AI Keyword Clustering Tool - Topical Clustering + Bulk SERP

AI Keyword Clustering Tool 🧠🔍

Bulk AI keyword clustering, topical clustering map and live SERP-validated MERGE / SPLIT recommendations in a single run. Submit up to 1,000 keywords per batch; get Google Ads search volume, CPC, 12-month trend, deep semantic clusters with canonical_query + central_entity + buyer intent + recommended content format, a hierarchical CORE / OUTER topical authority map keyed to your business context — and per-cluster top-10 Google SERPs cross-checked for keyword cannibalization and content consolidation opportunities.

A practical alternative to Ahrefs / Semrush / MarketMuse / Frase / Surfer SEO / KeywordInsights when you need the clustering output, not a full SEO suite subscription. Pay per 1,000 keywords. No subscription. No API keys to manage.

This actor is built for:

• 📈 SEO professionals & agencies planning pillar pages and topical authority maps
• ✍️ Content marketers & strategists turning a seed list into a 6-month editorial calendar
• 🛠️ In-house SEO teams & developers integrating bulk keyword clustering into pipelines, dashboards, n8n / Make / Zapier flows
• 🤖 AI agent builders wiring topical maps into LLM workflows via Apify MCP
• 🎯 GEO / AEO specialists generating cluster-level briefs for AI-engine optimization

Co-designed with a senior SEO analyst. Every metric, threshold, validation layer and output field reflects what a professional content-strategy deliverable needs to look like — the kind that holds up in an agency client review or an editorial-planning meeting.

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📌 Table of Contents

• ✨ Features
• 🎯 Use Cases
• ⚡ Quick Start
• 🧾 Input Parameters
• 📤 Output
• 💰 Pricing
• 🆚 How it compares
• ❓ FAQ
• 🔎 SEO Keywords

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✨ Features

• 🧠 AI semantic clustering of up to 1,000 keywords per batch
  • Deep semantic embeddings group keywords by intent and meaning, not just surface tokens. "ascendent kalkulator" + "kalkulator ascendentu" + "jak obliczyć ascendent" land in one cluster, not three.
• 🗺️ CORE / OUTER topical authority map
  • Every cluster is classified relative to your businessContext: CORE = pillar pages (your main offering or a direct derivative); OUTER = supporting / E-E-A-T content that builds topical authority around the core. Output is a hierarchical pillar → supporting structure with URL-safe slugs ready for editorial planning.
• 🔍 Live Google SERP validation — MERGE & SPLIT recommendations
  • For every cluster's canonical query, we fetch the live Google top-10 and check cross-cluster URL overlap. MERGE = two clusters with ≥ 50% URL overlap (Google ranks them as the same intent — consolidate to one page). SPLIT = a cluster whose sampled members have < 30% mean SERP overlap with the canonical query (the cluster mixes distinct intents — separate them).
• 📊 Per-keyword Google Ads metrics
  • Search volume, CPC, competition + competition_index, full 12-month monthly history and month-over-month trend — for every keyword in the expanded set.
• 🧮 Per-cluster intelligence
  • canonical_query (the cluster's root keyword, picked by volume × low-competition), central_entity (the head noun), intent (commercial / informational / transactional), recommended_format (ranking / how-to guide / comparison / informational article — picked from the SERP), members[], members_count, total_volume, avg_cpc, avg_competition, top-10 SERP for the canonical.
• 🌱 Optional seed enrichment
  • Submit fewer than 200 seeds and the pipeline auto-expands each with related queries (Google PAA + Related searches + organic title tokens + product-filter attributes + AI-generated query variants). Submit 200+ and your input IS the corpus — no auto-expansion, just clustering.
• 🌍 Country & language localization
  • 53 countries, 2-letter ISO codes (us / en, de / de, pl / pl, fr / fr, …). Cluster labels and topical-map text honor the language code.
• 🧼 Clean structured JSON output
  • Drop straight into SEO dashboards, BI tools, Looker / Metabase, spreadsheets, agent workflows, or Apify MCP clients.

