

On the security side, this challenge will likely always remain and will take a combination of individuals protecting their own data and companies providing more transparent data use initiatives to tackle this challenge.

Location intelligence, however, will continue to grow and aid in the creation of better, smarter cities. Especially as this technology advances, and more cities compete to implement smart initiatives, more will come to rely on location intelligence as the crucial component.

Image Credit: Scott Webb; Pexels

The post How Location Intelligence Will Create Even Smarter Cities appeared first on ReadWrite.