From seo-skills
Analyzes paid-search competitive landscape for a domain or keyword using SE Ranking PPC data. Produces a competitive ads brief with ad copy patterns, SERP ad/shopping visibility, and bid-keyword shortlist.
How this skill is triggered — by the user, by Claude, or both
Slash command
/seo-skills:seo-adsThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
> Example output: [examples/seo-ads-hostinger-com-20260514/ADS.md](../../examples/seo-ads-hostinger-com-20260514/ADS.md)
Example output: examples/seo-ads-hostinger-com-20260514/ADS.md
Map a domain's paid-search footprint and the competitive landscape around its target keywords. Output: a brief on what the brand is bidding on, who else bids on the same terms, ad-copy patterns the leading competitors use, SERP ad+shopping presence per keyword, and a recommended bid-keyword shortlist.
us).Validate input & preflight
DATA_getCreditBalance — surface remaining credits.Domain mode DATA_getDomainAdsByDomain
volume × CTR-by-paid-position × bid-share).Keyword mode DATA_getDomainAdsByKeyword
Intent enrichment DATA_getKeywordQuestions
SERP ad/shopping presence DATA_getSerpResults
tads (top ads above organic), bads (bottom ads below organic), sads (shopping ads / Google Shopping pack), mads (mobile/map-pack ads).Ad copy pattern analysis
Paid-keyword gap (domain mode) DATA_getDomainKeywords with type: 'adv'
type: 'adv' switch.DATA_getDomainCompetitors with type: 'adv'): pull their paid keywords with type: 'adv'.Recommended bid-keyword shortlist
Synthesise ADS.md
Create a folder seo-ads-{target-slug}-{YYYYMMDD}/ with:
seo-ads-{target-slug}-{YYYYMMDD}/
├── ADS.md (synthesised brief — primary deliverable; inlines paid footprint, bidding landscape, SERP ad/shopping pack, ad copy patterns, paid keyword gap)
├── recommended-keywords.csv (bid-keyword shortlist — load-bearing CSV the PPC team pastes into bid tooling)
└── evidence/
├── 01-paid-footprint.md (domain mode: brand's paid keywords — raw step output)
├── 02-bidding-landscape.md (keyword mode: advertisers on the keyword — raw step output)
├── 03-question-variants.md (DATA_getKeywordQuestions enrichment)
├── 04-serp-ad-shopping-pack.md (SERP feature inventory per keyword)
├── 05-ad-copy-patterns.md (clustered headline/description patterns)
└── 06-paid-keyword-gap.md (domain mode: type='adv' diff vs competitors)
Step files 01, 02, 04, 05, 06 are inlined as sections in ADS.md; the copies in evidence/ preserve the raw step outputs for reproducibility.
ADS.md follows this shape:
# Paid-Search Intelligence: {target}
> Snapshot dated {YYYY-MM-DD} · Country: {country} · Mode: {domain | keyword}
## Footprint summary
- Paid keywords: {n}
- Estimated paid traffic: {n}/mo
- Average CPC: ${n}
- SERP slots covered: {n} of top-4 above organic across {n} target keywords
## Top 10 paid keywords (domain mode)
| Keyword | Volume | CPC | Position | Ad copy excerpt |
|---|---|---|---|---|
| {kw} | {n} | ${n} | {pos} | "{headline} — {snippet}" |
| ...
## Bidding landscape (keyword mode — for "{keyword}")
| Advertiser | Position | Ad copy excerpt | URL |
|---|---|---|---|
| {domain} | {pos} | "{headline} — {snippet}" | {url} |
| ...
## Ad copy patterns (top patterns observed)
1. **Pricing-led:** "{N}% off — start at ${X}/mo" — used by {n} advertisers.
2. **Outcome-led:** "Get {specific outcome} in {time}" — used by {n}.
3. **Trust-led:** "Trusted by {n} {audience}" — used by {n}.
4. ...
## SERP feature inventory
| Keyword | Top ads | Shopping pack | PAA | Image pack |
|---|---|---|---|---|
| {kw} | {advertiser list} | {✓/✗} | {✓/✗} | {✓/✗} |
| ...
## Recommended bid-keyword shortlist
See `recommended-keywords.csv`. Top 10:
| Keyword | Volume | Est. CPC | Why |
|---|---|---|---|
| {kw} | {n} | ${n} | Question-intent variant; competitor X bids on head term but not this. |
| ...
## Constraints / caveats
- CPC and volume estimates are directional. Actual costs depend on Quality Score, time of day, audience, etc.
- {Note any ad-copy that's clearly seasonal / promotional and may not represent steady-state.}
## Recommended next step
Cross-reference these paid keywords with `seo-keyword-cluster` output to find under-served paid clusters. For organic content opportunities corresponding to these paid keywords, run `seo-keyword-niche`.
recommended-keywords.csv columns: keyword,volume,cpc_estimate,position_target,intent,competitor_count,why_recommended
seo-keyword-niche for organic content opportunities derived from paid keyword research.seo-competitor-pages if the bidding landscape reveals "X vs Y" / "alternatives" intent — those keywords convert best as comparison pages, not paid ads.DATA_getDomainAdsByDomain / DATA_getDomainAdsByKeyword, the type: 'adv' enum switch on DATA_getDomainKeywords, DATA_getDomainKeywordsComparison, DATA_getDomainCompetitors, DATA_getDomainPages, and similar tools surfaces the paid view of the same data structures. Combine with the tads/bads/sads/mads SERP-feature filters and the CPC filter on SERP queries to map paid landscape comprehensively.npx claudepluginhub seranking/seo-skills --plugin seo-skillsResearches competitor PPC strategies, keywords, ad copy, landing pages, and budgets using SpyFu. Useful for analyzing PPC spend, keyword gaps, or competing brands.
Analyzes competitor ads across Google, Meta, LinkedIn, TikTok, and Microsoft using ad libraries and auction insights. Evaluates copy, creatives, keywords, spend, and identifies gaps/opportunities.
Competitor ad intelligence analysis across Google, Meta, LinkedIn, TikTok, Microsoft, and Apple Ads. Analyzes competitor ad copy, creative strategy, keyword targeting, estimated spend, and identifies competitive gaps and opportunities. Use when user says competitor ads, ad spy, competitive analysis, competitor PPC, or ad intelligence.