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🎯 Use Cases

Use Case	What you can do	Why it helps
🧠 Topical clustering for pillar pages	Turn 1,000 keywords into 30–80 semantic clusters	Build hub-and-spoke / pillar-cluster content models from data, not guesses
🗺️ Topical authority map for new sites	CORE / OUTER classification keyed to your business	Plan the full topical authority footprint before writing a word
🔁 Keyword cannibalization audit	MERGE recommendations expose clusters Google sees as the same intent	Consolidate competing pages before they suppress each other's rankings
✂️ Content split audit	SPLIT recommendations expose clusters mixing distinct intents	Spin off misfit members to their own focused pages
📅 Editorial calendar planning	Per-cluster recommended_format + total_volume + intent	Prioritize the 30 highest-value clusters for the next quarter
💰 PPC keyword grouping	Bulk keyword grouping by intent + CPC + competition	Build ad groups that share intent (and Quality Score)
🤖 Topical maps for AI agents	Feed clean JSON into LLM workflows / Apify MCP	Replace expensive multi-tool SaaS stacks with one actor call
🎯 GEO / AEO content briefs	Cluster + canonical SERP + intent → AI-engine-ready brief input	Generate generative-engine-optimized content briefs from one dataset

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⚡ Quick Start

Click "Try for free" with the default input

The prefill is a curated 10-keyword running-gear seed list with a real businessContext. One run gives you 2–4 clusters, a topical authority map and at least one SPLIT or MERGE recommendation — enough to validate the dataset shape and pricing on your own account in ~3 minutes.

Real run — your own keywords

{
  "keywords": [
    "topical clustering",
    "keyword clustering tool",
    "keyword grouping",
    "semantic keyword clustering",
    "topical authority map",
    "pillar page planning",
    "content cluster tool",
    "seo content strategy",
    "keyword cannibalization",
    "MERGE keyword recommendation"
  ],
  "businessContext": "We sell AI-powered SEO software for agencies and in-house content teams — keyword research, content planning, AI brand visibility tracking. Buyer is a senior SEO / content strategist.",
  "country": "us",
  "language": "en",
  "enableSerpValidation": true,
  "enableSplitCheck": true
}

Tips for clean clusters

• businessContext is REQUIRED — it drives CORE / OUTER classification. The richer the context, the sharper the topical map. 1–3 specific sentences beats one generic.
• 200+ keyword inputs skip auto-expansion — submit your own complete keyword universe at scale; submit < 200 if you want the pipeline to add Google PAA / Related / variant queries.
• Group by language per run — mixed-language batches work, but produce stronger clusters when seeds share a language.
• Toggle enableSerpValidation off for cheaper exploratory runs without MERGE / SPLIT recommendations.

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🧾 Input Parameters

Parameter	Type	Required	Default	Description
keywords	array<string>	✅	—	1–1,000 seed keywords. Case-insensitive duplicates removed automatically.
businessContext	string	✅	—	1–3 sentences describing what your business does. Drives CORE / OUTER classification.
country	string	❌	us	2-letter ISO-3166 country code, lowercase. 53 supported (us, gb, de, fr, pl, es, …).
language	string	❌	derived from country	2-letter ISO-639 language code, lowercase. Set explicitly when your keywords are in a different language than the country default.
enableSerpValidation	boolean	❌	true	Run live SERP overlap analysis for MERGE recommendations.
enableSplitCheck	boolean	❌	true	Run SPLIT coherence check for clusters > 10 members.
minClusterSize	integer	❌	2	Smallest reportable cluster (members below this get marked outliers).
maxClusters	integer	❌	auto	Hard cap on cluster count. Default auto-tunes via cluster quality score.

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📤 Output

One dataset item per batch run, with a full ClusterResult payload.

Example output (trimmed)

