South San Francisco, California

What the business base is made of, what it is specialised in against the national pattern, and what that mix implies. This is the part a development office would read first.

Composition, not health. geonet records what trades exist and where; it does not record formation, closure, employment or revenue, so none of those appear here. What makes this economics rather than a directory is the NAICS coding: it lets the local mix be read against the BLS survival curves and against the 323 industry groups this research has screened.

What this city is specialised in

Location quotient is this city's share of a trade divided by the same share across 10 US metro tables. Above 1.25 is the conventional threshold for a local specialisation.

The census: the only figures on this page that count people rather than businesses, and the three cohort readings they make possible.

The register says what trades exist. The census says who lives here — and it is the only thing on this page that counts people. Figures are American Community Survey 2019–2023 five-year estimates for South San Francisco city, California, the incorporated place, which is the city proper, and every comparison is against the United States as a whole, from the same ACS tables.

Detailed language is not published for American places. B16001, the table with individual languages, has no place-level rows; C16001 is what exists, and it names six languages and groups the rest into families. A Canadian city on this site names about forty.

Who the city is for

Three readings, each built from real numbers against real benchmarks. This is not an index. Every signal is shown with its own value, its benchmark and which way it points, and the band simply counts how many point the same way — so a reader who disagrees with one signal can drop it and still use the rest.

A community appears in the business register before it appears in prose — a national church, a society, a credit union, a newspaper. Those are counted as institutions, and they are what suggests residents. A restaurant serving a cuisine is counted separately as trade, because every city has those and they say nothing about who lives nearby. The ranking is by institutions.

Streets, not neighbourhood names. The data knows that Greek institutions sit on one street and Greek restaurants on another; it does not know the word "Greektown", so it does not use it.

Every business on file, grouped by the sector it trades in. This is the economic-development view: where the 1,356 businesses actually are, and the specific trades inside each sector.

Brands from a register of 2,024 franchise systems, matched into this city by name. A high count is a signal in both directions: the territory works, and it may be taken.

15 of these brands are a single common word — Metro, Avenue, Budget — so their counts include businesses that merely share the word. They are marked rather than dropped.

Four unrelated jobs share the name: selling existing homes, owning and letting them, managing them for someone else, and building new ones. For anyone weighing a move or a licence these are the counts — and the ownership question goes to /property, which answers it building by building.

Real estate is a local job market in its own right, and four unrelated trades get the same name. Counts are businesses filed under each trade in the register, which lists a brokerage once however many agents work there — so this measures firms, not licensees.

The Ultimate 411 half of local: everything where the customer does not have to come to you.

A shop needs the customer to walk in. These 157 services do the opposite — the mobile mechanic, the mobile groomer, the bookkeeper, the junk haul — and they are the ones a person can start without a lease. 0 of them already match a trait filed in this city's register.

The 157 Service=1 rows in search.local: work where the provider travels to the customer. "present" counts businesses already filed under that exact trait name; a blank is a coverage gap, not proof of absence, because the two vocabularies were built separately.

wander.schools is a post-secondary table — universities and colleges. K-12 public and private schools are not in it, and only 7 of its 1,686 rows carry coordinates, so these are listed and not mapped.

What a person moving a parent here would ask first. The register files clinics and pharmacies; it has no category for a hospital at all, so hospitals are matched by name and the limit is stated rather than hidden.

geonet carries no 'hospital' trait, so these are matched on the business name. A distance-to-hospital figure needs a source that states hospital locations.

Named in full, because the gaps are the part most likely to be misread as an answer.

• Census figures are 2021, taken on 11 May 2021: income is for 2020 and the labour figures were measured mid-pandemic, so the unemployment rate on this page is a 2021 reading rather than a current one.
• wander.schools is now readable, but it holds universities and colleges only and 1,679 of its 1,686 rows have no coordinates. K-12 public and private schools need a separate source — in Ontario the Ministry of Education school finder, in British Columbia the provincial school list. wander.citytowns, hotels and territories remain denied to the ru user.
• No 'hospital' trait exists in geonet; distance to a hospital needs an external source such as StatCan's Open Database of Healthcare Facilities.
• 0.0% of businesses here carry no coordinates, so a map or address lookup would miss them. Postal codes reach 100%.