North America · USDProgrammatic SEO in United States
The most saturated programmatic market on earth — and the one where thin pages get demoted fastest.
We build and run programmatic SEO surfaces for US companies — from the data model and the templates to the publishing engine, the performance budget and the monthly index hygiene that keeps them ranking.
One engine, six moving parts — running in United States
Programmatic SEO is not a content order. It is a data model, a template system, a performance budget and a maintenance routine that has to keep working after launch. We own all four.
Keyword matrix, sized before a line is written
We map every entity you own — locations, products, integrations, providers — against real US demand, then cut the combinations that would produce a page nobody searches for. Typically 60–80% of a proposed matrix does not survive this step, and that is the point.
Templates with a uniqueness gate
Each template ships with a minimum-unique-content threshold enforced at publish time. A page that cannot clear it is held back, not published thin. This is the single biggest defence against the scaled-content abuse policy.
First-party data plumbing
Sheets, Airtable, your product API, your listing feed, your CRM — we wire the real source and keep pages live against it. Data that changes gets a freshness date; data that dies gets a 410, not a soft 404.
Performance budget enforced in CI
US SERPs are mobile-first and brutally competitive. We hold LCP under 2.5s and INP under 200ms on a mid-range Android over 4G, and the build fails if a template regresses past budget.
Schema, entities and AI answer surfaces
Service, Product, FAQ, Breadcrumb and ItemList JSON-LD per template, plus llms.txt, entity files and citation-ready summaries so ChatGPT, Perplexity, Gemini and AI Overviews can quote you accurately.
Index governance, monthly
Coverage reports, crawl-budget triage, cannibalisation checks, pruning of the bottom decile and consolidation of near-duplicates. Programmatic surfaces do not fail at launch — they fail in month seven, unmaintained.
Industries we build these surfaces for in United States
Each vertical has its own page types, its own data source and its own failure mode. Pick yours to see what we'd actually ship.
Integrations, Alternatives, Use Cases, Templates
The highest-converting SaaS pages are the ones your product already implies: every integration pair, every competitor alternative, every job-to-be-done. We generate them from your own product data so each page carries something only you can publish — real field mappings, real limits, real screenshots — instead of a paraphrased feature list.
- X + Y integration pages
- Alternatives / vs pages
- Use-case pages
- Template & example galleries
- Free tool pages
Reference implementations, not clients or partners. Listed because their public page architecture is worth studying.
Who we run programmatic SEO for in United States
Different buyers, different matrices, different risks. The engine is the same; the model is not.
SaaS & product teams
You have an integrations directory, a competitor set and a dozen use cases sitting in your product data. That is a few thousand legitimate pages waiting to be built — provided each one carries real field-level detail rather than a rewritten feature blurb.
The United States page architectures worth copying
Real operators, described by what they actually publish. We build the same structural discipline into surfaces a fraction of their size.
Entity-per-property at national scale
Zillow's public surface is a textbook entity model: a page per property, a page per building, a page per neighbourhood and a page per market, each generated from the same structured record and each carrying data no editorial team could hand-write.
- Property, building, neighbourhood and market layers stack rather than compete
- Freshness is the product — stale inventory is retired, not left to decay
- Home-value estimates give every page a data point competitors cannot copy
The order we work in for United States
No batch of pages goes live before the batch before it has been measured. That sequencing is the reason these surfaces survive core updates.
Demand and gap audit
We pull your Search Console, your competitors' indexed page types and the US SERP layout for each intent class. You get a written list of the page types that can realistically rank, and the ones we advise against.
Entity model and URL architecture
Clean, shallow URLs with taxonomy expressed as tags rather than folders — the same structure logic we use across the WBP site. One canonical home per entity, no duplicate paths.
Pilot batch of 50–200 pages
We ship a small batch first and let it get indexed and measured. Nobody publishes 20,000 URLs on trust. If the pilot does not earn impressions in 4–6 weeks, we change the template, not the volume.
Scale with quality gates
Once the pilot proves out, the engine publishes in controlled waves with the uniqueness gate, performance budget and schema validation running on every page.
Internal link fabric
Hub pages, sibling links, contextual cross-links and breadcrumb chains generated from the entity graph — so authority reaches the deep pages instead of pooling at the top.
Measure, prune, refresh
Monthly: what ranks, what stalls, what gets cited by assistants. Winners get expanded, stalls get rewritten, the tail gets consolidated or removed.
How the United States build actually runs
Your data, your WordPress, your domain. We bring the engine, the gates and the discipline.
We publish from the source you already trust.
No re-keying, no CSV graveyard.
Google Sheets, Airtable, Notion, your product API, WooCommerce catalogues, MLS and listing feeds, or a plain CSV drop. Each row becomes a page, each update becomes a revision, and each removal becomes a proper 410 rather than an orphan.
United States in numbers
Figures we work from, with the source stated. Where a number is directional, we say so.
What building at scale in United States is actually like
Almost every category in the US already has someone running a template at scale. Zapier has integration pages, G2 has comparison pages, Zillow has one page per address. So the question is never whether programmatic works here. It's whether your version of it survives contact with a market where the incumbents publish better data than you do.
