The 'confidence value' is an innovative and more effective approach to evaluate the accuracy and reliability of IP geolocation data using BigDataCloud's proprietary technology. Conventional methods can only provide a single-point location estimate that may not represent the actual location of a dynamically assigned IP address. This issue is further compounded by the challenge of verifying and reconciling conflicting data from multiple sources, which explains why human-based validation remains a common approach, despite its limitations.
To address these limitations, BigDataCloud's confidence value is determined by integrating the outcomes of two independent and parallel processes. The first step employs a unique patent-pending technology for network routers' service area estimation to determine the confidence area within which an IP address could be located if dynamically assigned. This approach provides an additional automatic verification step, which enhances the accuracy and reliability of the resulting geolocation data.
The second step involves collecting field evidence data to confirm the actual location of the IP address. The results of these two processes are then compared, and a confidence value is assigned based on the quality and reliability of the data. The confidence value ranges from low to high, depending on the degree of support and quality of the outcomes.
It should be noted that a low confidence value does not necessarily mean that the IP geolocation estimation is inaccurate. However, a medium-high confidence value suggests a higher level of accuracy and reliability, and the 'confidence' value serves as an essential indicator of the data quality. It can be used to assess the accuracy and reliability of IP geolocation estimation, which can be critical for several industries such as advertising, security, and e-commerce.