Scraping store locators yourself, or buying the dataset
You can build a US points-of-interest dataset yourself: collect brands' store-locator pages, add government registries and open data, and keep it all current. Mogean does that work and sells the result. This page sets out what the work involves and what Mogean's side of it looks like.
Everything about Mogean here is stated on the methodology and pricing pages. What the work costs you depends on your team, so there is no figure for it on this page.
Side by side: the work
| Mogean | Doing it yourself | |
|---|---|---|
| Finding the sources | 3,194 brands and 17 government sources in one catalog, plus open geospatial data (Foursquare Open Source Places and Overture Maps). | List every brand you need and find each one's store locator. Add government registries and open datasets for what locators do not cover. |
| Getting the records out | Extracted directly from each brand's own store locator, not from a third-party directory. | Write and test an extractor for each locator. |
| Keeping up | 201 brands re-extracted in the current release, published as dated releases (current data as of 2026-10-11). | A change to a locator can break its extractor, so each one needs watching and fixing. |
| Combining sources | Records are matched on name, address and geographic proximity into one location, with the surviving record chosen by source priority. | Match the same place across sources and decide which record wins. |
| Knowing where a row came from | Every row carries a provenance tier: brand-extracted, government registry, Foursquare-derived or Overture. | Record each row's source yourself. |
| Checking the result | A release that fails its automated checks does not ship. | Write your own checks for addresses, categories, duplicates and counts. |
| What it costs | Published prices: brand datasets $19–$79 one-time, category bundles $199–$1,999 one-time, single-state datasets $19–$662 a year, the full US master $14,900 a year. Free sample rows on the dataset pages, no sign-up. | Engineer time, hosting and upkeep. It depends on your team. |
When doing it yourself makes sense
If you need a site that is not in the catalog, or a field the catalog does not carry, writing your own extractor may be the right call. Mogean's methodology page lists its known limitations: smaller and regional chains are still being onboarded, and independent businesses are covered only where a government registry or open dataset includes them.
If what you need is the locations for known brands, categories or states, with the sources recorded and the file in hand, that is what the ladder sells.
The whole ladder, the custom-dataset formula and the license tiers are on the pricing page. How the data is built and checked is on the methodology page, and the schema and loading guides are in the docs.
FAQ
For each brand you need, find its store locator, write an extractor, and fix it when the locator changes. Then add government registries and open datasets for what locators miss, match the same place across all of them, record where each row came from, and re-run it on a schedule. Mogean's methodology describes how it does each of these steps.
It depends on your team's time and how many brands you need, so this page gives no figure. On the buying side: Published prices: brand datasets $19–$79 one-time, category bundles $199–$1,999 one-time, single-state datasets $19–$662 a year, the full US master $14,900 a year. Free sample rows let you check a dataset before you pay. See pricing.
Every row traces back to a brand's own store locator, a government registry, or open geospatial data. The methodology page names the sources and the checks each release passes.
Mogean publishes dated releases; the current one is data as of 2026-10-11, and 201 brands were re-extracted in the current release. The changelog shows what changed.
Yes. Free sample rows on the dataset pages, no sign-up. The docs cover the schema and how to load the files.