BigGeo's Cell Towers dataset delivers tower coordinates, carrier identifiers, radio technologies, and estimated coverage ranges for 100,000 sites, ready for immediate spatial analysis. For the first time, your team can identify underserved coverage areas, prioritize deployment targets, and validate site acquisition decisions without a single field survey.

Most data vendors sell you a national license to millions of records you will never contact. BigGeo works differently.You tell us where you sell, and we cut you exactly that geographic slice of the dataset. A single city.
A cluster of ZIP codes. A metro area. A county. Whatever matches your territory. The result is a lean, CRM-ready file containing only the companies in the markets you actually work, delivered at a fraction of the cost of a full national license.

Wireless infrastructure teams are making six-figure deployment decisions on data that is incomplete, outdated, or locked inside formats no one can query at speed. Field surveys eat weeks of budget. Coverage models built on bad tower data produce bad tower placement. And every week a dead zone stays unaddressed is a week a competitor or a federal broadband program fills it instead.
Every record includes geospatially indexed tower locations, so your team can instantly map existing infrastructure, calculate inter-site distances, and identify placement candidates without converting or cleaning raw coordinates.

Carrier identifiers attached to each tower let you analyze competitive coverage density by operator, identify underserved corridors no single carrier has claimed, and build a defensible rationale for new market entry or expansion.

Knowing whether a site runs LTE, 5G NR, CBRS, or legacy technologies tells your engineering team what gaps to fill, not just where. Technology-aware gap analysis changes how you prioritize small-cell versus macro tower deployment.

Coverage range estimates per tower let you model actual signal footprints, overlay them against population or address density, and surface the specific geographies where investment will have the highest coverage yield per dollar spent.

BigGeo AI is live in ChatGPT today and shipping in Claude, giving your engineers and GIS analysts direct access to the Cell Towers dataset through plain language queries, no GIS software required, no data pull, no waiting on a specialist. A site acquisition manager can ask which counties in a target state have fewer than three LTE towers per 100 square miles and get a governed, data-grounded answer in seconds. The underlying tower data never leaves the governed compute path regardless of how the query is routed.
The dataset refresh cadence is defined by the provider and disclosed on the dataset listing inside BigGeo Marketplace. What we can tell you is that the data is indexed and queryable the moment a refresh lands, so your team is always working against the most recently available version, not a stale export sitting in someone's shared drive. For RF planning and site acquisition workflows, we recommend combining this layer with your own ground-truth field data inside DataLab to validate critical site decisions.
Yes, and that is exactly the workflow BigGeo is designed for. Your internal tower records, permit data, or site acquisition files can be uploaded directly into DataLab, where they index onto the same DGGS spatial grid as the Cell Towers dataset. From there you can run combined queries, surface gaps between what you have and what exists in the market, and build coverage models that reflect both your proprietary knowledge and the full external picture.
The Cell Towers dataset contains 100,000 records and is positioned for national scope, which means it includes tower infrastructure across both urban and rural geographies. For grant-specific workflows like BEAD or RDOF applications, the dataset's coverage range attributes allow you to model served and unserved areas directly, rather than relying on FCC Form 477 data alone, which is notoriously optimistic in rural reporting.
No GIS specialist is required to start asking questions. BigGeo AI lets any analyst query the dataset through plain language inside ChatGPT today. For teams that do want direct data access, the dataset is available through BigGeo Marketplace and activates inside DataLab, where it can be queried via API, visualized in DataScape, or exported for use in your existing RF planning tools. Integration is designed to take hours, not weeks.
Request a sample using the form on this page and a BigGeo team member will follow up with a scoped sample relevant to your target geography and use case, not a generic data dump. If you want to see the full workflow before committing, book a 30-minute session and we will walk through coverage gap analysis live against the Cell Towers dataset using your region of interest.