Programmatic SEO Page Planner
Programmatic SEO is how startups generate hundreds of high-intent pages from templates — "{Your Product} vs {Competitor}", "Best {Category} for {Industry}", "{Integration} + {Your Product}". This skill figures out which patterns are worth building, designs the templates, and prioritizes the buildout.
Core principle: pSEO isn't about spinning content. It's about finding a data axis (something that varies per page) where each variation has real search demand and your product has a genuine answer. This skill validates both before you invest in building.
When to Use
- "How do we scale SEO pages without writing each one manually?"
- "Should we build vs/ comparison pages?"
- "What programmatic SEO patterns work for SaaS?"
- "How can we rank for hundreds of long-tail keywords?"
- "Plan our pSEO strategy"
Tool Enhancement (Optional)
This skill works with existing capabilities but produces significantly better results when paired with a keyword data API for bulk volume lookups across hundreds of long-tail variations.
Agent Prompt to User
"I can plan your programmatic SEO strategy using our existing tools. However, for the best results — especially accurate search volume data across hundreds of keyword variations — I'd recommend connecting a keyword data API."
Recommended: DataForSEO (pay-per-use, ~$0.01/keyword, no monthly minimum)
- Sign up at dataforseo.com → get API login + password
- Set
DATAFORSEO_LOGIN and DATAFORSEO_PASSWORD env vars
Alternatives that also work:
- Keywords Everywhere API ($1 per 10 credits = 100K keywords, very cheap) → set
KEYWORDS_EVERYWHERE_API_KEY
- SEMrush API (if you have a subscription) → set
SEMRUSH_API_KEY
- Ahrefs API (if you have a subscription) → set
AHREFS_API_TOKEN
"Want to use one of these, or should I proceed with baseline mode? Baseline still works — I'll use our Apify-based SEO tools for top-level data, though volume estimates for individual long-tail patterns will be less precise."
Mode Selection
- Enhanced mode — Bulk keyword volume lookups via DataForSEO / Keywords Everywhere / SEMrush / Ahrefs. Gets exact monthly search volume, keyword difficulty, and CPC for each pattern variation. Enables confident prioritization.
- Baseline mode — Uses
seo-domain-analyzer (Apify) for domain-level metrics and web_search for pattern validation. Volume estimates are directional, not exact. Still produces a solid blueprint — just less granular on per-variation demand.
Phase 0: Intake
- Your product — URL + one-sentence description
- Category — What category/market do you play in?
- Competitors — 3-5 competitor URLs (we'll analyze their pSEO plays)
- ICP — Who's searching for your product? (roles, industries, company stages)
- Existing content — Do you already have a blog/resource section? (URL if yes)
- CMS/tech stack — What powers your site? (Webflow, WordPress, Next.js, etc.) — informs template feasibility
- Tool preference — Enhanced mode with keyword API, or baseline? (see Tool Enhancement above)
Phase 1: Pattern Discovery
1A: Competitor pSEO Analysis
Run site-content-catalog for each competitor:
python3 skills/site-content-catalog/scripts/catalog_site.py \
--url "<competitor_url>" \
--output json
Analyze URL structures for programmatic patterns:
/vs/, /compare/, /alternatives/ — Comparison pages/integrations/, /connect/, /apps/ — Integration pages/for-{industry}/, /solutions/, /use-cases/ — Vertical/use-case pages/templates/, /examples/, /glossary/ — Resource pages/tools/, /calculators/, /generators/ — Tool pages
For each pattern found, note:
- URL pattern (regex)
- Estimated page count
- What varies per page (the "data axis")
- Sample page titles
1B: Market Pattern Mapping
Based on your product category, evaluate these standard pSEO pattern types:
| Pattern Type | URL Structure | Data Axis | Best For |
|---|
| Versus/Comparison | /vs/{competitor} | Competitor names | High-intent, bottom-funnel |
| Alternatives | /alternatives/{competitor} | Competitor names | Displacement queries |
| Integrations | /integrations/{tool} | Tool/app names | Mid-funnel, ecosystem |
| Industry verticals | /for/{industry} | Industry names | Vertical targeting |
| Use cases | /use-cases/{use-case} | Job-to-be-done | Mid-funnel, discovery |
| Glossary/Definitions | /glossary/{term} | Industry terms | Top-funnel, authority |
| Templates/Examples | /templates/{type} | Template types | Mid-funnel, utility |
| Tools/Calculators | /tools/{tool-name} | Tool functions | Top-funnel, link bait |
| Location pages | /{service}-in-{city} | City/region names | Local-intent (if relevant) |
1C: Customer Language Mining
Run reddit-scraper to find how ICP talks about the problem:
python3 skills/reddit-scraper/scripts/scrape_reddit.py \
--query "<category> OR <problem keyword>" \
--subreddits "<relevant_subs>" \
--sort relevance --time year --limit 50
Extract:
- Questions people ask → potential glossary/guide patterns
- "How do I [X] with [tool]?" → integration/use-case patterns
- "Is there a [X] for [industry]?" → vertical page patterns
- Comparison discussions → vs/ page patterns
1D: Keyword Volume Validation
Enhanced mode (DataForSEO / Keywords Everywhere / SEMrush / Ahrefs):
For each candidate pattern, generate 20-50 keyword variations and pull exact volumes:
- "your-product vs {competitor1}", "your-product vs {competitor2}", etc.
