You want to start using POI data to improve your business profitability but do not know where to start?
Read on to learn all you need to know the basics of Point-of-Interest data, the technicality and mechanics of POI analysis and possible use cases and applications by industry and more.
2. What is a Point-of-Interest (POI)?
3. How is POI data generated?
4. Ways to represent POI data
5. How is POI data used?
6. Uses and industrial applications of POI data
7. Where can you get POI data?
8. How to choose the right POI data vendor
More about Data Delivery
9. How Quadrant is changing the POI data landscape
Welcome to our Quadrant POI Data Knowledge Base! Through these chapters, we will learn about what POI data is, why it is useful, and the mechanics behind its collection and real-world usage.
There has been a seismic shift in how consumers interact with businesses and locations around them. Hailing a cab on the street has been replaced by ride-share services like Uber and Grab. Instead of queuing or making appointments at their favourite restaurants, people have their food delivered to their doorstep. There is an app for everything, from buying clothes to running errands, from finding housekeeping or laundry services, and so on. It is almost unimaginable that we once lived in a world where all these services did not exist.
With the rapid increase in 'at your door' services, POI data becomes vital to efficiency. Without an accurate reference of location, delivering these services would be difficult. Uber drivers need to know the restaurant's exact location to pick up the next passenger, and it makes sense for a fast-food chain to open a new store in a growing residential area where customers are underserved.
The most rudimentary way of acquiring data is the automatic extraction of POIs from web sources like Google Maps, OpenStreetMap, etc. Some companies use web scraping tools to export POI information directly into a file or database. While sites like OpenStreetMap allow the extraction of geospatial data points, others are actively preventing mass scraping with stopgap measures like IP blocking. Getting around these might not be illegal, but it is discouraged. Overall, this method is time-consuming and labour intensive, and it is not ideal for large-scale POI projects that need a larger volume of data. The data acquired from these sources also requires intensive data preparation to be used for analysis.
Location engines like Google Maps also heavily rely on businesses and places supplying their own information. If they do not voluntarily update these data points, information can become outdated and introduce inconsistency and inaccuracy into datasets.
In the past decade, there has been a surge in the use of social media and thus in user-generated content, including location data. Many businesses rely on user-generated location data or purchase data from vendors who run applications that collect such data. Remember your last check-in on your favourite social media app? You probably added a new location or verified one for a location data collector.
Location data collectors record locations pinned by users and create their own POI records based on that information. However, geographic data provided by a user does not guarantee accuracy, as it is dependent on the hardware, the location permissions of the application, and precision settings. Unintentional mistakes can also deteriorate the quality.
Most government bodies require businesses to provide their commercial location as part of their business registration process. These postal addresses can form a POI dataset. Many countries make this data publicly available. For example, the Accounting and Corporate Authority (ACRA) of Singapore makes the historical and current data of 1.5 million companies available for public use, research, or application development purposes under their open data initiative.
However, businesses close, grow and move offices or operate at a different location than their officially registered address. Since they may not proactively update this information with the government body, these data can become outdated and inaccurate over a period of time.
Some POI data providers hire or contract personnel to manually maintain their POI database: walking the city with a smartphone running a purpose-built app and adding new locations or verifying existing ones. Compared to other methods, this process guarantees accuracy and promises a healthy stream of POI data.
This method of data collection also avoids infringement on users’ privacy and sale of their location data. These purpose-built apps do not store, collect, or share any data other than the physical location (without tying context back to an actual human being and their mobile device).
Commonly expressed in latitude and longitude (Lat/Long), the geographic positions of a location are called coordinates. A POI can be identified with data points as minimal as the latitude and longitude. These data can be procured from satellite-based mapping services or collated using GPS-enabled devices (such as smartphones, fitness trackers, tablets, etc.). Using multiple coordinates, it is possible to create a larger virtual perimeter for a real-world geographic area known as Lat/Long Boundary or Geofence. A boundary can be radial or in the shape of a polygon formed by connecting multiple Lat/Long points. These boundaries help businesses identify and assess POIs within a specific area to draw trends and patterns.
Another common method to represent a POI is its physical address, which usually includes a government-assigned Pin, Postal, or Zip Code. Initially aimed at helping mail carriers sort and deliver mail efficiently, the postal code system became widely used to determine the location of a place of interest. However, there is no global standard for postal codes. In some countries, like Singapore, a postal code can identify an individual housing block. On the other end, Hong Kong, a territory comparable in size and population, does not use the postal code system at all. Most places fall somewhere in between, where a postal code is not enough to pinpoint an individual Point-of-Interest but can be used as an “official geofence” in data analysis.
