Semantic core and clustering
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
- Core built from day one
- Gaps spotted before launch
- Quick cycles for MVP
- Local queries targeted
- Clusters expanded
- Overlaps removed
- Markets unified
- Hierarchies mapped
- Monitoring ongoing
What goes into keyword research?
Semantic core pricing
We price by depth and scope of research — not by keyword count alone.
More possibilities for your project
- 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.