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Semantic core and clustering

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Large-scale semantic clustering adapted to New York’s dense, high-competition SERP environment.
NYC competitive SERP
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
Why do we publish content, but traffic doesn’t grow?
Because keywords aren’t mapped to intent.
Some terms bring clicks — others bring exits.
Articles overlap — pages fight each other.
Clusters missing — search engines get confused.
If the core isn’t structured, growth is guesswork.

What goes into keyword research?

Mapped from real intent
We capture how users actually search, not just 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

Publishing content without results?

Let’s chat

Semantic core pricing

We price by depth and scope of research — not by keyword count alone.

Starter semantic core (basic keyword grouping)
~ $1,000
Growth package (advanced clustering and site mapping)
~ $2,500
Enterprise package (large-scale core with ongoing updates)
~ $5,000
Get your custom estimate

What our clients say

Marcus Brown
Marketing Director
star 5

We've worked with Toimi on two projects now, and both times the result was spot on. Timelines were realistic, communication was clear, and the team handled all details without us having to chase.

Susan Miller
HR Director
star 5

They didn't just ship features — they explained trade-offs, suggested improvements, and really thought about long-term use. Felt like an extension of our team.

David Chen
Product Manager
star 5

Fast, professional, and no overcomplication. Our landing page went live on schedule and performed better than expected.

Camila Martinez
Marketing Manager
star 5

Easy to work with, thank you!

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 New York’s extremely competitive SERPs?

We build deep multi-level clustering, analyze enterprise competitors, and model search intent with high granularity.

Do you work differently with local NYC 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 NYC?

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 NYC e-commerce and marketplaces.

How do you handle long-tail at NYC 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.

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