How accurate can IP Geolocation get?

BigDataCloud August 18, 2025

IP geolocation is one of the most important — and often misunderstood — technologies powering today’s internet. It lets service providers estimate where online visitors are located without intrusive tracking. That makes it essential for:

Showing content in the right language and region
Enforcing copyright and digital rights
Running localised marketing campaigns
Detecting fraud and unusual activity
Adding an extra layer of security to online transactions

But how accurate is IP geolocation in practice? Some believe it’s only reliable at the country level; others expect it to behave like GPS. The truth sits in between: IP geolocation can be very accurate under the right conditions, but it is not designed — even in theory — to pinpoint every user with 100% precision. To understand why, we’ll start with the apparent “shortage” of IP addresses and then explain why that isn’t a real technical limitation.

The Scale of Global Demand (2025)

Before looking at numbers, it’s worth noting that the internet actually uses two address systems today: IPv4 and IPv6.

IPv6 is the modern system with an almost inexhaustible supply of addresses (2¹²⁸), easily enough for every device for generations.
IPv4 is the original system, limited to about 4.29 billion addresses. Despite that limit, it still carries the majority of internet traffic in 2025.

So why focus on IPv4 here? Because although IPv6 adoption is growing, it is still uneven. Most networks, websites and services continue to rely heavily on IPv4 for compatibility. That’s where the practical constraints — and the real-world limits of IP geolocation accuracy — are most visible.

On paper, the internet looks like it should have a severe address shortage:

≈ 5.5 billion internet users worldwide
≈ 281 million registered domains
≈ 4.5 billion smartphone users
≈ 19–21 billion connected IoT devices

Meanwhile, IPv4 provides just 4.29 billion theoretical addresses, and only about ~3.1 billion of those are actively routable on the public internet at any given time. How does the internet cope — and what does this mean for geolocation?

IPv4: Why It’s Not a Real Technical Shortage

The key is that most online activity only requires a one-way connection. Think of it like sending a letter: you write to a company, they reply to the return address, and the exchange is complete. You don’t need a dedicated post box for every person in your household — the post office sorts it all correctly. The internet works similarly.

When you browse a website, your device initiates the connection. The server replies to that specific request and the session closes. Your device doesn’t need to be permanently reachable from the outside world, so it doesn’t need its own unique, permanent public IP address. That’s why it’s perfectly fine — and normal — for many users to share the same public IP.

To make this work, the internet uses several well-established techniques:

NAT (Network Address Translation): multiple devices in a home or office share a single public IP.
Carrier-Grade NAT (CGNAT): mobile carriers connect millions of subscribers through relatively small address pools.
Anycast: the same public IP can be advertised from multiple servers worldwide for performance and resilience.
Name-based (virtual) hosting: hundreds of websites can operate from one IP by using the domain name to route each request.

In other words, from a technical perspective, IPv4 remains sufficient for how the internet actually works today and into the future. What people often call a “shortage” is mostly an allocation and economic imbalance (for example, very large legacy blocks held by some organisations while high-growth regions must purchase addresses on the secondary market). That imbalance can make IPv4 expensive, but not technically inadequate.

The Flawed “One IP = One Device” Assumption

Because billions of people and devices share ~3.1 billion routable IPv4 addresses, it is not true that every public IP corresponds to a single device at a single fixed place. Modern design breaks that assumption in several ways:

NAT & CGNAT: entire households or tens of thousands of mobile users can appear under the same outward-facing IP.
Anycast & load balancing: a single IP may serve users across multiple regions simultaneously.
Dynamic assignment: an IP can represent different users in different locations at different times.

That makes it theoretically impossible for IP geolocation to be 100% precise for every user. It is intentionally designed to provide evidence-based area estimates rather than an exact personal locator. Understanding this helps set realistic expectations for accuracy.

How IP Assignment Affects Accuracy

Static IP addresses: the best-case scenario

A static IP stays linked to one device, server or household. When strong evidence lines up — ISP records, geofeeds, long-term observation and network measurements — static IPs can be geolocated very precisely (often down to a few metres in raw data).

For privacy, BigDataCloud deliberately rounds to the nearest kilometre, so the maximum reported precision is within ~1 km². For developer control, our IP Address Geolocation with Confidence Area API also returns a polygon (the confidence area) so you can combine both a point and a bounded region in your logic.