Invented by Gustavo Niemeyer, Geohash is a geocoding system that allows the expression of a location anywhere in the world using an alphanumeric string. Geohash is a unique string derived by encoding and reducing the two-dimensional geographic coordinates (latitude and longitude) into a string of digits and letters. A Geohash can be as vague or accurate as needed depending on the length of the string. A Geohash uses grids for spatial indexing where the world is recursively divided into small grids, with each added grid introducing an extra level of accuracy. One of the primary benefits of a Geohash is that it is excellent for precisely pinpointing a POI. By dividing a larger area into grids, you can eliminate most unwanted areas upfront and only focus on the square where your potential targets are in. It also allows for faster geofencing than the lat/long method, saving time and money.
H3 is a hierarchical geospatial indexing system much like Geohash. However, it uses hexagonal grids instead of rectangular grids. H3 was developed by the popular ride-sharing app Uber to optimise ride pricing and dispatch by visualising and exploring spatial data. The H3 grid system was open-sourced in early 2020 and is slowly gaining popularity. The H3 system works best for efficient radial lookups. Which is why H3 is best for calculating distance between two places and allows circular geofences.
Information about a specific location or a collection of similar locations can help businesses drive better decisions. Combined with additional contextual parameters such as human mobility, sociology, dynamics of an area, and more, POI can be used to build meaningful information structures that enable robust analysis and planning.
POI data has multiple use cases and applications across industries. It powers navigation systems (for mapping or apps like food delivery, errands, online retail etc.) urban planning and architecture, supply chain logistics, transit management, and more.
Both users and businesses need timely and accurate locations to find and deliver relevant services. Businesses need POI data to connect with their customers in the physical world: delivering or picking up a package, picking up a passenger who requested a ride on their ride-sharing app, assessing competing outlets before expanding to a new neighbourhood, and more. Users also rely on POI data to navigate their surroundings to find emergency services, get transportation, find places to shop, etc.
POI data can facilitate the interaction between consumers and businesses in the physical world. Therefore, data collectors aim to build exhaustive databases of relevant locations. Companies and governments can leverage these POI data to identify trends and patterns in a region and derive actionable insight to:
- Commission research and monitoring studies
- Improve navigation and mapping systems
- Making supply chain operations more efficient
- Improve transit, healthcare, and public services
- Match consumers with service providers, and more
With the right context, POI data can be used by retail outlets to monitor traffic to one of their sites or of their competitors. Logistics businesses can save costs and improve customer experience with accurate address data. Real estate companies use POI data for site selection and project planning based on market potential. Governments can use POI data to enforce regulations, monitor public health and well-being, plan public infrastructure and services, and more. The main goal of POI data is to identify a place of interest, establish its accurate location, and help businesses understand the happenings around that place to make better, well-informed decisions. POI can be essential in assessing competition, improving operational efficiency, planning the expansion of your business, and more.
The food and dining industry needs accurate POI data to make and fast deliveries and optimise workforce efficiency. The speed and efficacy in delivery times can win or lose customer loyalty and impact operational costs. The competition in the food delivery sector is stiff, it takes little for customers to switch to another application. Estimated delivery time too long? Too few options? Delivery was delayed due to traffic? Users are quick to take their business elsewhere. Using reliable residential and commercial POI data, food delivery applications can create reliable fulfilment systems and gain competitive advantage to retain customers.
-Calculate accurate delivery times and provide accurate ETAs
-Map specific regions to establish presence in underserved areas.
-Identify efficient routes for delivery assignments and save costs
With retail increasingly moving online, last-mile delivery costs increased significantly. As a result, companies must optimise their logistics to remain profitable. By using accurate and reliable POI data, postal services, fleet and freight businesses, on-demand transport companies, and online marketplaces can improve their routes, minimise errors, plan placement and expansion of pickup and delivery points, etc. They can also use POI data to build reliable apps that ensure efficiency and save time. Cab hailing services can use accurate POI data to enrich their apps, optimise their routes, and fulfil customer requests faster.
-Map residential complexes to optimise delivery operations
-Assess coverage to expand drop-off and pick-up points
-Optimise fleet route to improve efficiency and save time & costs
Facing increased regulation and disruption from modern technology, banks and financial institutions that want to maintain their competitive edge need to leverage POI and mobility data. In the insurance sector, the POI data in a region can be paramount to risk assessment and formulation of policies tailored to that region. In retail banking, POI data can be used to map a network of bank counters or ATMs across the city. Combined with mobility data, retail banks can explore new ways of engaging customers, enhance touch-points, and improve operational efficiency.
