Multi-location local SEO: structuring how you run a network

The choice is not ideological. It depends on how many locations you have, whether they are owned or franchised, and how much time local teams genuinely have.

The hybrid model wins in most cases, provided the boundary is written down. Three fields almost always belong to head office: the name, the primary category and the address — the ones where an unlucky edit triggers a suspension. Special hours, photos and review replies belong locally, because they need responsiveness head office will never have.

NAP — name, address, phone. On a single location, consistency is housekeeping; across forty locations it is recurring work, because every inconsistency replicates across every directory, every aggregator and every location page on the site.

Three rules hold a network together. One reference spelling per location, decided once and stored in a master file — including address punctuation and phone number format. A local phone number per location rather than one national number: a number shared by forty profiles weakens the signal on each. One location page per site on the website, which the profile's website field points to — not the group homepage.

That last point is the most neglected and the most costly: forty profiles all pointing at the same homepage transmit no local signal, and the visitor lands on a page where they have to search for the location they had just found.

Two locations of the same brand four miles apart compete for the same local pack across the ground between them. That is unavoidable, and not always a problem: the brand takes two of the three slots, which is excellent.

It becomes a problem when the wrong location wins — the one with the least capacity, the worst stock, or an already stretched team — while the other sits empty. That case is detected by measurement and resolved by arbitration, not by manipulating a profile.

Across thirty sites, effort does not spread evenly. The question to settle each quarter is: where do the three available days of work go?

The most workable sort crosses two axes: the commercial potential of the area — population, competitive density, the site's revenue — and the visibility gap against the network average. High potential and low share of voice is a priority; low potential and low share of voice only deserves a profile tidy-up.

A third criterion settles close calls: the cost of the fix. Completing a profile with no services and no photos takes half a day and produces a measurable effect; closing a two-hundred-review gap takes two years.

A network report showing only an average position is useless: it adds up thirty unrelated situations. The template below reads location by location, with a network total at the head of each block.

One chart makes this report actionable in a second: a scatter plot with completeness score on the x-axis and top 3 share of voice on the y-axis, one dot per location. Dots at the bottom right — complete profile, low visibility — are competition or catchment problems; dots at the bottom left are profile problems, and therefore fixable straight away.

The metrics and how to calculate them are set out in the local SEO KPIs.

Twenty locations times thirty sites is six hundred measurement points: the budget explodes before you have learnt anything. At network scale the rule changes.

Budget four to six locations per site — the site itself, two neighbourhoods in its catchment, a neighbouring town, a competitor — plus two or three boundary points between adjacent sites. Across thirty locations that is around one hundred and fifty points, with three to five keywords: a sustainable setup, and above all one that is comparable site to site.

The condition for comparability is that the placement logic is identical everywhere. Six locations chosen by the same rule across thirty sites produce a ranking of locations; six chosen case by case produce thirty incomparable diagnoses. The placement method is detailed in the tracking points article.

Pinperf tracks every branch on its own named locations and consolidates the results at network level: share of voice per site, comparison between locations, detection of contested boundary areas. Local teams see their profile, head office sees the whole.