Why We Chose IPinfo for IP-to-Location Data in Website Personalization
At If-So, our customers rely on us to deliver experiences that feel locally relevant the moment a page loads, whether that means the right language, the right offer, or the right regional message. That makes location data a foundational dependency.
Like many teams, we were aware of the common concern that “IP geolocation is inaccurate.” In fact, we experienced the limitations firsthand. As adoption of our geolocation features increased, inaccuracies, especially at the city level, began creating customer friction and limiting our ability to scale confidently.Rather than accept those constraints, we rigorously evaluated alternative providers to understand what truly drives reliable geolocation for real-world personalization. This post shares what we learned and why IPinfo ultimately became the foundation for our location-based experiences.
What Website Personalization Needs from Location Data
Effective personalization does not require GPS-level precision. What it needs is location data that is accurate and useful in production environments.
In most website personalization scenarios, location operates at three practical levels:
- Country
- Region/state
- City
The right level depends on the rule being triggered. For example:
- Geo-based headline swaps
- Regional promotions and offers
- Language or currency defaults
- Store locator pre-selection
In each case, the goal is not pinpoint accuracy down to a street address. The goal is to reliably place visitors in the correct geographic bucket so personalization rules behave predictably.
Where IP Geolocation Can Go Wrong
Before switching providers, we experienced how even small inaccuracies in location data can impact websites.
When IP data is inconsistent, personalization breaks in visible ways:
- Visitors see messaging for the wrong city or state
- Language or currency defaults feel incorrect
- Shipping or legal notices appear in the wrong regions
- Regional promotions misfire
As adoption of our geolocation feature grew, we began noticing occasional inconsistencies, especially with city-level detection. It became clear that even small variations in data accuracy can influence user experience and campaign results.
Ultimately, geolocation quality contributes directly to how seamless and effective your dynamic content feels.
Why IP Location Can Look Inconsistent
Even strong geolocation systems must handle real-world internet complexity. Through our evaluation process, we found several structural reasons why IP location can vary.
Mobile Networks and Shared IPs
Mobile carriers frequently use CGNAT (Carrier-Grade NAT), which places many users behind a single public IP address. As a result:
- Large numbers of users can appear to originate from the same network location
- Traffic patterns can look geographically “jumpy”
- Apparent user density can be misleading
For personalization systems like ours, this means city targeting must be supported by data that properly accounts for mobile network behavior.
VPNs, Proxies, and Privacy Tools
Privacy technologies intentionally abstract user location, which introduces legitimate uncertainty.
For personalization use cases, this is usually an uncertainty management problem, not a fraud problem. The key is working with a provider that surfaces reliable signals and confidence indicators so rules can adapt appropriately.
Some relay-based privacy systems, like Apple’s iCloud Private Relay, can still present stable regional signals, while others provide a completely different location. Understanding this distinction is important when designing resilient targeting logic.
IP Reassignment and Movement Over Time
IP addresses are not static assets. Networks evolve constantly:
- IP blocks change ownership
- Infrastructure gets reconfigured
- Routing patterns shift
- ISPs recycle address space
With our previous provider, we saw how static or slowly updated databases can degrade over time. Personalization rules that initially worked well became less reliable months later.
Fresh, continuously validated data turned out to be essential for long-term stability.
What We Looked for in a Geolocation Provider
When we set out to evaluate a new provider, we approached the decision from a product and customer experience perspective.
We prioritized:
- Accuracy and consistency, especially at the city level
- Transparency into confidence, not blind certainty
- Frequent updates and data freshness
- Fast, reliable API performance at WordPress scale
- Responsive support for data corrections
To validate our decision, we ran our own benchmarking tests across multiple providers, measuring city-level accuracy within a 50 km radius.
The results were decisive.
IPinfo achieved 82% accuracy within 50 km, compared to 50% from our previous provider, which was a 32-point improvement. That level of difference directly addressed the customer complaints we had been seeing.
How IPinfo Approaches Geolocation Accuracy
What stood out to us about IPinfo was not just the raw accuracy improvement, but the methodology behind it. Their approach combines multiple signals, active measurement, and continuous validation.
Measurement Signals from ProbeNet
A key differentiator is ProbeNet, IPinfo’s internet measurement platform, which observes network behavior from globally distributed points of presence.
In practical terms, this means IPinfo is not relying solely on registry or WHOIS-style data. They are continuously measuring real-world network conditions.
For If-So, this translated into:
- Fewer unexpected location shifts
- Better city-level stability
- Reduced long-term data drift
Freshness: Continuous Updates and Corrections
Data freshness became one of the most important factors in our evaluation.
Because IP infrastructure changes constantly, continuous updates help prevent the slow degradation that breaks targeting rules over time.
Since switching to IPinfo, we have seen a near-elimination of location accuracy complaints, which strongly validates the importance of ongoing data maintenance.
Built for Real Products
Beyond the data itself, IPinfo demonstrated strong operational reliability:
- Easy API integration into our WordPress plugin
- Stable performance at scale
- Fast support turnaround (often well under 48 hours)
- Production-ready documentation
Our integration process required minimal developer time, which allowed us to move quickly.
Practical Personalization Use Cases Powered by IP Location
With more reliable location data, we have been able to confidently expand our geotargeting capabilities across our platform. Today, customers use If-So with IPinfo to power:
- Location-based banners and promotions
- Localized testimonials and case studies
- Regional pricing and shipping defaults
- Store locator pre-selection
- Timezone-based content scheduling
- Dynamic Keyword Insertion (DKI) by geography
- Lead routing and support assignment by region
As confidence in the data improved, these features moved from experimental add-ons to core personalization workflows.
Better Personalization Starts with Better Location Methodology
Our experience confirmed something important: many frustrations with IP geolocation stem from outdated, static data approaches rather than inherent limitations of the technology itself.
Before adopting IPinfo, accuracy issues created customer friction and limited our ability to scale geolocation as a core offering. After switching, we saw a measurable improvement in accuracy, a sharp drop in complaints, and the confidence to expand location-based personalization across our platform.
Today, geolocation drives more than 50% of our sales, and our API usage has almost doubled every year since 2021.
For If-So, better personalization truly started with better location methodology, and IPinfo provided the reliability we needed to make geolocation a cornerstone of our product experience.