What we see repeatedly: a US surface launches with 4,000 URLs, indexes 900 of them, and stalls. Not a penalty — a budget problem plus a sameness problem. Google crawls the first few hundred, finds the same three paragraphs with the city swapped, and quietly stops asking for more.
So the work here is unglamorous. Get a real data source. Prove per-page uniqueness before publish, not after. Keep LCP inside budget on a 4G connection out of a Midwest suburb, not on your MacBook.
The failure modes we keep finding in United States
Scaled pages don't get demoted for being scaled. They get demoted for being interchangeable, slow, or wrong about the place they claim to serve.
The March 2024 core update plus the scaled-content-abuse policy hit template surfaces that added no information. In the US the enforcement is visibly faster because the corpus is bigger — Google has plenty of alternatives to serve.
Large US catalogues routinely submit 20k+ URLs from a domain with a handful of referring domains. Googlebot samples, finds low value, and slows down. The fix is fewer, denser pages plus an internal-link mesh that actually points at the deep set.
Commercial US SERPs are ad-heavy. Pages built for position tracking rather than for click-through under-perform their rank.
"Best plumbers in Toledo" written from a national dataset reads national. Users bounce, and the engagement signal follows.
How we build a United States surface
Same order every time. The uniqueness gate and the performance budget come before a single page publishes.
- 1Source a defensible dataset
Public APIs, licensed data, or your own product telemetry. If two competitors could generate the same page from the same scrape, the page isn't worth publishing.
- 2Set a uniqueness gate
We shingle every draft against the rest of the set and block anything above a similarity threshold before it reaches the queue. Blocked pages either get more data or don't ship.
- 3Budget Core Web Vitals per template
One LCP budget, enforced in CI. No template ships if the p75 field estimate breaks it.
- 4Publish in waves and measure
Batch one goes out, we watch indexation and impressions for two weeks, then batch two. Publishing 8,000 URLs in one night is how surfaces die.
- 5Build the internal mesh
Hub pages, sibling links and breadcrumb chains so deep URLs sit three clicks from the homepage instead of orphaned in a sitemap.
United States companies and tools worth studying
Not partners — reference implementations. External links are nofollow.
Automation platform with tens of thousands of integration pages.
The reference implementation of app-pairing programmatic SEO — every page is backed by a real live registry, which is why it holds.
zapier.comBacklink and keyword research suite.
Its free-tool and glossary surfaces show how utility pages earn links that a plain template never will.
ahrefs.comSoftware review marketplace.
Comparison pages backed by first-party review volume — the data moat is the reviews, not the template.
g2.comReal-estate marketplace.
One indexed page per listing, sustained for years, because each carries genuinely unique data.
zillow.comEdge network and caching.
Where most US programmatic surfaces get their TTFB back after the origin buckles under crawl load.
cloudflare.comFrontend hosting with ISR.
Incremental static regeneration is the practical way to keep 50k pages fast without a nightly full rebuild.
vercel.comWhat you'd build this on
| Option | Best for | Trade-off |
|---|---|---|
| Content teams that need editorial control over generated pages. | Needs disciplined caching to survive crawl spikes. | |
| Product-led SaaS with a live data source. | Engineering time you may not have spare. | |
| Marketing teams under ~10k pages. | Item limits and shallow control over rendering. | |
| Very large read-only catalogues. | Full rebuilds get slow past a certain size. |
Cities in United States
Each city has its own angle, its own blockers and its own first moves — because they genuinely differ.
Finance, media and legal — the highest-CPC borough-level SERPs in the country.
Product-led SaaS — where integration and alternative pages carry more weight than location pages.
Manufacturing, logistics and legal — service-area intent with genuine local volume.
Fast-growing tech and consumer brands with under-built local SERPs.
Bilingual demand and a LATAM gateway — the one US market where Spanish pages genuinely earn their keep.
Cloud, retail tech and a Bing share that's higher than the national average.
Industries we build these surfaces for in United States
Programmatic SEO in United States — straight answers
Will a programmatic surface get us penalised in the US?›
Not by itself. Scaled pages that add nothing get demoted; scaled pages built on real data get indexed. The policy targets value, not volume.
How many pages should a first US batch be?›
Usually 150–400. Enough to read a signal, small enough to reverse cleanly if the signal is bad.
Do we need separate Spanish-language pages?›
Only if you can staff them properly. A machine-translated duplicate set is a liability in a market this competitive.
How long before we see indexation?›
First crawl within days, meaningful impression data in four to six weeks, revenue attribution usually in a quarter.
Want the United States surface scoped before you build it?
We'll audit the data source, size the first batch, set the performance budget and tell you honestly if programmatic is the wrong tool for your category.
Other markets
United Kingdom
Canada
Australia
Germany
United Arab Emirates
Singapore
Saudi Arabia
Netherlands
France
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Italy
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Switzerland
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Norway
Denmark
Poland
Portugal
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Austria
Finland
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Greece
Japan
South Korea
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Oman
Turkey
Egypt
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Nigeria
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Brazil
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Chile
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Hong Kong
Taiwan
Pakistan
Hungary
Ukraine
Jordan
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Peru