Location Validation

Up to 70% of user location data in mobile adtech is of insufficient quality for effective ad targeting. Learn more about why and what to do about it.

At first glance, location data seems straightforward.
A coordinate coming off a device defines the point on the earth's surface where it is located.
However, the mobile adtech ecosystem today isn't designed to consider the origin and quality of incoming user coordinate data.
In fact, only ~30% of these user coordinates in mobile adtech is actually of sufficient quality for effective targeting.
Some of the reasons why the adtech ecosystem doesn't adequately address location quality include:
Overlooked Technology Limitations
There are inherent technical reasons why location data may be poor quality.
Adtech Limitations
Adtech systems (such as OpenRTB) are not currently designed to pass the valuable metadata, generated by mobile devices.
Lack of Standards
There aren’t requirements on how location data should be collected, stored, or passed into the adtech system. There is no current accreditation for location data.
Unless you validate user location data, you risk reaching the wrong people, or sometimes no people at all.
Location Targeted Ad
Wrong Person
The existing adtech ecosystem permits a large volume of poor quality data to be used for ad targeting.
Your browser does not support SVG
The Solution:
Location Validation cleans out imprecise and invalid data from the mobile adtech ecosystem, so you can target ads effectively.
Each coordinate is validated against a set of rigorous criteria. As the system sees more data, these validation criteria improve.
Example of coordinates that are filtered out:
Truncated Coordinates
The number of decimal places in a latitude or longitude represent the precision of the measurement. For example, coordinates with only three decimal places indicate the user is up to 100 meters from where the device claims she is.
Invalid Coordinates
An unreasonably high volume of user locations appear to have repeating numbers, such as (0,0), or other suspicious patterns. These are generally the result of coding errors in the mobile app.
Out of Bounds Coordinates
Many coordinates fall outside the bounds of the earth or close to the extremes of the earth, where very few people live. Others fall in places such as the middle of the ocean. These are generally the result of coding and data errors.
Blacklisted Coordinates
Factual has a list of 650k+ blacklisted coordinates that is constantly improving through machine learning.
Bad Devices + Bad Apps
Device IDs might appear unusually frequently or pop up in random locations across the country within the span of a few seconds. Some apps generate a disproportionate volume of poor quality data.
Your browser does not support SVG
ms to validate
billion data points/month

Factual Location Validation Stack

User location data is passed to Factual from our partners.

Incoming data points are validated against a set of rigorous criteria.

Factual indicates whether or not each coordinate should be used for ad targeting, returning only data that meets our quality standard to the bidder/ad-server.

Factual's location validation stack pre-processes data before being used in Proximity or Audience — helping our partners target with data that meets our high quality standards.
Learn more about Factual’s solutions that leverage the Location Validation Stack: Data for Marketers Data for Analytics Contact Sales