-Map buildings and structures in disaster-prone zones
-Engage customers with targeted Out-of-Home advertising
-Assess and improve ATM coverage in a region
In combination with mobile location data, POI data can help retailers increase profits and provide better services to their customers. Knowing where their customers are can help them optimise Out-of-Home advertising, increasing footfall in their stores. POI data can help retailers get an accurate idea of footfall of their competitors as well. With POI data, retailers can also conduct performance and comparison analyses for all stores across a region. POI data can also be used to drive customers from online venues to physical retail locations.
-Identify competition in a particular neighbourhood
-Site and footfall analysis for new stores and point of sales
-Plan expansion in a new city or country
When looking to buy or rent a home, customers always want to know about the amenities and attractions in an area. POI data can help real estate developers gather insights before investing or building in a new neighbourhood. Providing rich and accurate data about their project's surroundings also helps drive sales. Online property directories can utilise POI data to provide customers with accurate data about a neighbourhood, facilities in their areas of interest, directions, and more.
-Map dining, schools, hospital, and facilities around new projects
-Neighbourhood assessment for competition & valuation research
-Enrich online selling and renting platforms with location precision
Network and high-speed internet availability are paramount to mobile usage, television consumption, etc. Therefore, it is more important than ever for telecom companies to plan for network capacity in a region. POI data can help them assess coverage needs, perform competitive analysis, and determine exactly where to build new infrastructure. Combined with data points like area density and competition, telecom businesses can use POI data to plan store openings and offer lucrative plans for their customers.
-Assess coverage and plan expansion in specific areas
-Gain a competitive edge over other networks and services
-Expand customer base by providing stores in ideal proximity
POI data can be used to plan and optimise Out-of-Home marketing campaigns. Using location-based ads, businesses can deliver tailored, relevant messages and drive customers to their points of sale. Inaccurate POI data can quickly turn a location-based campaign into an irrelevant barrage of messages, wasting money and diminishing brand equity.
-Improve ROI, reduce ad waste and increase footfall
-Perform competitive analysis using POI data in regions of interest
-Strategise ad placement and target the right audience
Governments and local authorities as well as emergency and public service agencies can leverage POI data multiple ways. They can use POI data to map regions accurately and optimise services like public transit, emergency healthcare, law enforcement, and more. Combined with mobility data, POI can help fast-track activities like contact tracing, crime alerts, and more.
-Improve public services based on the availability of facilities
-Optimise and monitor traffic, healthcare, and public infrastructure
-Create crime/disaster response plans by mapping SOS services
An ideal POI database evolves with changes happening in the physical world. New businesses open, existing ones move or close, neighbourhoods expand, new parking facilities become available in high-density areas (where they are most needed), and more. Furthermore, urban spaces are constantly changing. Recently, our world was greatly impacted by the COVID-19 pandemic, as many businesses went out of business and closed. All these changes in the physical world need to be documented to keep our complex digital economy going, and POI databases do just that.
But where do you get POI data that is fresh, accurate, and reliable? There are numerous POI data providers who map the world using various methods, and enrich it by adding new places and removing outdated information.
When looking to acquire POI data, you must start with defining a clear objective. The second step is answering what data points you need to achieve this goal. Thirdly, you must assess your challenges and existing in-house capabilities for working with the procured data.
While quality and accuracy are paramount for POI data, there are other key factors to consider. What are the data provider's delivery capabilities? What is the effort you need to put into preparation to use the data? How do you pick the right partner from a sea of POI data providers? A few considerations to make before you procure POI data for your business are:
- Define your goals and challenges
- Identify the category of location data you need.
- Determine the frequency of updates (daily, monthly, annual)
- Align accuracy with your use case (What happens if the accuracy is off by 100 meters, how does it affect your business?)
Here are the key parameters to assess and choose the right POI data partner:
The first step in assessing a POI data provider should always be assessing their coverage of regions and various POI categories. Are they providing enough data in the area your project is focused on? Does the region have enough data points from the POI category your analysis needs? Most POI data providers claim global coverage, but they will always have more density in one country, state, or city than another. To ensure adequate data procurement, you must verify the coverage of POI data by requesting updated numbers and sample data from the regions you are interested in.
The accuracy of POI data is paramount to your analysis. To determine the accuracy, you must understand your data provider's POI collection and verification methods. You can create a reference dataset to compare information when you receive sample data from a vendor in evaluation. Do the latitudes and longitudes in the sample align with the reference data set? Is an inaccuracy of a few meters acceptable? You must also assess how they classify POIs and define attributes, as the lack of standards and clear naming conventions can result in inaccurate analysis despite the volume of data.
