Audience segmentation is key to any marketing strategy. Location intelligence-driven advertising gives more timely and complete insights into audiences than ever before. Linking the places a person visits over the course of a day or a week provides a more rounded view of their interests and priorities.
With accurate and precise location data advertisers can analyze consumer movements and build user audiences based on real-world places and geometry. This results in more contextual relevant advertising, improving the efficiency of campaign spend and therefore ROI.
No. 1: What is the source of the place data?
It is important to know where place information is coming from because different sources can interpret a place differently. For example, the same park can mean different things to dog walkers or runners. If it is used for a sports game or a concert different audiences will bring different interpretations if they are editing location sources. Places also change in different weathers, some are busy during summer months and closed during winter. Places are in many senses alive and full of change. Any technology needs to be able to clean, normalize and standardize multiple different potential references to a place if it is to give accurate data.
HERE sources millions of records of place data daily, gathered from thousands of sources including business listings, social media, financial transaction indications, brand and niche sources, targeted search engine resources, communities and local field insights. Machine learning technology then processes, sorts and contextualizes that data to deliver a reliable dataset of places globally.
No. 2: How is the place data organized?
There are several ways to organize information about places—using polygons, geofencing and centroids.
A geofence is a virtual fence around a physical location. A phone can be detected entering the area. A person walking past a store can then receive a voucher on their device.
A centroid is a central location used to determine a user’s location. A user’s location is determined by tying the user to the nearest IP address at the time they are on their device.
Some companies build polygons from the latitude and longitude signals coming from apps, others use commercial satellites and some create them manually.
HERE Places Footprints associates places with their precise building shape. The associations are generated via proprietary algorithms and updated via machine learning. Data collection continuously reinforces our understanding of reality. Confidence scores provide guidance to our expected performance of the matching algorithms give the specific inputs related to that POI.
No. 3: How precise is the place information? Is it possible to know if a customer is inside a specific store within a mall or if they are in the parking lot?
Building footprints and indoor venue maps enable precise and accurate targeting, audience segmentation, and campaign measurement to within a meter.
2D footprint technology offers a polygon representation of points of interest, including shopping malls, sports venues, airports and more.
Meanwhile, the best 2D and 3D indoor venue maps for places such as malls, airports, train stations, universities, hospitals and stadiums, offer insights into exact consumer location.
You can use these technologies to improve the quality of your latitude and longitude placements and to feed into your algorithms for further optimization and enhanced data science.
For example, HERE partners with Verve, with leading mobile platform for location-powered programmatic video and display marketing, to enrich Verve's Velocity platform with places, building polygons and venue maps data. This enables B2B customer to improve audience segmentation and ultimately server consumers more relevant advertising.
In addition to leveraging our data sets, you can also access HERE places and polygon data through HERE Advertising Data Services REST API. Use the service to translate dynamic location signals into nearby points-of-interests and precise building shapes, analyze mobility patterns and places people visit, and build more precise audience segments.
Want to hear about the four other questions? Learn about the challenges. Click here to check out our eBook: The Guide to Buying Location Data for Marketers.