Programmatic SEO: How to get started

Programmatic SEO has an image problem. Somewhere between the generative AI boom and Google’s 2024 spam crackdown, the term turned into shorthand for “publish 50,000 AI pages and pray”. That’s a shame, because the principles behind it run some of the most useful pages on the web, and because the people doing it badly were rarely doing programmatic SEO in the first place.

I first wrote this guide in February 2024, alongside my Programmatic SEO course for Traffic Think Tank. This October 2026 version merges in my separate piece on programmatic SEO versus programmatic content (the two get confused constantly) and updates everything for what has changed since: AI-generated pages at scale, Google’s scaled content abuse policy, and the quality guardrails I now consider non-negotiable.

In this guide, I’ll:

• demystify what programmatic SEO is, and what it isn’t, including the most common misconceptions
• explain the difference between programmatic SEO and programmatic content, and how they work together
• walk through what Google’s scaled content abuse policy means for programmatic builds in 2026
• look at examples of programmatic SEO done well
• go step by step through running a programmatic SEO project
• finish with the quality guardrails I’d put on any AI-assisted programmatic build

This is a beginner-friendly guide. It will give you a complete picture of the topic, but it only touches on the main concepts. For the in-depth, specialised version, take my Programmatic SEO course on Traffic Think Tank: six sections, 4+ hours of video lessons, 10,000+ words of written tutorials, and the stories of three practitioners who have run successful programmatic campaigns.

What is programmatic SEO?

Programmatic SEO (pSEO for short) is an umbrella term for programmatic methods of improving organic search visibility. Notably, it includes:

• Automated, scalable content production methods, which are not the same as AI-written content (more on that below)
• A data-driven approach to identifying opportunities and setting strategy
• An emphasis on systems design, not on individual pages or keywords
• A focus on page quality, because a template multiplies whatever you put into it, good or bad

In practice, it usually combines several components. A variety of content sources (ideally including original research and proprietary data) are organised in a content database. That database is connected to a scalable page template. Publishing happens programmatically: data is pulled from the database and arranged in the template according to predefined rules. This makes page publishing and editing programmatic too, which streamlines on-page SEO: fix the template once and every page improves.

Why does programmatic SEO exist?

Programmatic SEO addresses the growing number of highly niche search intents with unique, high-quality pages. “Can dogs eat mango?”, “Google Docs and Google Sheets integration”, “best coworking cafés in Lisbon”: nobody is going to hand-write a page for every one of these combinations, yet every one of them is a real person with a real question.

Done well, pSEO generates organic traffic while providing a real benefit to visitors: every query, no matter how niche, gets a high-quality resource that answers it. It can be very profitable when executed to a high standard. It also lets you scale other areas of SEO, such as content enhancements and internal linking, through the same dynamic process.

Programmatic SEO vs programmatic content: what’s the difference?

With the rise of generative AI, the two phrases are used interchangeably. That leads to programmatic SEO practices being bundled with AI content, and then dismissed along with it. They’re not the same thing, and the difference matters more in 2026 than it did when I first wrote about it.

Programmatic SEO focuses on automating aspects of your SEO strategy. Most often it refers to database-driven, rule-based automation: structured data in, templated pages out, with rules deciding what goes where.

Programmatic content (often just called AI content now) deals with the automated creation and distribution of content. Historically, that meant tailoring content to audience segments across platforms using data on user preferences. Today it mostly means text, images and video generated by large language models (LLMs) and other generative models.

In short: programmatic SEO can involve programmatically generated content, but doesn’t have to. And programmatically generated content doesn’t inherently carry any of the core principles behind programmatic SEO, or any SEO principles at all. A site of 10,000 ChatGPT articles with no database, no keyword structure, no template logic and no unique data is not a programmatic SEO site. It’s just a lot of text.

