Published prices. All of them.
Every brand dataset, category bundle, single-state dataset, and government source on this site is priced on the page — down to the 22,365,661-location full US master at $14,900/yr. No quote request, no “contact sales” gate above the hobby tier. The one exception to a flat number is the custom cut, and even that is priced by a published formula, not a person — see below.
The whole ladder
pricing pricing-v2Every dataset we sell, one table. Two rows are explicitly not a flat number — custom datasets are formula-priced (below) and government-source pricing scales by source size — everything else is exactly what you pay at checkout.
| Dataset | One-time | Updates subscription |
|---|---|---|
| Brand dataset priced by location count · under 100: 1,329 · 1,000–5,000: 249 · over 5,000: 55 | $19–$79 | $49–$199/yr |
| Category bundle e.g. Business and Professional Services — 2,519 brands, 7,332,239 rows, $4,998/yr | $199–$1,999 | $498–$4,998/yr |
| Single-state dataset e.g. AK — 589 brands, 56,551 locations, $19/yr | 40% of the Full US master’s price per location, floor $19 save 60% per location against the Full US master, above the $19 floor | proportional, per year |
| Custom dataset any brands × categories × states × columns, quoted instantly | formula — see below | +150% of one-time, per year |
| Government source e.g. USDA SNAP retailers — 238,715 rows | from $199 | scales by source size |
| Ground Truth US 1,720,593 locations · pipeline + government tiers only | — | $4,900/yr |
| Full US master 22,365,661 locations, every tier priced against what building this costs, not a rival's price. | — | $14,900/yr |
Formats: CSV + Parquet on every dataset, GeoJSON on geo datasets. Prices shown are internal-use (×1); the license selector at checkout applies the Embedded (×3) or Redistribution (×10) multiplier. AI/ML training rights are a separate add-on, not a multiplier of the tier price: add 4× the dataset’s internal-use (×1) price to any license tier, on top of that tier’s own price, excluding open-licensed data (including the geometry, timezone, and government-source streams); contact us to add it. Available on Internal, Embedded, or Redistribution.
How custom dataset pricing works
You describe what you want; this formula sets the price. It is deterministic — the same request always quotes the same number — and published here so a quote is never a surprise.
Worked example
a custom dataset of urgent care locations in TexasSame request, same price, every time · shareable permalink
License, in plain English
Three tiers, published rates, picked at checkout — not buried in terms. Each tier’s rate applies to every dataset on this page, one-time or subscription.
Use the data inside your own organization — analysis, internal tools, and reports you don't sell or hand off. The default license, and what every price on this page is quoted at.
Ship the data inside a product or service you sell to others — a customer-facing app, a paid dashboard, a feature built on top of it. Selected at checkout; the price recomputes live.
Resell or hand off the raw data itself to third parties, priced right here at x10 and selected at checkout, with no call, no quote, and no negotiation to enable it, on any brand, category, state, or custom dataset. The Full US master's redistribution license closes by direct agreement, at this same published rate: $149,000/yr.
One-time vs. updates
One-time
A single file, delivered instantly, yours to keep. Right for a point-in-time analysis, a one-off report, or a dataset you’ll refresh manually later.
Updates subscription
A refreshed file with each release of that dataset. Billed yearly. Cancel any time: access runs through the end of the current term, and every file you already downloaded stays yours under your license.
Buying for a team
Card checkout is instant, at any amount. Orders of $5,000 or more can also pay by invoice or PO — Net-30, files unlock once payment is received (typically 1–3 business days by ACH). You enter the company name, billing email and an optional PO number at checkout and we email the invoice; no card is charged. Custom cuts are paid by card; to be invoiced for one, email sales@mogean.com.
Compare: Mogean vs SafeGraph · Mogean vs Foursquare · Mogean vs scraping it yourself
FAQ
These are the checkout prices. Every dataset on this page is self-serve — guest checkout, instant delivery, no sales call. The only two exceptions are marked explicitly above: government-source pricing scales by source size, and redistributing the Full US master needs a private agreement.
One-time buys a single file, delivered instantly, yours to keep. The updates subscription delivers a refreshed file with each new release of that brand, category, or state. Cancel any time; access runs through the end of the current term.
By a published formula, not a person: locations in your selection times a per-tier rate, floored at $29, then scaled by your license type — capped so it never costs more than the cheapest published dataset that already contains what you asked for. See the worked example above.
We accept cards for any order size, instant checkout. For orders of $5,000 or more, you can also pay by Net-30 invoice with a PO number — files unlock once payment is received. Custom cuts are paid by card; to be invoiced for one, email sales@mogean.com.
Every dataset on this page is cut from one dated release (data as of 2026-11-01). Every location carries a provenance tier that says where it came from and how it was verified: a brand's own store locator, a government registry, or open data. A release that fails its automated checks doesn't ship. The methodology page explains the sources, how often they are refreshed and the checks each release passes. The changelog explains how store openings and closures are counted from Mogean's dated releases.
Yes, and it is public, no sign-up. The docs carry the data dictionary (every column with its type, an example value and how often it is filled), delivery formats, licensing and the schema changelog. The loading guides show how to open each file format with DuckDB and Python, with examples tested against real files.