Programmatic SEO Architecture
Turning data assets into organic acquisition channels at scale. Not content operations — infrastructure.
Programmatic SEO architecture is the practice of building systems that generate query-capturing pages from structured data rather than producing content manually. Done right, it lets a single well-designed template serve thousands of queries that would be impossible to address one page at a time.
The operative word is data. The architecture is only as good as what it's built on. If the data doesn't offer something genuinely useful at the query level — specific, accurate, differentiated — the system just scales mediocrity. The pages exist but don't earn visits, don't earn citations, and eventually don't earn rankings.
When it makes sense
Programmatic architecture is the right investment when several conditions are true simultaneously:
Data with genuine utility. You have data that is proprietary, licensable, or acquirable at a level of granularity that competitors aren't serving. Rate data, inventory data, location data, pricing data, product specifications — anything where the value is in the specifics, not the summary.
A large enough query surface. If there are hundreds or thousands of variations of the same underlying question — by location, by institution, by product type — and each variation has real search demand, a template-based approach outperforms manual content production by an order of magnitude.
Engineering capacity to build and maintain it. This is infrastructure, not a content calendar. It requires a pipeline, a data layer, and templates built to render correctly for both crawlers and users.
When it doesn't
The failure cases are instructive:
No genuine data differentiation. If the data is the same as what incumbents already have, the pages have no reason to exist. Structured presentation of commodity data isn't a value proposition.
AI-generated content as a substitute for data. Using AI to generate thousands of pages that technically have unique prose but no underlying data utility is scaled thin content. It produces the appearance of programmatic architecture without the substance. Google has gotten progressively better at identifying it, and the manual action risk is real.
Query surface too narrow. If the variation space is small — a few dozen permutations rather than hundreds — the infrastructure investment outweighs the return. Manual content production is the right answer.
No engineering capacity and no path to build it. Strategic direction without execution isn't enough here. The architecture has to get built.
The pitfalls — including ones I've encountered directly
At Fortune, I led the development of a content engine using licensed Curinos financial data to capture high-intent queries that manual editorial teams couldn't reach. It was a successful proof of concept in data utility and freshness. However, it also provided a front-row seat to Google's evolving stance on site reputation. The policy changes revealed that Google's primary concern isn't just utility—it's topical proximity. If content, however useful, is perceived as being "hosted" rather than integrated into the site's core authority, it faces significant headwind. Success today requires a clean line between your data assets and your domain's established topical footprint.
The lesson isn't that programmatic architecture is risky. It's that the value has to be in the data and the utility, not in the domain authority underneath it. A system built on genuine data differentiation on a clean domain doesn't have this exposure. A system built on borrowed authority with thin data does.
Template cannibalization. When the data differentiation between pages is too thin, the pages compete with each other rather than targeting distinct queries. The template logic has to reflect real variation in the underlying data.
Data freshness decay. Programmatic pages built on stale data degrade over time. The pipeline has to be maintained. Financial data in particular has a short shelf life.
Rendering infrastructure failures. A programmatic system that produces thousands of pages that can't be crawled or rendered correctly is worse than not building it. The technical foundation has to be solid before scale is added.
How I've done it
At Fortune Media
Licensed savings and CD rate data from Curinos — including granular state-level CD data — across competitive verticals. That data was the specific answer to two bottlenecks: editorial capacity that couldn't scale to cover the query surface manually, and data freshness that the editorial team couldn't maintain at the rate the content required. Designed template architecture to capture high-intent queries at scale on Fortune's domain, driving significant traffic and revenue outcomes before the site reputation policy changes clarified the boundaries of what works on a publisher domain.
At Banksparency
Built the entire pipeline from scratch — no licensed data, no inherited authority, no editorial team, no link-building efforts or budget. A serverless architecture ingesting daily financial data from 80+ institutions, structured into query-capturing pages targeting granular queries the category incumbents have no interest in serving. Roughly 9–10K monthly pageviews. Proof of concept that data utility drives discovery without content operations.
Two different approaches, same underlying principle: the data has to earn the page's existence.
What an engagement looks like
The right engagement depends on where you are and what you need:
Strategic validation. You have a programmatic concept and want an experienced assessment of whether the data, the query surface, and the technical approach are sound before committing engineering resources.
Architecture and specification. I design the pipeline, the template logic, the query coverage strategy, and the rendering infrastructure. Your engineering team builds it. I spec what they build and stay involved through execution.
Embedded direction. For teams that need ongoing strategic oversight through the build, I work directly with product and engineering to ensure the architecture gets implemented correctly and evolves as the data and query landscape changes.
Fractional or part-time. For companies that want senior direction embedded more deeply, I'm available on a part-time or fractional basis.
Every engagement starts with an honest assessment of whether programmatic architecture is the right investment for your specific situation. If it isn't, I'll say so.