IP Geolocation accuracy
3/26/2023 Daily accuracy report - Russian Federation (the)

Based on ground truth data collected over a 24 hours period ended at Sun, 26 Mar 2023 00:00:00 GMT
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Why and how do we do that?

It is difficult to overestimate the importance of a precise IP address geolocation. Often, it is the only entirely non-intrusive tool available to indicate where our online customers/visitors are coming from and learn how we can serve them better by catering to their geographical properties.

However, IP geolocation cannot be 100% accurate and has limitations. Some of which we've described in our How accurate can IP Geolocation get? blog post.

Moreover, estimating an overall IP Geolocation accuracy is a complex problem. We have to put it up to test against a massive range of IP addresses with diverse locations, sources, and providers to test the accuracy comprehensively. Ideally, we should try it against our potential customer base, where IP addresses are associated with real people, just like our visitors are. Typically, this ground-truth reference data is rare and must be harvested thoughtfully.

So, where are we getting our reference data from?

  1. First, we kindly ask our website visitors to share their location with us. You may have noticed it when you visited our What is my IP Address? page.
  2. Then we provide a range of iOS and Android apps, such as App store badge Google play badge These apps are the best in range and must-have tools for every network professional and enthusiast. We provide these apps for absolutely free and without ads. In exchange and only with the user's consent, we collect location information associated with the public IP address used. 
  3. We also offer a FREE Client-side reverse geocoding API. It is an industry-first free reverse geocoding and IP Geolocation API without access rate or volume limitations. We only enforce a strict client-side use policy, ensuring that the requested location will likely reflect the caller's IP address and actual service location.

 

At all times, BigDataCloud refrains from gathering any data that could establish a connection between the user's IP address or location and their actual identity. We do not seek to obtain information about end-users or their activities, nor do we engage in surveillance or store personal data associated with IP addresses, even for internal purposes. It should be noted that we do not possess any such information, and we do not sell any personal data.

 

What do we do with the received data?

Whenever an IP address/location pair is received on any collection channels, we instantly carry out the IP Geolocation check against our latest dataset and store the accuracy results. We also perform the same check against the competitive datasets and automatically generate a comprehensive report presented below.

Noticeably, the data we collect is perfectly suitable to represent real-life internet users, website visitors, mobile app users and IoT devices around the world. However, it is less likely to include infrastructural segments such as network routers or public websites.

We also go to great lengths to make sure we exclude abusers. However, we allow VPN and other anonymisers, likely in the same way and proportion one would expect from the traffic hitting a random website or another public service.

We often get several location samples for the same IP address, for example, when the user is on the move. We take the best hit point accuracy record to report, so it is based on distinct IP addresses regardless of the number of occurrences.

We operate precisely the same algorithm and sample categorisation for all datasets, constantly comparing apples to apples.

The Scope

This report can be customised to represent IP addresses reported from a selected country or territory only. 

IP Address Geolocation Service Providers

We are aiming to include as many IP Geolocation original data vendors as possible. We guarantee that we're making absolutely no use of another provider's data beyond the scope of this report. 

If you are an IP Geolocation provider, please get in touch with us and let us access your data, API access is prefered, and we will happily include it in our automated report. We promise to handle your data with great respect and confidentiality expected. 

Included vendors
adjusted to represent records associated with Russian Federation (the) only
Legend
BDC
Product / website link
Blocks Count*
2,746,354
Distinct lat/lng locations
62,805
Dataset
3/25/2023
Legend
IP2Location
Product / website link
Blocks Count*
99,461
Distinct lat/lng locations
2,987
Dataset
3/4/2023
Legend
MaxMind GeoLite2
Product / website link
Blocks Count*
41,107
Distinct lat/lng locations
1,866
Dataset
3/23/2023
Legend
db-ip
Product / website link
Blocks Count*
255,021
Distinct lat/lng locations
22,526
Dataset
3/1/2023
Legend
WhoisXmlApi
Product / website link
Blocks Count*
229,323
Distinct lat/lng locations
5,393
Dataset
3/23/2023

* The blocks count field represents the total number of unique records presented in the dataset. This value is generally applicable to flat data sources. However, the BigDataCloud database does not have such a metric available as we get down to a single IP address resolution. Therefore, we offer a total number of network segments detected by the likelihood of serving the same territory and purpose.

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Confidence area accuracy

BigDataCloud's innovative patent-pending technology enables accurate estimation of the geographical area served by an IP address, rather than a specific device or location. This area is known as the confidence area, and it is represented by a polygon. Some other providers refer to it as an accuracy radius represented by a circle.

The chart provided below showcases the accuracy of this area. If the ground-truth location data is within the confidence area or the accuracy radius of the IP address, it is considered a hit. Therefore, the percentage of location data that hits within this area is known as the Hit Ratio.

Confidence area accuracy (Russian Federation (the))
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Point accuracy

The point accuracy data represents the actual error in the straight distance detected between the actual location reported to the one estimated by an IP Geolocation.

All networks combined (Russian Federation (the))
15,488 distinct IPv4 addresses
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Wired consumers

Wired consumers' chart data primarily represents fixed network installations such as wired WiFi, home and office consumers.

Fixed network detection is a complex issue therefore we must assume that some false-positive cases are included.

Wired consumers (Russian Federation (the))
4,958 distinct IPv4 addresses
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Cellular consumers

Cellular consumers classification represents the network IP addresses that were detected as servicing cellular networks.

Cellular consumers (Russian Federation (the))
7,417 distinct IPv4 addresses
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Hosting and mixed network consumers

This category represents the IP addresses that were detected as servicing hosting networks, VPNs, proxies and mixed networks. The mixed networks are the network subnets that serve legit customers like cellular users and are also subleased to host some VPN or proxy services.

In addition, this category also usually includes residential proxies.

Hosting and mixed network consumers (Russian Federation (the))
8,075 distinct IPv4 addresses
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Country accuracy

The chart below represents the country estimation accuracy of the IP geolocation data providers.

Country level accuracy (Russian Federation (the))
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