Seo competitor gap analysis

Example output: examples/seo-competitor-gap-analysis-wix-com-20260514/REPORT.md

Competitor Gap Analysis

Identify the specific keywords your competitors rank for in the top 20 that your domain does not, ranked by commercial value and realistic capture difficulty.

Prerequisites

• DataForSEO MCP server connected.
• User provides: (a) target domain, (b) 3 to 5 competitor domains (or ask the skill to auto-discover them), (c) market country (default: us), and optionally filters (min volume, max KD, intent).

Process

1. Validate or discover competitors mcp__dataforseo__dataforseo_labs_google_competitors_domain

   • If the user did not provide competitors, pull the top 5 organic competitors for the target in the target market.
   • Surface the list to the user and ask them to confirm or override before proceeding.
   • Note: large competitor lists can exceed the MCP inline limit. Cap with limit and filters; if the result is written to a file, read that path, parse the {data: [...]} JSON, sort by common_keywords desc, and take the top 5.

2. Pull competitor keyword sets mcp__dataforseo__dataforseo_labs_google_ranked_keywords

   • For each competitor, pull keywords where they rank in the top 20 of the target country.
   • Save per-competitor lists.

3. Pull target keyword set mcp__dataforseo__dataforseo_labs_google_ranked_keywords

   • For the target domain, pull all ranking keywords in the target country (any position).
   • This is the exclusion set.

4. Compute the gap mcp__dataforseo__dataforseo_labs_google_domain_intersection (cross-check)

   • Keywords ranked by at least one competitor in the top 20 but not ranked by the target domain at all.
   • Use the domain-intersection endpoint as a cross-check.

5. Filter and segment

   • Apply user-specified filters on volume, KD, and intent.
   • Segment by intent: informational, commercial, transactional, navigational.
   • Segment by competition: how many of the N competitors rank for each gap keyword.

6. Score and prioritise

   • Score each gap keyword: traffic potential (volume × CTR model) + intent weighting + inverse KD.
   • Surface the top 50 opportunities with reasoning per keyword.

7. Map to content actions

   • For each top opportunity, recommend: new article, expand existing page, refresh existing page, programmatic template.
   • Flag quick wins: competitors rank with thin content (detected by URL pattern and content-length heuristics).

Output format

Create a folder seo-competitor-gap-analysis-{target-slug}-{YYYYMMDD}/ with:

seo-competitor-gap-analysis-{target-slug}-{YYYYMMDD}/
├── REPORT.md                                (synthesised report — primary deliverable)
├── gaps.csv                                 (full gap list — load-bearing CSV the writers/planners paste into briefs)
└── evidence/
    ├── 01-competitors.md                    (competitor list / discovery — raw step output)
    ├── 02-competitor-keywords-{domain}.md   (one per competitor — raw step output)
    ├── 03-target-keywords.md                (target's existing ranking set — raw step output)
    └── 04-gap-raw.md                        (human-readable full gap list before filtering — raw step output)

Top-level: REPORT.md + gaps.csv. The numbered step files preserve the raw API outputs in evidence/ for reproducibility.

REPORT.md follows this shape:

# Competitor Gap: {target}
Market: {country}
Competitors analysed: {list}

## Summary
- Competitor keywords in top 20: {n}
- Target keywords overall: {n}
- Gap keywords (opportunities): {n}
- Gap traffic potential: ~{n}/mo

## Top 50 opportunities

### Informational intent
| # | Keyword | Volume | KD | Competitors ranking | Action | Score |
|---|---|---|---|---|---|---|
| 1 | {kw} | {n} | {n} | {3 of 5} | New article | {score} |
| 2 | ... | ... | ... | ... | ... | ... |

### Commercial intent
| # | Keyword | Volume | KD | Competitors ranking | Action | Score |
|---|---|---|---|---|---|---|
...

### Transactional intent
...

## Quick wins (top 10)
Keywords where competitors rank in positions 5 to 20 with thin content, low domain rank, or old dates.

| # | Keyword | Weakest competitor position | Suggested angle |
|---|---|---|---|
| 1 | {kw} | example.com at #14 (2022 article, 800 words) | Fresh, comprehensive guide |

## Recommended next steps
1. Run `content-brief` on the top 3 opportunities to generate writer-ready briefs.
2. Run `keyword-cluster-planner` on the full gap list to build a sequencing plan.
3. Track the gap keywords once content ships — for your own verified site use GSC (`mcp__gscServer__get_search_analytics`); for any-domain tracking, save dated `serp_organic_live_advanced` snapshots to local storage (the `seo-drift` pattern).

## Files
- gaps.csv: full gap list for spreadsheet analysis
- evidence/04-gap-raw.md: human-readable full gap list before filtering

gaps.csv columns: keyword,volume,kd,cpc,intent,competitors_ranking,top_competitor_position,target_position,action,score

Tips

• DataForSEO allows up to 2,000 calls/min, 30 concurrent. Skills pace sequentially. For large sites, dataforseo_labs_google_ranked_keywords may paginate heavily; set a ceiling (e.g., top 1,000 keywords per domain via limit) unless the user explicitly asks for the full set.
• DataForSEO bills per call; this run issues ~N calls (one ranked-keywords pull per seed plus the intersection cross-checks). Use the documented limit/ceiling params to cap.
• The competitors_ranking count is the best signal of realism. Keywords ranked by 4 of 5 competitors are validated opportunities; keywords ranked by only 1 may be noise.
• Do not recommend capturing branded competitor keywords unless the user explicitly asks. Pivoting to compete on "competitor brand review" is a viable strategy but only if the user opts in.
• When many gap keywords cluster around a theme, recommend a hub page plus cluster rather than 50 individual articles.
• Chain this skill with content-brief and keyword-cluster-planner naturally. Mention them in the Recommended next steps section of the output.