Location data is only as valuable as its usability. Raw geospatial signals are messy, inconsistent, and full of noise. Without thorough processing and transformation, even the largest datasets remain difficult to integrate, analyze, or act on.
It’s common for teams to spend considerable time and resources to turn raw data into actionable signals. That’s why Unacast doesn’t simply sell location data; we make it production-ready by handling the heavy lifting of cleaning, normalizing, and structuring data. Ultimately, this allows our partners to focus on what matters: building products, running analytics, and driving revenue.
The Challenge: Raw Data is a Mess
It’s normal for data teams to assume they need more location data, but the real challenge is making the data they already have usable. Raw location data comes with major hurdles:
- Inconsistencies Across Sources – Different providers use different data formats, timestamps, and accuracy thresholds.
- Noise and Redundancy – Devices generate overlapping signals that must be consolidated without losing valuable metadata.
- Anomalies and Outliers – GPS drift, signal spoofing, and invalid signals contaminate datasets.
- Privacy Risks – Regulatory compliance is ever evolving and often requires a specialist’s attention and enormous amounts of resources.
For most companies, handling these issues in-house is too significant a burden for data teams. The necessary engineering resources, complex forensic analysis, and continuous monitoring are simply cost-prohibitive. Larger enterprises often have the resources, but handing this, even just for location data, is a massive budget line.
Unacast offers another approach.
Transforming Raw Signals into Production-Ready Data
Instead of passing along raw data, Unacast applies multiple layers of advanced processing to transform raw signals into curated and actionable location intelligence.
1. Signal Merging: Consolidating Without Losing Value
Raw signals often contain duplicate or near-identical data points due to multiple pings from the same device. Our signal merging process groups spatially and temporally similar signals while retaining key metadata. By eliminating redundant data points, we reduce storage and processing overhead without introducing artificial smoothing. The result is a dataset that remains lightweight yet rich in insight, making it easier to integrate into downstream analytics and applications.
2. Forensic Analysis: Identifying Irregular Data Patterns
Anomalous data can lead to inaccurate models, poor product performance, and flawed business decisions. Because of how common these anomalies are in the data supplies, Unacast has developed proprietary algorithms to analyze and detect these signals. These “forensic flags” are attached to every signal record to help companies understand which signals are dubious and provide more in-depth analytics to better determine which signals are most relevant for their use case. Unacast’s meticulous validation process ensures that the location data powering our partners' applications is both trustworthy and precise.
3. PrivacyCheck: Enforcing Compliance Without Losing Utility
Privacy remains a key concern in location intelligence, and Unacast enforces rigorous compliance measures. We apply PrivacyCheck, our proprietary privacy-enhancing technology (PET), to ensure that data generated by consumer mobile devices while visiting sensitive locations is never used, shared, or resold. Our PrivacyCheck product has set the standard across the location data industry, not only adhering to stringent compliance standards like GDPR and CCPA, but ensuring that location data is ethically sourced and responsibly processed.
4. Normalization: Delivering Data in a Usable, Consistent Format
Unstructured, inconsistent data slows down integration and analysis. Our normalization process standardizes timestamps, geographic coordinates, and device identifiers, creating a unified schema that is ready for integration into analytics, modeling, and visualization platforms. With Unacast, companies receive clean, reliable, and immediately functional data within their existing workflows.
Why it Matters: More Insights, Less Engineering Overhead
By handling the complexity of location data processing, Unacast enables companies to:
- Reduce engineering workload – No need to build and maintain in-house data pipelines.
- Improve data quality – Clean, normalized data leads to more accurate analytics.
- Accelerate time-to-value – Production-ready datasets speed up product development and decision-making.
- Ensure privacy and compliance – Processed data meets regulatory standards without extra effort from internal teams.
Raw location data is complex, noisy, and inconsistent. Unacast transforms it into high-quality, production-ready data assets, allowing companies to focus on innovation rather than infrastructure.
Let us handle the hard part so you can focus on building what’s next. Get in touch today to see how Unacast can power your location intelligence needs.
Read on for part three in our series on building enterprise-grade location data infrastructure for adtech products.