{
  "batch_id": "a3cdcec9-826e-4fb0-aaef-978196d0736e",
  "status": "done",
  "country": "us",
  "language": "en",
  "business_context": "We sell AI-powered SEO software …",
  "summary": {
    "input_keywords": 10,
    "expanded_keywords": 290,
    "total_clusters": 30,
    "outliers": 0,
    "total_search_volume": 388170,
    "core_topics": 10,
    "outer_topics": 20,
    "split_recommendations": 9,
    "merge_recommendations": 17
  },
  "keywords": [
    {
      "keyword": "topical clustering",
      "google_search_volume": 480,
      "google_cpc_usd": 11.70,
      "google_competition": "LOW",
      "monthly_history": [{"year": 2026, "month": 4, "search_volume": 590}],
      "trend_mom_pct": 22.9,
      "cluster_id": 0
    }
  ],
  "clusters": [
    {
      "id": 0,
      "canonical_query": "topical clustering",
      "central_entity": "topical clustering",
      "cluster_label": "Topical Clustering & Topical Authority Maps",
      "intent": "commercial",
      "recommended_format": "ranking",
      "classification": "CORE",
      "members": ["topical clustering", "topical authority map", "topical authority tool", "..."],
      "members_count": 17,
      "total_volume": 18570,
      "avg_cpc_usd": 14.32,
      "serp_top10": [
        {"rank": 1, "url": "https://example.com/topical-clustering", "title": "...", "domain": "example.com"}
      ]
    }
  ],
  "validation": {
    "splits": [
      {
        "cluster_id": 4,
        "canonical_query": "keyword clustering",
        "mean_serp_overlap_pct": 22.5,
        "subgroups": [["semantic keyword clustering"], ["keyword grouping tool"]],
        "reason": "mean SERP overlap of 5 sampled members vs 'keyword clustering' is 22.5% (< 30%); the cluster likely mixes distinct intents"
      }
    ],
    "merges": [
      {
        "cluster_ids": [1, 13],
        "canonical_queries": ["keyword research", "keyword research tools"],
        "serp_overlap_pct": 60.0,
        "reason": "top-10 SERP overlap of 60.0% between 'keyword research' and 'keyword research tools' (≥ 50%) — Google ranks them as the same intent"
      }
    ]
  },
  "topical_map": {
    "core": [
      {
        "pillar_page": "topical-clustering",
        "central_entity": "topical clustering",
        "attribute_type": "Main",
        "supporting_pages": [3, 7, 12],
        "cluster_id": 0
      }
    ],
    "outer": [
      {
        "page": "keyword-cannibalization",
        "central_entity": "keyword cannibalization",
        "reasoning": "A diagnostic concept supporting the core clustering offering, not a primary pillar.",
        "cluster_id": 12
      }
    ]
  },
  "created_at": "2026-05-14T12:53:14Z",
  "completed_at": "2026-05-14T12:54:30Z"
}

Output fields

Category	Fields
🆔 Batch	batch_id, status, country, language, business_context, created_at, completed_at
📊 Summary	input_keywords, expanded_keywords, total_clusters, outliers, total_search_volume, core_topics, outer_topics, split_recommendations, merge_recommendations
🔑 Per-keyword	keyword, google_search_volume, google_cpc_usd, google_competition, monthly_history[], trend_mom_pct, cluster_id
🧠 Per-cluster	id, canonical_query, central_entity, cluster_label, intent, recommended_format, classification (CORE/OUTER), members[], members_count, total_volume, avg_cpc_usd, avg_competition, serp_top10[]
✂️ MERGE / SPLIT	validation.splits[], validation.merges[] — each with cluster_id(s), canonical_query, SERP-overlap %, machine-readable reason
🗺️ Topical map	topical_map.core[] (pillar pages), topical_map.outer[] (supporting pages) — both with URL-safe slugs

You can download the dataset in JSON, CSV, Excel, HTML or RSS — Apify Store handles the format conversion.

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💰 Pricing

Pay-per-event — one event per batch (up to 1,000 keywords), charged only on successful runs. No subscription. No platform usage charges. No outbound API keys to manage.

Apify subscription	Effective price / 1,000 keywords
Business	$0.99
Scale	$1.25
Starter	$1.75
Free	$3.95 (one batch fits inside the $5 monthly Apify free credit)

Sending fewer than 1,000 keywords counts as one batch (the pipeline cost is dominated by SERP fetches and Gemini calls, not the input array length).