	Programmatic SEO	Programmatic content
Core idea	A system: database + template + publishing rules	Automated creation and distribution of content
Typical engine	Rule-based automation over structured data	Generative AI, personalisation engines
Main job	Earn visibility for many specific, long-tail intents (pre-click)	Engage and convert the person once they arrive (post-click)
Where the value comes from	The data, the keyword structure, the template’s usefulness	Relevance and personalisation of the content itself
Biggest risk	Thin, duplicate or cannibalising pages	Inaccuracy, sameness, losing the brand voice
Requires SEO principles?	Yes, by definition	No, which is exactly the problem

The original distinction I drew was between pre-click and post-click. Programmatic SEO is about attracting traffic through strategic visibility in search results. Programmatic content is about the experience after the click: personalised modules, tailored recommendations, content that speaks to the segment that landed on the page.

They work well together when each does its own job. Programmatic SEO lays the groundwork: it identifies the long-tail opportunities, builds the database and template, and gets the right person to the right page. Programmatic content then takes the baton, personalising the experience so a visitor who arrived with a narrow question finds the next step (signing up, buying, downloading a guide) that fits them. A comparison site might use pSEO to publish “best {software} for {industry}” pages, and programmatic content to reorder the listings or surface the FAQs most relevant to that visitor’s company size.

Where it goes wrong is when programmatic content is used as a substitute for the programmatic SEO system, rather than a component inside it. And as we’ll see, Google’s spam policies don’t care which label you use.

What are the common misconceptions about programmatic SEO?

There are several prevailing misconceptions:

• “It’s equivalent to spam.” It can be, but only when it’s done with the intention to spam. Not every spam page out there uses programmatic SEO, in the same way that not every programmatically built site section is automatically spam. If your pSEO build contains low-quality (thin or keyword-stuffed), plagiarised or fully automated content with no added originality, no value to the search landscape and no value to the user experience, then it’s likely spam. Otherwise, you’re good.
• “Programmatic SEO only works for niche sites.” Any website can implement programmatic SEO or benefit from its principles. Large organisations managing broad websites often find it easier to execute properly, thanks to research and development budgets, in-house SEO expertise and established authority. Despite popular belief, they might benefit from pSEO principles even more.
• “Programmatic SEO creates low-quality, unoriginal content.” With the right research, a coherent database and a well-organised template that accounts for content SEO, technical SEO and user experience, programmatic SEO projects flourish.

Successful programmatic SEO websites share the same goals, characteristics and approach. Practically, each one has a robust, well-informed and well-organised database, a template, and a scalable way to publish and edit pages.

What changed since 2024: AI-generated pages and Google’s scaled content abuse policy

When I first published this guide, the March 2024 core update was rolling out. With it, Google introduced three new spam policies: scaled content abuse, site reputation abuse and expired domain abuse. The first one is the one every programmatic SEO needs to understand.

Google’s announcement said it was strengthening action against producing content at scale to boost rankings, “whether automation, humans or a combination are involved”. When the rollout finished in April 2024, Google reported 45% less low-quality, unoriginal content in search results, beating the 40% it had predicted.

The spam policy itself defines scaled content abuse as generating many pages “for the primary purpose of manipulating search rankings and not helping users”. Its examples read like a list of every lazy programmatic build I’ve ever audited:

• using generative AI tools to generate many pages without adding value
• scraping feeds or search results and generating pages from them, including through automated transformations like synonymising or translating
• stitching or combining content from different pages without adding value
• creating multiple sites to hide the scaled nature of the content
• creating many pages that make little sense to a reader but contain search keywords

Then, in January 2025, Google updated its Search Quality Rater Guidelines. As Search Engine Land reported, raters are now told to give the Lowest rating when all or almost all of a page’s main content is copied, paraphrased, or auto- or AI-generated with little effort, little originality and little added value. The guidelines also gained a scaled content abuse section of their own, naming generative AI as one example of a low-effort tool for mass-producing pages.

