Using Geolocation Data with Greater Confidence
For well over a decade, IP geolocation data has provided thousands of organizations invaluable insights on the location of every website visitor, reducing fraud and ensuring regulatory and licensing compliance while providing a better customer experience.
And for all that time, users of the data have had to balance its significant strengths (see below) against one shortcoming: an unavoidable degree of uncertainty.
Fortunately, Neustar counters that uncertainty in its UltraGeoPoint geolocation data with a numerical measure called a Confidence Factor for key geographic data points assigned to any given IP address.
Confidence Factors are the next best thing to 100% accuracy. They strengthen the considerable value geolocation data already provides through its unique and positive attributes:
- It works for virtually every visitor. Geolocation data identifies a user’s location based solely on the IP address of the device they’re using to connect to the Internet. And since Neustar provides location data for both IPv4 and IPv6 addresses, you get near universal coverage.
- It doesn’t require user participation or opt-in. Your organization can gain location insights for any visitor – registered or unregistered, known or unknown.
- It’s virtually instantaneous. Location insights are returned in near real time. You can ingest the data into a decisioning engine at the moment a visitor arrives at your website, and its use won’t add delays or latency that can degrade the customer experience.
- It’s compliant with privacy regulations. As a passive, non-invasive technology, IP geolocation data can easily comply with the constellation of data privacy regulations around the world.
These characteristics make IP geolocation data ideal for achieving important business or regulatory objectives that require knowing a user’s location when it might otherwise be unknown.
It helps companies prevent fraud and alerts them to potential cyberthreats. It simplifies compliance with geographic restrictions on content and services. And it improves the customer experience by enabling geographically personalized interactions.
With all these strengths, there is one shortcoming. IP addresses have no inherent link to geography (yes, there are country codes, but they’re not universally applied). And there is no absolute truth set for the location of IP addresses. Moreover, some Internet routing connections obscure locations by funneling thousands of widely dispersed users through a small number of IP addresses.
These realities make it impossible to wring all the uncertainty out of geolocation data, despite heroic efforts to make it as accurate as possible.
At Neustar, we’ve invested millions of dollars to create and continually improve a strong, robust and highly accurate geolocation database, supported by a global data collection network and curated by deeply experienced Network Geography Analysts.
Our database is updated continuously for both IPv4 and IPv6 addresses. Location assignments are created by sophisticated algorithms using multiple inputs that include the IP address itself, the organization that registered it, traceroutes for data traveling to and from it, the routing type used to reach the Internet, and in some cases relevant data from qualified, reputable third-party sources.
Yet even with all these resources and inputs, assigning a geographic location to an IP address inevitably involves some degree of uncertainty.
Confidence Factors combat this uncertainty with a quantitative measure that an IP address is actually in use at its assigned location. They’re a crucial innovation in geolocation data, allowing organizations to use it with a much higher degree of certainty. And when you’re driving decisions affecting fraud, cyberthreats, regulatory or contractual compliance and user experience, you don’t want uncertainty.
Our Confidence Factors (CFs) reflect the strength of the correlation between the different data sources we use to assign a location to an IP address. If all data sources point to the same location, the Confidence Factor is very high. If there is less agreement, it is lower. You can learn more about our methodology in this free whitepaper.
We calculate separate Confidence Factors for each geographic data point – country, state, city and postal code (where available) – to give users flexibility in meeting their specific geographic data requirements. And since CFs are quantitative, they can be incorporated in any application that uses geolocation data:
- Fraud prevention, where a higher CF gives greater weight to location data identifying visitors from a county a financial services firm doesn’t serve, for example, or allowing a state to identify non-residents applying for state funds
- Cybersecurity, where CFs help ensure more accurate location data to identify suspicious log-ins seeking access to sensitive or restricted content, or that may represent a potentially active cyberthreat
- Gaming and gambling, allowing operators to confidently provide unrestricted access to players located in countries or states they are licensed to serve, or alternately route them to a deeper authentication process that asks for additional information
- Media and content distribution, helping OTT and streaming media providers decide whether to deliver or defend access to geographically restricted entertainment content or enforce contractual blackouts for live sports events
Each of these applications improves business outcomes based on correct data about the user’s location – and involves potentially serious consequences if the data is incorrect.
Confidence Factors help organizations get these decisions right. They allow them to use geolocation data to improve accuracy and outcomes – with confidence.
To learn more about how you can confidently incorporate the unique insights available through UltraGeoPoint in your customer journeys, contact us or give us a call at 1-855-898-0036 in the US or +44 1784 448444 in the UK.