Dynamic IP addresses: why results vary

Most people use dynamic IPs — temporary addresses leased by their internet provider. Sometimes the same address remains with you for weeks; other times it changes daily or whenever you reconnect. If your address is long-lived, geolocation can approach static-like accuracy. If it was used in a neighbouring suburb yesterday and reassigned to you today, the point estimate may lag reality.

Why ISPs use dynamic addresses

To manage a finite public address pool efficiently
To simplify provisioning and reduce operational overhead
To add a light layer of privacy and rotation for end users

How geolocation handles it

ISPs allocate from blocks (ranges). Some blocks are very small; others span multiple suburbs or an entire city. That’s why BigDataCloud returns a confidence area polygon — it reflects the maximum plausible region where a dynamic IP could realistically be. The user is inside that region, but the exact dot can shift as the address is reassigned.

Example: if your ISP uses a pool across Sydney’s north shore, geolocation will correctly place you in that broader area — though not necessarily on your exact street.

Mobile / Cellular Networks: Why They’re Harder

Mobile networks add unique wrinkles that non-technical readers should keep in mind:

Mobility: you can travel hundreds of kilometres while your phone keeps the same outward-facing IP.
Massive sharing (CGNAT): tens of thousands of subscribers may share a single public IP via carrier gateways.
Centralised egress: carriers often route traffic through a small number of gateways (e.g., a state capital), so a session physically in Adelaide might appear to come from Melbourne if that’s where the gateway is.

What this means for accuracy

City-level accuracy is often achievable; suburb-level may be possible but is not guaranteed.
In some cases, the confidence area may be large (a whole metro area or state — in rare cases, country-scale).
Even operators generally cannot provide precise, real-time per-IP locations without consulting internal logs, which is outside normal practice.

Geolocation remains very useful on mobile (fraud checks, policy enforcement, broad personalisation), but results should always be treated as approximate rather than pinpoint.

Hosting vs Consumer Networks

Many IPs belong to data centres, corporate networks or hosting providers rather than households. These addresses are usually static and describe the location of the infrastructure (e.g., a server or VPN exit), not a specific end user. A trustworthy service doesn’t just provide coordinates; it also classifies the IP (consumer, mobile, hosting) so you can interpret the result correctly.

Edge Cases to Expect

International roaming

When travelling overseas, a mobile operator may tunnel your traffic back to the home network for billing and control. You might be in Paris, but your public IP looks like Sydney. Sensible defaults — plus clear flags — help prevent misinterpretation.

VPNs, proxies and TOR

These services intentionally mask the user’s true IP. Geolocation will show the exit node. In these scenarios, accurate classification (VPN / proxy / TOR) is often more useful for risk and policy than the raw coordinates.

Evidence-Based Results, with Confidence

BigDataCloud applies a strictly evidence-based approach — we do not guess. Accuracy is communicated in two complementary ways:

Confidence area: the polygon marking the maximum plausible service area for the IP (returned by our IP Address Geolocation with Confidence Area API).
Confidence value: a qualitative indicator (low / medium / high) of evidence strength and consistency (see How to interpret Confidence Value).

For independent, provider-by-provider outcomes, visit the Daily IP Geolocation Accuracy Report to see ongoing accuracy across networks and countries.

Quick Reference

IP type	Characteristics	Accuracy potential
Static	Permanently assigned; strong, consistent evidence	Very high (metres in raw data), privacy-capped to ~1 km
Dynamic	Temporarily assigned; block-based; may be reassigned	Moderate to high; bounded by confidence area
Mobile / CGNAT	Shared by many users; centralised egress; mobility	City / state level typical; sometimes broader
Hosting	Servers, VPNs, proxies, TOR exits	Represents infrastructure, not an end user

Conclusion

IP geolocation is a powerful and privacy-conscious way to understand where online traffic comes from — but it’s not GPS and it never was. With only ~3.1 billion routable IPv4s versus billions of users and devices, it’s impossible to map every public IP one-to-one to a single person. Instead, geolocation provides evidence-based area estimates that are extremely useful for localisation, analytics and fraud prevention.

Static IPs: very accurate, privacy-capped.
Dynamic IPs: accuracy varies; use the confidence area.
Mobile / CGNAT: approximate by design; interpret with classification.
Hosting: reflects infrastructure, not individuals.

If you need both precision and a clear risk envelope, use our IP Address Geolocation with Confidence Area API, consult the Confidence Value guide, and keep an eye on the Daily Accuracy Report.