Google’s guidance on using generative AI content completes the picture. Generating many pages without adding value may violate the scaled content abuse policy. AI outputs can contain hallucinations, so fact-check them, and that includes metadata (titles, meta descriptions, structured data and alt text). E-commerce sites are also asked to label AI-generated images and product data.

What this means for programmatic SEO (my read)

Notice what none of these documents say: they don’t ban templates, databases, automation or AI. Google’s 2023 guidance on AI-generated content already said its focus is on the quality of content rather than how it’s produced, and that using automation primarily to manipulate rankings is the problem. The policy targets intent and value, not method. That’s exactly what good programmatic SEO practitioners have always said.

What has changed is the bar. In 2020, “we organised a dataset into a useful template” was differentiation in itself. In 2026, anyone can spin up 10,000 AI-written pages in an afternoon, so a template wrapped around generic text is no longer worth much. The value has to come from things a language model can’t produce on its own:

• Proprietary or first-party data: your product catalogue, your reviews, your pricing, your usage data, your original research
• Aggregation that saves real effort: combining sources the user would otherwise have to visit one by one, and doing the comparison for them
• Useful functionality: filters, calculators, maps, comparison grids, live availability
• Information gain: something on each page that the rest of the results don’t already say

There’s also an AI search angle. A page that merely reformats a public dataset is exactly the kind of answer an AI Overview or a chatbot can now produce by itself. In my opinion, programmatic pages that hold up in 2026 are the ones built on data and functionality the answer engines have to cite or send people to, not the ones they can trivially replace.

What are examples of programmatic SEO?

These are examples I highlighted in 2024. Templates change all the time, so look at the current versions yourself, but the principles hold.

• Forbes has incorporated programmatic elements into its “person” pages, including automated summaries of the person’s background and key sources of income, and sections of internal links that promote discovery of Forbes lists and other content.
• Zapier’s integration pages and software landing pages pull data from its database of existing integrations and software, and use content patterns to populate the text elements.
• Canva has created thousands of pages from its templates database, targeting queries like “create {type of creative}” or “free {template example}”.
• G2 uses programmatic SEO for its “best {category} software” pages. It uses content patterns to generate reusable structures for FAQs and other text, and its company database to populate the listings and build custom visualisations like the G2 Grid below.

Other notable examples of programmatic SEO done well are NomadList (now Nomads.com), rome2rio, and Booking.com’s list-based articles and landing pages. What they all have in common is that the data is the product. Strip the text out and the pages would still be useful. That’s a good test for your own build.

What are the benefits and limitations of programmatic SEO?

The benefits of programmatic SEO are that it enables:

• scalability in SEO enhancements and page publishing
• better conversion rates in highly targeted searches
• speed in editing and publishing
• brand domination in highly targeted searches
• when executed properly, improved traffic and revenue

The challenges are:

• Quality control, to avoid thin pages, page duplication and cannibalisation
• Investment: time, expertise and software costs (and in 2026, model and API costs if you generate any text)
• Indexation and crawling, which become an issue when there are quality problems or poor internal linking
• Duplication, when keyword modifiers are poorly chosen
• Site-wide risk: since 2024, a large block of low-value pages isn’t just ignored. It can earn a manual action for scaled content abuse, and in my experience a bloated, low-quality section weighs on the rest of the site too

There are also broader concerns: environmental costs, web quality and the spread of misinformation. Generative AI has made all three more pressing, because generating a page now costs compute, and an unchecked model can repeat an error across thousands of URLs in minutes. These concerns can be addressed, but only if the principles of programmatic SEO are executed with care.

How to do programmatic SEO: a step-by-step guide

In this section, I’ll take you through a rough overview of the steps needed to run a programmatic SEO project. It won’t cover everything, but it should give you a feel for the complexity and organisation a campaign needs.

