The Business Need

Based out of New York City, our client is a leading location intelligence company in the travel industry that provides actionable insights based on the changing location of GPS devices. They assist customers from various industries such as tourism, gaming, hotel, attractions, and many more in providing geo-analytics solutions at a massive scale.

Their highly- efficient technology analyzes the movement of devices to measure how consumers interact with locations. Their location attribution analytics platform helps marketers with new metrics to evaluate the link between marketing exposures and market visitation.

They approached Xtract.io to get location data for 2 prominent industries - 1) the Automotive industry, which includes identifying the nearest dealership stores, repair & maintenance centers, and sales centers, and 2) the Public utility category, which includes airports, hotels, parking garages, and home improvement centers.

Challenges

The customer required POI and Polygon data for the locations under these categories. The objective of this data is to integrate them into their mapping application and get valuable insights offered to their customers. For example, using this data and ingesting it into their application provides them a flexible way to visualize roads, parking spaces, and nearby stores around a particular location. Using this information, our customer assists end-users in mobile marketing and location intelligence solutions.

Inaccurate datasets in their storage base made it difficult for them to identify the right target segment and potential clients for their loyalty programme. To improve their supply chain and marketing strategy, our customer wanted a method that could identify data inconsistencies in real time. Since the categories are vast and the data on the Internet is humongous in size, the customer approached Xtract.io for the same.

Additionally, most of these places are changeable and indoors, for which data accuracy is the key factor considered by the customers. For example, hotels or home improvement stores may relocate, and real-time information may be missing.Similarly, airports and parking garages consist of multi-levels with different stores and foot traffic on each level. Therefore, it is important to accurately capture the finest details of all these locations.

The general category of information included the following data points.

Datapoints Type
Polygon ID
Brand Name
Sub-brand name
Address Location Data
State
Zipcode
Category
Website
Polygon Coordinates Polygon Data

Xtract.io Analysis & Solutions

With years of experience in the geospatial industry, Xtract.io validated the raw information on the Internet and chartered a plan to extract locations and create polygons for a huge set of data. Our team started extracting polygons based on the industry niche and started to build and deliver these datasets. Xtract.io also refreshes this data and updates the customer on the latest dataset twice a year.

Category/Industry #Locations Delivered
Automotive Industry - US 190781
Hotels - US 56089
Airports - US 200
Parking Garage - Washington DC 1142
Home Improvements - US 179

Additionally, Xtract.io successfully delivered POI and Polygon for parking spaces in Washington DC, US.

This includes:

  • Rooftop parking

  • Multiple-level

  • Parking garage

  • Independent parking structure

  • Helipad parking with the following data points

Data Attributes
1. Unique ID 8. Lat/Long
2. Source 9. Parking Structure
3. Location Name 10. Rooftop Parking Availability
4. Location address 11. Rooftop Landing Availability
5. City 12. Rooftop Landing Location Space
6. Zip 13. Rooftop Size
7. Phone Number 14. URL

Xtract.io delivered all the POI and polygon datasets, pertaining to automotive industry, individual brands, and public places of interest in a quick turnaround time, with 95% accuracy. We are happy to help our customer in devising location-based marketing and advertising campaigns for their travel consumers.

1.5 million POI & Polygon data delivered

95% accurate POIs

15+ data points

Biannual data refresh cadence

© 2022 Mobius Knowledge Services | All Rights Reserved.