Programmatic SEO Checklist

Pre-build your top ~500 pages by traffic and use on-demand fallback ('blocking') for the rest. Keeps build times under a couple of minutes at 100K+ pages instead of 30+ minute full rebuilds.

Before generation, build an intent matrix (e.g. 'San Francisco Plumbers' = local, 'Plumbing Tools' = commercial). Use it to prevent templates from cannibalizing each other.

Generate a small cohort and measure performance before scaling to thousands. If it underperforms after a few months, fix intent match and data quality before expanding.

Start with 10-20 pages, then ramp to 50-100 per week. Publishing thousands of pages at once triggers algorithmic scrutiny and risks penalties.

Score every generated page on a 100-point scale (data completeness, uniqueness, engagement, technical health). As a rule of thumb, auto-noindex weak pages and flag borderline ones for human review. The exact cutoff is your own quality bar, not a Google standard. A common starting point is to noindex below ~70 and review 70-79.

Measure unique word count across sibling pages and consider noindexing very thin variants to avoid thin-content issues. There's no official Google minimum; a threshold like ~500 unique words is a practical rule of thumb, not an established standard.

Use automated scoring to measure content deviation between templated pages, and merge or consolidate near-duplicate siblings into their parent hub. A target like ~30%+ unique content is a useful internal heuristic rather than a documented Google threshold.

Apply the Nomad List-style principle that every generated page should carry genuinely unique, non-boilerplate data rather than just templated filler. Setting a minimum (e.g. a handful of distinct data elements) is a sensible internal rule of thumb, though the specific count is your own bar, not a documented Nomad List standard. Pages that fall short get noindexed automatically.

Flag pages with stale data, broken feeds, or outdated API responses before they publish. Prevents wasting crawl budget on dead pages.

Run a GSC analysis for multiple URLs ranking for the same keyword, then 301-redirect weaker variants into the strongest. Consolidation studies show large traffic uplifts.

Track indexed vs submitted pages in GSC monthly. A low indexation rate is a signal that Google sees limited value in many pages. Fix it via better TTFB, internal linking, and less sitemap spam. A target like ~70%+ is a practical benchmark to aim for, not an official Google threshold.

Use a CDN, optimize database queries, and cache aggressively. Time To First Byte under 200ms is a baseline threshold for crawl efficiency at 100K+ pages.

Audit site architecture monthly. Pages deeper than 3 clicks get deprioritized crawl budget. Use breadcrumb links and category hubs to flatten depth.

Create separate, descriptively named sitemaps (sitemap-cities.xml, sitemap-products.xml). Split into many files at scale. Only lastmod matters, so ignore priority and changefreq.

Add a robots/meta rule to noindex any page scoring below your quality threshold, keeping thin variants out of the index until they're improved.

After ~6 months with zero traffic: enrich with unique data, consolidate into a parent, 301 to a sibling, or 410 delete. Don't let ghost pages accumulate and waste crawl budget.

Every child page (e.g. 'Plumbers in San Francisco') must link up to its parent ('Plumbers in California') to create crawlable pathways and authority flow.

Link each page to nearby or related variants (SF → Oakland, San Jose). Creates relevance signals and prevents orphaned content.

Hub pages target broad head terms; spokes target long-tail. Link every spoke back to its hub and to 3-5 sibling spokes. Never mix intents within a single hub.

Link definitions to comparison pages, comparisons to product directories, and back again to build semantic relationships across template types.

Add the right schema for each template: Product + AggregateRating for reviews, FAQPage for Q&A, LocalBusiness (with lat/long) for locations, BreadcrumbList for hierarchy.

Most programmatic sites skip breadcrumb markup. Add nested BreadcrumbList JSON-LD clarifying the Category → Subcategory → Item hierarchy. ~30 minutes per template.

Convert 'Common Questions' blocks into a clean Q&A format, which AI systems extract more readily than long body prose. FAQ rich results were deprecated in 2023 and schema alone has minimal direct AIO effect, so treat mainEntity/acceptedAnswer FAQPage JSON-LD as an optional add-on, not the lever.

LLMs extract roughly the first ~2,000 words for grounding. Put unique data, specs, or CTAs up top, and use modular 40-60 word paragraphs for distinct vector embedding.

Create a /llms.txt route listing 10-20 core hub URLs (not individual programmatic pages) plus a brand description and a checkable fact. Auto-update it from your CMS. Adoption by major AI crawlers is still unproven (near-zero measured citation lift so far), so treat it as low-cost insurance, not a citation lever.

Roughly a third of international sites have conflicting hreflang tags. Use subdirectories (example.com/fr/) over subdomains and verify bi-directional return tags.

Use a GSC Page regex like ^https://example\.com/(city|state|product)/ to isolate each template and track impressions, CTR, and position separately from editorial content.

Use GA4 regex filters matching your URL structure to compare conversion rates between templates and identify which patterns earn the most revenue.

Set alerts for stale content: delayed API responses, missing fields, or expired dates (e.g. event validThrough). Schedule quarterly refreshes for high-traffic pages.

Use descriptive alt text, an image sitemap, and ImageObject schema. Prefer load-more buttons over infinite scroll for SEO, and only index high-volume filter combinations.