Step 1: Choose your content niche

For a programmatic SEO project to succeed, whether you’re building an entire website or a site section, the niche you choose should have:

• clearly defined goals, a reason to exist and a target audience
• relatively low competition: an under-saturated niche with room to introduce original content to the web
• sufficient demand, in terms of search terms and the number of search variables
• enough data, or a clear way to source original, high-quality data that can be condensed into a database
• search terms that can be broken down into variables

That last point is where programmatic keyword structures come in, specifically head terms and modifiers.

Head terms are broad, ambiguous keywords describing the search intent your pages aim to address. Modifiers are variables related to the head term (or entity): typically different attributes that add context to it. Together, they create programmatic SEO keywords. Some examples:

Company	pSEO keyword (head term in bold)	Example titles
Zapier	{software} + {software} integration	Google Docs + Google Sheets Integration
Purina	can {animal} eat {food}	Can cats eat pork? Can dogs eat mango?

You can choose a single-variable strategy (the Zapier example) or a multi-variable strategy (the Purina example), depending on the complexity of the query and the data you have.

Step 2: Research and organise your keyword universe

Traditional keyword research leans on metrics that are becoming less useful on their own, like search volume, keyword difficulty and competitive density. Newer approaches, like semantic keyword research, focus on concept and knowledge expansion and topical authority, while taking user search behaviour and intent into account. When doing keyword research for programmatic SEO, focus on:

• selecting head terms with enough potential for variants, and expanding your knowledge of the concept
• choosing terms with low competition and lower search volumes
• looking at SERP data to find opportunities to answer the query more clearly than the existing content does

The difference between traditional keyword research and programmatic keyword research is where you look. With programmatic keywords, you’re hunting for templatable structures with multiple variable possibilities and low competition.

Beyond the semantics (entities and attributes), consider the business purpose of each attribute and its variables. For instance, “influencers named Anna” and “influencers with dogs” might both have negligible search volume, but there’s a business rationale for a landing page on the latter: it’s useful to companies in the pet niche doing influencer marketing. Nobody is commissioning a campaign based on the influencer’s first name.

A rough process to follow:

1. Go through keywords for your head term, identify the term’s attributes, and note potential pSEO keywords with a single- or multi-variable strategy.
2. Map all possible entity-attribute combinations in your niche, adding every possible variable for each attribute.
3. Choose the ones most closely related to your goals, business and site purpose.
4. Programmatically combine head terms and variables into your final target queries.
5. Validate the keywords through user research, search volume scoping (global and local) and SERP research.
6. Finalise your keyword list and prioritise topic clusters.

Programmatic keyword research is all about finding head term and variable patterns with potential, and organising them into a coherent keyword universe for your pages to target. (My Traffic Think Tank course has a 40+ minute tutorial on just this step, packed with examples like the one above.)

In 2026, I’d add one more validation step: check whether each combination deserves a page at all. If the data for a combination is too thin to say anything specific, or two combinations would produce near-identical pages, merge them or skip them. This is the single biggest lever against scaled content abuse, and you pull it before a single page exists.

Step 3: Structure and populate your programmatic SEO database

When organising your database, consider these core principles:

• Choose a host and platform that fit how you’ll publish the pages and the CMS you’re building on. Make sure the database supports the data types you need (images, text, numbers and so on).
• Name parameters descriptively and use a consistent syntax. Follow database organisation best practices.
• Plan data entry: how you’ll enter, validate and clean data. Choose processes that allow automation and avoid manual entry errors.
• Build with an SEO-first mindset, so each entry (typically one page) supports best practice for titles, headings, content and images. Automate the checks where you can.
• Plan with a systems mindset: every field you add is a field you’ll have to maintain across thousands of rows.

Once that’s ready, you can start creating content. There are many ways to source it:

• content from subject-matter experts
• public datasets
• scraping or combining information from multiple sources (respecting terms of use and adding value, not just stitching)
• your own first-party data and original research
• generative AI, used to write from your database rather than instead of it

On that last point: the safest pattern I know is to give the model only the fields from your database and ask it to write from those, never from its own “knowledge”. That keeps every generated sentence traceable to a data point you can check. I walk through this approach in how to use generative AI with structured data for programmatic SEO on MLforSEO.

