Supabase locations table with geo-indexing. Template-driven location page generation with unique signals per location (hours, team, local testimonials, neighborhood context). LocalBusiness schema with correct location data per page. Sitemap per region for crawl budget management. Central brand governance layer with per-location content permissions.
Where enterprise projects fail
And that's a massive problem. Near-me and city-level searches convert at 2-3x the rate of generic category searches, because those users already know where they are and what they want. They're basically ready to call. So while you're absent from those results, a smaller competitor -- sometimes a single-location operation with zero other advantages over you -- is capturing every one of those high-intent leads. We've seen this play out in markets from Phoenix to Chicago. The traffic you should own by default is just... going elsewhere.
Google's pretty good at detecting that, honestly, and once it decides your location pages are thin content, it'll consolidate or drop them from the index entirely. That's when things get painful. Recovery isn't just a matter of adding a few paragraphs -- the real kicker is that Google needs to see consistent quality signals over time before it'll reconsider those pages. Could take months. And in a competitive local market, those are months where a competitor is collecting every organic click your pages should've been generating.
That's cannibalization -- and it's incredibly common in franchise systems. Instead of one page concentrating all the ranking potential for "plumber in Denver," you've got two pages splitting it, and both rank worse than they would've alone. Plus the inconsistencies in content and structured data create trust signal confusion that quietly drags down your whole domain's authority. Nobody wins that situation.
What we deliver
Franchisees swapping city names into the same template is why Google flags your pages as thin and your near-me traffic goes to a single-location competitor. We've built 500+ location pages in one Next.js codebase with per-location LocalBusiness schema and real differentiation -- so Denver stops competing with your own Aurora location for the same keyword.
See this capability in action
Frequently asked
How do you create unique content for hundreds of location pages without writing each one manually?
Each location page generates from a structured database record containing that location's actual data -- team members, local service variants, hours, neighborhood context, testimonials from real customers at that specific spot. An AI generation layer turns those data points into natural prose, which then gets scored for uniqueness and quality before anything publishes. The pages read like someone wrote them by hand. But they're produced at scale. And for locations with particularly rich local data -- a long-established store in Boston with dozens of reviews and a well-known local team -- we layer in human-written paragraphs on top to push the uniqueness signal even further.
How should we handle two locations that are close together competing for the same search term?
Two nearby locations shouldn't target identical city-level terms. That's just splitting authority for no reason. Instead, the architecture separates them by hyper-local signals: Location A targets the neighborhood-specific terms for its actual catchment area, Location B does the same for its own neighborhood, and both link up to a city-level hub page that aggregates them. The hub is what competes for the broad city-level term -- "electrician in Seattle," say -- and then routes traffic to the right location based on what the user's actually looking for. You capture the full city-level search volume without two pages undercutting each other.
What structured data is required for multi-location businesses?
Every location page needs LocalBusiness schema -- or the right subtype, because Google cares whether it's a Restaurant versus a MedicalBusiness versus an AutomotiveBusiness. Each instance needs accurate PostalAddress, telephone, openingHoursSpecification, and geo-coordinates. You'll also want BreadcrumbList schema reflecting the location hierarchy, and if you're pulling in reviews, AggregateRating nested within the LocalBusiness schema. Here's the thing people miss: none of this can live only at the root domain level. A single Organization schema for the whole company doesn't tell Google anything useful about your Portland location specifically. Per-location generation isn't optional -- it's the whole point.
How long does it take to see ranking improvements across all our locations after the project launches?
Most enterprise clients see measurable ranking movement in tier-2 markets within 60 to 90 days of going live, though competitive metro locations can take longer. Timeline depends on how much technical debt exists across your current location pages. We prioritise the weakest-performing markets first so you capture quick wins while longer-term optimisation continues in parallel.
What does multi-location SEO typically cost for an enterprise with 40 or more locations?
Pricing starts from a project scoping fee, then moves to a monthly retainer based on location count, audit complexity, and how much franchisee coordination is involved. We do not charge per-page fees that balloon your invoice as you grow. Most enterprise engagements fall into a fixed monthly structure covering audits, content templates, technical fixes, and reporting -- contact us for a tailored estimate.
We are based in the US but want a UK agency -- how does working across time zones actually function day to day?
Working with a London agency from North America is straightforward in practice. Our core hours overlap with US East Coast mornings, and we use asynchronous tools for everything else so nothing blocks progress overnight. You get a named account lead, a shared project board, and fortnightly video calls. Most clients say the time difference causes fewer delays than internal approval chains do.
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