- "best {category} for {industry1}", "best {category} for {industry2}", etc.
- "{your-product} {integration1} integration", etc.
Aggregate per pattern type:
- Total addressable monthly searches across all variations
- Average volume per variation
- Volume distribution (are a few variations high-volume or is it evenly spread?)
- Average keyword difficulty
Baseline mode:
Use seo-domain-analyzer for competitor domain metrics, web_search to spot-check if key variations have SERP results (indicating real demand), and manual estimation based on:
- Competitor page count per pattern (more pages = likely more demand)
- Google autocomplete suggestions for pattern variations
- Reddit/community question frequency
Phase 2: Pattern Evaluation
Score each candidate pattern on:
| Factor | Weight | How to Assess |
|---|
| Search demand | 30% | Total addressable volume across all variations |
| Intent quality | 25% | How close to purchase decision? (vs/ = high, glossary = low) |
| Template feasibility | 20% | Can you create a useful, differentiated page from a template? |
| Data availability | 15% | Can you programmatically source the data that varies? |
| Competitive gap | 10% | Are competitors NOT doing this pattern, or doing it poorly? |
Score each pattern 0-100. Rank by score.
Feasibility Check Per Pattern
For each pattern scoring 50+, validate:
-
Data source — Where does the variable data come from?
- Competitor names → manual list (finite, high-value)
- Integration/tool names → API marketplace, app directory
- Industry names → standard industry lists
- Terms/glossary → keyword research output
- Templates → product feature matrix
-
Content differentiation — Can each page offer genuine value, or will they be thin?
- vs/ pages need real feature comparisons, not just "we're better"
- Integration pages need actual setup guides or use cases
- Vertical pages need industry-specific pain points and examples
-
Technical feasibility — Can your CMS generate these at scale?
- Static site generators (Next.js, Astro) → excellent for pSEO
- Webflow CMS → good, max 10K items per collection
- WordPress → good with custom post types
- Manual creation → not pSEO, just a lot of pages
Phase 3: Template Design
For each pattern being built, design:
Template Blueprint
## Pattern: [vs/{competitor}]
### URL Structure
/vs/{competitor-slug}
### Title Template
{Your Product} vs {Competitor} — [Year] Comparison | {Your Brand}
### Meta Description Template
Compare {Your Product} and {Competitor} side-by-side. See pricing, features,
pros/cons, and which is better for {ICP description}.
### H1
{Your Product} vs {Competitor}: Honest Comparison
### Page Sections (content framework)
1. **TL;DR** — 3-sentence summary of key differences (above fold)
2. **Quick comparison table** — Feature matrix with checkmarks
3. **Detailed comparison** — 4-6 key dimensions, 2-3 paragraphs each
4. **Pricing comparison** — Plan-by-plan breakdown
5. **Who should choose {Your Product}** — ICP fit description
6. **Who should choose {Competitor}** — Fair assessment
7. **What real users say** — Review quotes from both sides
8. **CTA** — Trial/demo prompt
### Data Required Per Page
- competitor_name: string
- competitor_slug: string
- competitor_features: array (from their website/docs)
- competitor_pricing: object (from pricing page)
- competitor_reviews: array (from G2/Capterra)
- your_differentiators: array (per competitor)
### Content Guidelines
- Minimum 1,500 words per page
- Must include at least one unique insight (not just feature lists)
- Use actual screenshots or diagrams where possible
- Update quarterly (pricing/features change)
Repeat for each pattern type.