Step 4: Create your page template and content patterns

How much time and effort you put into your page layout will make or break the project. The goal is a template that’s user-centric and search-friendly.

Before you design anything, research competitors (in your niche, or in similar ones). Pinpoint the template elements that successful competitors use, and build a custom must-have list for your site type.

A good template is user-friendly, well structured (from a UX, web development and SEO standpoint, technical and on-page) and data-driven. Consider loading speed, mobile responsiveness, navigation and links, and structured data.

Don’t neglect continuous improvement, which is vital for keeping the project successful. Build with a “kaizen” principle in mind: successful programmatic SEO sites always end up attracting big competitors, or getting absorbed into new SERP features (and, these days, AI answers).

Content patterns are templatable word structures that can be replicated across many pages without compromising quality. They can be as short as a heading or title, or longer: a paragraph, or a structure for answering a question. The technique is often used for entire content types, like listicles. Content patterns are good for users, for content quality and for scalability, which is why so many companies use them. For example:

• Glassdoor populates its FAQ sections from its company ratings database using a content pattern. Users get a familiar experience, and the site gets internal linking opportunities that improve page discovery.
• Amazon populates several product page elements from its listings data, notably the comparison tables, which improves the experience and adds real value.

Content patterns are classic rule-based automation, and they’re still the right tool for most of a programmatic template. Use generative AI for the parts where variation genuinely helps the reader, not as a replacement for patterns that work.

Step 5: Publish your pages using a no-code or custom solution

The right method depends on your site structure, your coding skills and your requirements: whether you’re publishing a multilingual site, how many pages you have, your security needs, whether you take payments, and how you’ve structured your site architecture and content.

• No-code: platforms like Zapier, a WordPress plugin like WP All Import, or your CMS’s native dynamic collections (Wix and Webflow both have them).
• More sophisticated: a headless CMS, a static site generator or a custom application.

Set a publishing frequency and content calendar before you start. Make sure analytics and reporting are in place before launch, because you’ll want to monitor indexation from day one.

New for 2026: launch in batches. Publish a pilot batch first, watch how it gets crawled, indexed and engaged with in Google Search Console, and fix the template before you scale. If the first few dozen pages don’t get indexed, a few thousand more won’t fix it.

Step 6: Help search engines discover your pages

In 2024, I recommended automatic URL submission tools here. I’ve changed my advice. Google’s Indexing API is only meant for pages with JobPosting or BroadcastEvent structured data, and Google states that submissions go through spam detection and that abuse can get access revoked. For everything else, the sustainable route is:

• clean XML sitemaps, split by template or section so you can see indexing rates per page type in Search Console
• strong internal linking from your hub and category pages
• IndexNow for Bing and other participating search engines
• monitoring indexation with the URL Inspection API and a dashboard, so you spot problems per template

If pages aren’t getting indexed, treat it as a quality signal about the template, not a submission problem.

Step 7: Keep enhancing before and after launch

Don’t forget SEO enhancements for your programmatic pages, pre- and post-launch: sitemaps, structured data, image enhancements, and cannibalisation and duplication checks. Fuzzy matching is a quick way to catch near-duplicate titles and pages across thousands of rows.

Quality guardrails for AI-assisted programmatic pages in 2026

If you use generative AI anywhere in a programmatic build, these are the guardrails I’d put in place. Most of them are simple rules, which is the point: rules are cheap, predictable and auditable, and they’re the right way to keep a probabilistic model in check. (I go deeper into that split in rule-based vs AI-powered automation.)

