/seo-ads

name: seo-ads
description: Paid-search competitive landscape for a domain or keyword. Pulls SE Ranking's PPC data — domain ad keyword footprint, ad copy patterns, who else bids on the same keywords, SERP shopping/ad-pack visibility — and produces a competitive ads brief plus a recommended bid-keyword shortlist. Use when the user asks "paid search analysis", "competitor ads", "PPC competitive", "ad copy intelligence", "shopping pack", "who bids on this keyword", or "paid keyword footprint".

> Example output: [examples/seo-ads-hostinger-com-20260514/ADS.md](../../examples/seo-ads-hostinger-com-20260514/ADS.md)

Paid-Search Intelligence (Ads)

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.

Prerequisites

• SE Ranking MCP server connected.
• User provides: (a) a target domain OR a target keyword (skill detects which), (b) target country (default `us`).

Process

1. **Validate input & preflight**

• Determine: domain mode (analyse a brand's paid footprint) or keyword mode (analyse the bidding landscape for one keyword).
• `DATA_getCreditBalance` — surface remaining credits.

2. **Domain mode** `DATA_getDomainAdsByDomain`

• Pull paid keywords the target domain bids on.
• For each: keyword, search volume, CPC, position, ad copy (title + description), URL.
• Sort by traffic-weighted score (`volume × CTR-by-paid-position × bid-share`).

3. **Keyword mode** `DATA_getDomainAdsByKeyword`

• Pull all domains bidding on the target keyword.
• For each: domain, ad position, ad copy, URL.
• Surface the top 10 advertisers + their copy patterns.

4. **Intent enrichment** `DATA_getKeywordQuestions`

• For the keyword(s) in scope, pull related questions.
• Identifies question-phrased intent variants worth bidding on (often cheaper, higher conversion).

5. **SERP ad/shopping presence** `DATA_getSerpResults`

• For top 5 keywords (domain mode) or the target keyword (keyword mode):
• Use SERP-feature filters to detect ad-pack composition: `tads` (top ads above organic), `bads` (bottom ads below organic), `sads` (shopping ads / Google Shopping pack), `mads` (mobile/map-pack ads).
• Top SERP ad slots (positions 1-4 above organic, 1-3 below).
• Shopping pack presence (carousel of product cards).
• Image pack, local pack — these displace ad inventory.
• Capture which advertisers occupy those slots.

6. **Ad copy pattern analysis**

• Cluster ad headlines + descriptions by recurring patterns.
• Identify: USP language used by leaders, pricing/discount mentions, audience segmentation, CTA verbs.
• Highlight outliers (advertisers doing something different).

7. **Paid-keyword gap (domain mode)** `DATA_getDomainKeywords` with `type: 'adv'`

• Pull the user's domain's paid keywords using the `type: 'adv'` switch.
• For each top competitor (from step 2 or `DATA_getDomainCompetitors` with `type: 'adv'`): pull their paid keywords with `type: 'adv'`.
• Diff: paid keywords competitors bid on that the user's domain doesn't.
• This becomes the highest-leverage portion of the bid-keyword shortlist (step 8).
• Skip in keyword mode (no domain to gap against).

8. **Recommended bid-keyword shortlist**

• For domain mode: paid-keyword gap from step 7 + adjacent question-intent variants.
• For keyword mode: question-intent and long-tail variants that are likely cheaper than the head term.
• Each row: keyword, est. CPC, est. volume, who else bids, why-recommended.

9. **Synthesise** `ADS.md`

Output format

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 b