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Semantic core and clustering
Large-scale semantic clustering adapted to dense, high-competition SERP environments nationwide.
US keyword universe
Deep keyword modeling
Clean cluster logic
Challenges we solve
SEO begins with
structure.
We research the terms your audience actually uses and cluster them into meaningful groups. This creates a semantic core that informs site navigation, content planning, and SEO strategy — clear, measurable, and built to scale.
Traffic comes, but doesn’t
convert.
Intent analyzed. Keywords mapped.
Content ideas run dry, and growth stalls.
Structured clusters built. Topics expanded.
Pages compete with each
other.
Overlaps spotted. Cannibalization fixed.
Growth is flat. Opportunities go unseen.
New segments revealed. Opportunities unlocked.
Who we work with
Startups
Launching a new product? Shape a semantic core from the first day.
- Core built from day one
- Gaps spotted before launch
- Quick cycles for MVP
Launch with focus
Small businesses
Traffic stalls? We surface topics your audience needs and attracts views.
- Local queries targeted
- Clusters expanded
- Overlaps removed
Scale with clarity
Corporations
Large platforms demand precision. Unify clusters & maintain intent.
- Markets unified
- Hierarchies mapped
- Monitoring ongoing
Grow with consistency
What goes into keyword research?
Mapped from real intent
We capture how users actually search as well as what tools suggest.
Search behavior
User intent
Clustered with logic
Queries grouped into themes that guide both content and structure.
Topic clusters
Site hierarchy
Filtered for value
No vanity terms — only keywords that bring traffic and conversions.
High intent
ROI focus
Updated as markets shift
Your semantic core stays alive, adapting to trends and seasonality.
Dynamic data
Continuous growth
A keyword list becomes useful when it turns into a page map
Collecting phrases is mechanical. The work that matters is grouping them by what a search engine already treats as one topic, then deciding which group becomes a page. A list of eight thousand phrases with no map behind it never reaches anyone who writes.
Collect from several sources, not one tool
Search console data for what the site already attracts, suggestion lists, competitor pages, the vocabulary sales hears on calls, and the words used in the client's own documents. Single-source lists inherit that source's blind spots, and industry terminology is usually the part missing.
- Existing query data pulled first
- Client vocabulary collected from staff
- Competitor coverage mapped
Group by search results, not by wording
Two phrases belong together when their results overlap. Phrases that look similar often return entirely different pages, and phrases that look unrelated sometimes return the same ones. Grouping by string similarity produces clusters that cannot be turned into pages.
- Clusters formed from result overlap
- Similar wording split where results differ
- Cluster size kept workable
Assign each cluster to exactly one page
Here the map appears. An existing page, a page to be rewritten, or a new one where nothing covers the group. Two pages assigned to the same cluster will compete, and the cheapest moment to prevent that is now.
- Clusters mapped to existing pages first
- New pages justified against current coverage
- Overlaps resolved before writing starts
Order the work by what it can return
Volume alone ranks badly. Four things decide order: current position, whether the page exists, how commercial the intent is, and how hard the competing results are. A cluster sitting on the second page of results with a page already written is usually worth more than a larger one starting from nothing.
- Priority scored on several factors
- Near-miss positions taken first
- Effort estimated per cluster
Semantic core pricing
We price by depth and scope of research — not by keyword count alone.
Semantic core (keyword grouping)
~ $1,000
Clustering and site mapping
~ $2,500
Semantic core with ongoing updates
~ $5,000
Get your custom estimate
More possibilities for your project
We work with a wide range of tasks and formats.
Explore additional solutions that may be a good fit for your project.
Formats
Industries
- Online Stores
- Real Estate
- Healthcare and Dentistry
- Restaurants and Cafes
- Beauty Salons
- Education
- Construction
- Legal Services
- Tourism and Hotels
- Logistics
- Interior Design
- Apartment Renovation
- Auto Services
- Marketplaces
- Consulting
- Photographers
Let's chat
FAQ
Didn’t find what you were looking for? Drop us a line at info@toimi.pro.
How do you handle semantic collection in extremely competitive US SERPs?
We build deep multi-level clustering, analyze enterprise competitors, and model search intent with high granularity.
Do you work differently with local US queries?
Yes — density is high, so we create micro-clusters for neighborhoods and service zones.
How do enterprise-level competitors affect clustering?
We split intent types more aggressively to avoid cannibalization and build scalable structures.
How do you treat overlapping verticals in dense markets?
By separating informational, transactional, and branded universes.
What does your semantic workflow include?
Keyword extraction, SERP analysis, content gap mapping, clustering algorithms, manual refinement.
How do you handle noisy data?
Through bulk filtration, SERP sampling, and intent correction.
Do you adapt clusters for large category trees?
Yes — especially relevant for US e-commerce and marketplaces.
How do you handle long-tail at national scale?
We build hierarchical long-tail sets with clear output mapping.
Do you prioritize growth areas?
Yes — we surface clusters where competition is softer.
Do you provide a cluster-to-page map?
Always — with structural recommendations.
