programmatic-seo-planner

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

1. Your product — URL + one-sentence description
2. Category — What category/market do you play in?
3. Competitors — 3-5 competitor URLs (we'll analyze their pSEO plays)
4. ICP — Who's searching for your product? (roles, industries, company stages)
5. Existing content — Do you already have a blog/resource section? (URL if yes)
6. CMS/tech stack — What powers your site? (Webflow, WordPress, Next.js, etc.) — informs template feasibility
7. 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_content.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-post-finder to find how ICP talks about the problem:

python3 skills/reddit-post-finder/scripts/search_reddit.py \
  --subreddit "<relevant_subs>" \
  --keywords "<category>,<problem keyword>" \
  --days 365 --sort top --time year

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:

1. Data source — Where does the variable data come from?
2. Competitor names → manual list (finite, high-value)
3. Integration/tool names → API marketplace, app directory
4. Industry names → standard industry lists
5. Terms/glossary → keyword research output
6. Templates → product feature matrix

1. Content differentiation — Can each page offer genuine value, or will they be thin?
2. vs/ pages need real feature comparisons, not just "we're better"
3. Integration pages need actual setup guides or use cases
4. Vertical pages need industry-specific pain points and examples

1. Technical feasibility — Can your CMS generate these at scale?
2. Static site generators (Next.js, Astro) → excellent for pSEO
3. Webflow CMS → good, max 10K items per collection
4. WordPress → good with custom post types
5. Manual creation → not pSEO, just a lot