Phase 4: Prioritization & Roadmap
Build the implementation plan:
Priority Matrix
| Pattern | Score | Est. Pages | Volume/Page | Total Volume | Build Effort | Priority |
|---|
| vs/ comparisons | 85 | 15 | 300 | 4,500 | Medium | P0 — Build first |
| integrations/ | 72 | 40 | 80 | 3,200 | High | P1 — Build second |
| for-{industry}/ | 68 | 12 | 200 | 2,400 | Medium | P1 — Build second |
| alternatives-to/ | 65 | 8 | 250 | 2,000 | Low | P0 — Quick win |
| glossary/ | 45 | 100 | 40 | 4,000 | Low | P2 — Authority play |
Recommended Buildout Sequence
Month 1: Quick wins
- Build [pattern A] — [X] pages, [rationale]
- Build [pattern B] — [X] pages, [rationale]
Month 2: Scale
- Build [pattern C] — [X] pages, [rationale]
- Measure Month 1 patterns, iterate templates
Month 3: Expand
- Build [pattern D] — [X] pages, [rationale]
- Update Month 1 pages with performance data
Per-Pattern Data Source Plan
For each pattern, specify exactly where the variable data comes from:
- Manual curation (competitors list — finite, high quality)
- API source (integration marketplace)
- Scraping (review sites, competitor pages)
- Internal data (product features, pricing)
Phase 5: Output
# Programmatic SEO Blueprint — [Product Name] — [DATE]
## Executive Summary
- [N] patterns evaluated, [M] recommended for buildout
- Total addressable search volume: [X]/month
- Estimated pages to build: [Y]
- Recommended buildout timeline: [Z] months
---
## Pattern Analysis (ranked by priority)
### P0: [Pattern Name]
- URL structure: [pattern]
- Pages to build: [N]
- Total monthly volume: [X]
- Template blueprint: [see below]
- Data source: [where variable data comes from]
- Build effort: [Low/Medium/High]
- Expected time to rank: [2-4 months / 4-8 months / etc.]
[Full template blueprint per Phase 3]
### P1: [Pattern Name]
...
---
## Technical Requirements
- CMS: [capabilities needed]
- Data pipeline: [how to source variable data]
- Update cadence: [how often to refresh]
---
## Quick-Start Guide
1. Start with [pattern] — lowest effort, highest intent
2. Create [N] pages using the template above
3. Monitor for [X] weeks before expanding
4. ...
Save to clients/<client-name>/seo/pseo-blueprint-[YYYY-MM-DD].md.
Cost
| Component | Cost |
|---|
| Site catalog per competitor (Apify) | ~$0.05-0.10 |
| Reddit scraper | ~$0.05-0.10 |
| SEO domain analyzer | ~$0.10-0.20 |
| DataForSEO keyword lookups (enhanced) | ~$0.50-2.00 (depending on variation count) |
| Keywords Everywhere (enhanced alt) | ~$0.01-0.05 |
| Analysis | Free (LLM reasoning) |
| Total (baseline) | ~$0.20-0.50 |
| Total (enhanced) | ~$0.70-2.50 |
Tools Required
- Apify API token —
APIFY_API_TOKEN env var
- Upstream skills:
site-content-catalog, seo-domain-analyzer, reddit-scraper
- Optional (enhanced): DataForSEO (
DATAFORSEO_LOGIN + DATAFORSEO_PASSWORD), Keywords Everywhere (KEYWORDS_EVERYWHERE_API_KEY), SEMrush (SEMRUSH_API_KEY), or Ahrefs (AHREFS_API_TOKEN)
Trigger Phrases
- "Plan our programmatic SEO strategy"
- "What pSEO pages should we build?"
- "Design vs/ comparison pages for our product"
- "How do we scale to hundreds of SEO pages?"
- "Build a pSEO blueprint for [client]"
- "What programmatic patterns should we use?"
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