Learn more: Apify pay-per-event docs

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🆚 How it compares

	AI Keyword Clustering Tool	Ahrefs / Semrush UI scrapers	Single-engine keyword volume scrapers
Bulk semantic clustering	✅ 1,000 KW / batch	❌ raw keyword data only	❌
CORE / OUTER topical map	✅ keyed to your business context	❌	❌
Live SERP MERGE / SPLIT recs	✅ Google top-10 overlap analysis	❌	❌
Google Ads volume + CPC + 12-mo trend	✅ for every expanded keyword	✅	✅
Buyer intent classification per cluster	✅ commercial / informational / transactional	❌	❌
Recommended content format per cluster	✅ ranking / how-to / comparison / article	❌	❌
Subscription required	❌ pay-per-batch	❌ but typically $3–10 / scan	❌
Best for	content planning + topical authority + pillar pages	suite-replacement scraping	bulk volume only

Sibling actors from the same doesaiknow developer:

• Keyword Metrics Pro — raw bulk Google + Bing volume only, no clustering. $1.35 / 1,000 KW on Business tier, multi-engine.
• AI Brand Visibility — track how often your brand is mentioned by ChatGPT, Perplexity, Copilot, and Google AI Overviews.

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❓ FAQ

Q1: Why "topical clustering" instead of plain keyword clustering?

Topical clustering does what flat keyword clustering refuses to: it groups keywords by search intent + central entity + business relevance, not by string similarity. "running shoes for flat feet" and "best supportive trainers" cluster together — even with zero overlapping tokens — because Google ranks them on the same intent. That is the difference between a list of synonyms and a content map you can act on.

Q2: How is this different from keyword grouping in Ahrefs / Semrush?

Ahrefs and Semrush group keywords by token overlap on a single canonical query. We cluster on deep semantic embeddings, then validate against live Google SERPs (top-10 URL overlap). The MERGE recommendation, in particular, has no equivalent in the major SEO suites — it directly tells you which clusters Google itself sees as the same intent (≥ 50% URL overlap) and should be a single page.

Q3: What does the topical authority map actually contain?

Two arrays. core[] lists clusters whose central entity is your main offering or a direct derivative — each becomes a pillar page with a URL slug, attribute type (Main / Derived) and a list of supporting cluster IDs. outer[] lists clusters that are tangential but build E-E-A-T / topical authority around the core — each becomes a supporting article with a reasoning sentence explaining why it's adjacent. Together they're a complete pillar-cluster content plan.

Q4: How much does it cost to cluster 1,000 keywords?

One batch event — $0.99 on Business tier, $1.25 on Scale, $1.75 on Starter, $3.95 on Free (which fits inside Apify's $5 monthly free credit). No platform usage charges. No outbound API costs. No per-keyword surcharge. Sending 100 or 1,000 keywords both count as one batch.

Q5: Can I run this from n8n / Make / Zapier / a Python script / an AI agent?

Yes — use the Apify API client in your stack. Code samples auto-generated by Apify Store are below in the API section. The actor is also discoverable via the Apify MCP server, so Claude Desktop, Cursor, ChatGPT custom GPTs, n8n / Zapier MCP nodes and in-house AI agents can call it as a single tool.

Q6: What languages and countries are supported?

53 countries via the country parameter (us, gb, de, fr, es, it, pl, nl, se, br, pt, jp, in, mx, …). Language defaults from country but is overridable via language (e.g. country=pl, language=en for English keywords in the Polish ad-volume locale). Cluster labels, central entities and topical-map reasoning honor the language code — submit Polish keywords with language=pl and the labels come back in Polish.

Q7: What is the SPLIT recommendation actually checking?

For every cluster with > 10 members, we randomly sample 5 of them, fetch each one's live Google top-10, and compare the URL set to the cluster's canonical-query SERP. Members whose individual top-10 has < 30% URL overlap with the canonical are flagged as misfits — i.e. Google ranks them differently from the cluster's center, so they're mixing distinct intents. The subgroups[] field lists the misfits so you can pull them into their own focused cluster / page.

Q8: Do I need to deduplicate my keywords before submitting?

No. The actor lowercases + trims every input keyword and removes duplicates before billing — what shows up in the dataset is the unique set. Submit 50 raw variations of "best running shoes" and you'll see one keyword on the output side.

Q9: What happens if my run hits a timeout?

The clustering pipeline has a 12-minute backend hard limit; the actor polls for ~13 minutes. A 1,000-keyword run typically completes in 5–8 minutes. If a run does time out, the dataset is empty and you are not charged (PPE only fires on success).

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🔎 SEO Keywords

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