The physical world is ever-changing. While some POIs such as historical sites, beaches, etc. are unlikely to change, retail outlets, hospitals, offices can move or shut down. For instance many businesses closed down during the Covid-19 pandemic, with the economy recovering there'll be thousands of out-of-date POIs and potential for newer ones to be added. Outdated POIs can lead to false insights; therefore, POIs must be frequently updated. Ask your vendor questions about the frequency of updates to their database. When was the data last updated? Time between updates and more.
The accuracy and freshness of POI data depend on how your data provider collects their POI and keeps them updated. POIs are dynamic and subject to frequent changes. Most user-generated and web scraped POI data tend to be outdated, especially compared to manually verified data sets.
POI data can be challenging to work with if they are not normalised and deduped, and you might need additional resources (data preparation skills and tools) to clean the data. While manual vetting can ensure quality and customisation to your needs, it can be time-consuming and costly.
Most often vendors provide data via APIs where the data stays in a single location and can be tapped by multiple applications. However, you can also procure data in bulk. While APIs save costs associated with data storage, bulk delivery prides more flexibility in the customisation and usage of data.
API-based delivery can directly feed the POI provider’s database into the customer’s data platform or analytics applications.
- Ideal for powering an analytical platform or automated analysis
- Cost effective as Data is stored, and maintained by the provider
- Pick, choose, and import only the data that you need
- Embed data into any application supported by the data provider
- Lack of control over data health and quality
- No way to self-update an incorrect record
- APIs do not allow do bulk optimisations and analysis
- Can be costly when requiring POI in large volumes
- Need to build custom integrations for unsupported applications
You can also choose to obtain data in bulk, using data storage services like Amazon S3, Azure Blob, or Google Cloud. Bulk data delivery allows you to procure raw data which can be customised to fit your own use case. It is the best format to use with machine learning and other artificial intelligence analysis.
Most existing, widely available POI databases are quite inaccurate, and consumers often face mismatched information based on exact locations. Accurate POI information is valuable now more than ever, as the COVID-19 pandemic has rewritten the maps of businesses. Some companies were forced to shut down, and many moved online to sustain themselves. As the economy recovers and new POIs (Points-of-Interest) appear, companies will need accurate data to function, especially those in ad-tech, food and dining, communications, and navigation. To reach accurate outcomes, new domains in data science require superior quality POI input that companies like Google and other non-caching APIs do not offer.
To solve this problem, Quadrant has come up with a diligent, human based approach to collecting POI data. Quadrant POI Data is powered by Geolancer - an industry-leading manual verification project. How this works is, actual human verifiers, equipped with a smartphone run our proprietary app and manually add/verify POI data points, ensuring accuracy and authenticity. This unique process solves most of the problems plaguing other POI data sets, including user errors, GPS inaccuracies, and outdated information. The platform can be used to create bespoke data sets based on client requirements (for a specific area, for a category, or brand) or to verify a company’s existing POI data.
Our goal is to create solutions for people and the businesses that serve them. With our POI offerings, our customers will finally be able to apply analytical models against large, accurate POI datasets, deriving meaningful and actionable insights. With the increasing digital transformation of businesses, there is an enormous market need for quality POI data. Using Geolancer, we will be able to offer authentic, accurate, and up-to-date POI data to companies in the ride-sharing, real estate, e-commerce, delivery and logistics and other location powered industries.
POI Data combined with our expertise in mobile location data solution can provide deeper insights on the behaviour of our customers’ target audience making us a holistic data partner for them.
What is our POI data coverage?
Quadrant will be releasing point of interest data across Asia Pacific focusing on countries like Singapore, Australia, Vietnam, Malaysia, Indonesia, Cambodia, and Philippines. We will be adding locations as per our expansion plans and demand in other regions of the world.
How much POI data do we have?
The number of data points available or regions covered is unique, based on our customers’ needs and use cases. Quadrant POI data is driven by our Geolancer with a focus to input and update points of interest information daily. Our Geolancers are dedicated to attaining specific locations our customers request based on their business use case.
What is our method of data delivery?
CSV. Quadrant POI data will be delivered in bulk. This will allow customers to have full access to the database provided by our team. The CSV file will allow our data science teams to run Machine Learning algorithms and do perform analysis without any limitations.
What are the attributes available in Quadrant Enhanced POI?
-Mobile Latitude/ Longitude
-H3 Spatial Index