1. A minimum-data rule. Don’t generate a page unless the database row has enough unique data points to say something specific. Below the threshold, merge the combination into a broader page or noindex it.
2. Grounded generation only. The model writes from the fields you give it, and nothing else. No “fill in what you know about {city}”.
3. Automated fact checks against the source. Compare numbers, names and prices in the output with the database row, and reject pages that don’t match.
4. Duplication and cannibalisation checks. Measure similarity between generated pages, and between new pages and existing ones, before publishing.
5. Human review by sample, and in full for high-stakes pages. Review a meaningful sample of every batch, and every page in sensitive areas like health, finance and safety.
6. Metadata gets the same scrutiny. Google explicitly includes titles, meta descriptions, structured data and alt text in its fact-checking guidance, and on a programmatic build these errors multiply fast.
7. Transparency. Say how the pages are produced where it would help a reader trust them, and label AI-generated product data and images on e-commerce sites as Google asks.
8. Prune on a schedule. Pages that never get indexed or visited after a reasonable period get improved, merged or removed (with redirects where they have links).
9. Budget for the model. Track generation and regeneration costs per page. If a page isn’t worth the tokens it took to write, it probably isn’t worth publishing.

Bottom line? Programmatic SEO is helpful, but only if done right

Through my course, I had the pleasure of meeting three people with fascinating programmatic SEO experience, and I’ve followed the journeys of many others. Combined with my own work in the field, I can say this:

Programmatic SEO is not just spam, and it’s not just pumping out content programmatically. It’s a mindset for improving organic visibility that combines what’s best for the user (having niche searches properly addressed) with what’s best for the business (a scalable way to grow traffic and revenue). There’s a reason so many of the most successful sites use programmatic approaches, and why Google itself uses them when building its own SERP features.

I know there’s another side to this debate, and I’m aware this post leans on positive examples. There are plenty of negative examples of “programmatic SEO websites” out there. But under the hood, they usually turn out to be sites that were simply built programmatically, without the principles and best practices that experts in this niche swear by. In 2026, generative AI has made that kind of site cheaper to build than ever, and Google has made it riskier to own than ever. Build the system, not just the pages.

Programmatic SEO is not just pumping out pages. It’s a system that has to be good for the user and good for the business, or it isn’t worth building.

— Lazarina Stoy

People to follow to learn more

• Ian Nuttall, founder of PracticalProgrammatic.com and several SEO tools
• Deepak Ness, founder of UntalkedSEO.com

Frequently asked questions

Is programmatic SEO against Google’s guidelines?

No. Google’s spam policies target pages generated at scale “for the primary purpose of manipulating search rankings and not helping users”, whether they’re made by automation, humans or both. A programmatic build that publishes genuinely useful, data-backed pages is not what the scaled content abuse policy describes. A build that generates thousands of near-identical pages with nothing unique on them is.

Can I use AI to write programmatic SEO pages?

You can, as long as the AI is a component of the system rather than the whole system. Have the model write only from your database fields, fact-check the output against the source, check for duplication, review a sample of every batch by hand, and give metadata the same scrutiny. Google’s own guidance warns that generating many pages without adding value may violate its scaled content abuse policy.

What’s the difference between programmatic SEO and programmatic content?

Programmatic SEO is a system (a database, a template and publishing rules) designed to earn visibility for many specific search intents. Programmatic content is the automated creation and distribution of content, today mostly through generative AI. Programmatic SEO can include programmatic content, but programmatic content on its own doesn’t include any SEO principles.

How many pages should I launch with?

Fewer than you think. Launch a pilot batch, watch crawling, indexing and engagement in Search Console, and improve the template before you scale. Only create pages for keyword combinations with enough unique data to deserve them.

Where can I learn programmatic SEO in depth?

My Programmatic SEO course on Traffic Think Tank covers everything in this guide in much more depth, across six sections, including keyword research for programmatic SEO, content patterns, templates, databases, content automation and interviews with three practitioners.

Where to go from here

If you’re ready to go deeper, my course takes you from zero to a working programmatic SEO system. And if you’d rather have someone audit or design the system with your team, that’s the kind of work I do as a fractional growth and AI automation lead.