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SAAS / AI SOLUTIONS · SAN FRANCISCO, CA · 4-MONTH ENGAGEMENT

Semantic SEO Case Study: Azuno

Semantic SEOEntity OptimizationLocal SEOGoogle Business ProfileLLM Content Alignment
Azuno Case Study

Background

Azuno is a fast-growing SaaS company specializing in AI-driven analytics. Despite an innovative product, the team struggled to gain traction in search results — their content wasn't ranking for relevant queries, and potential customers were missing them entirely.

The Client Challenge

Azuno, a fast-growing SaaS company specializing in AI-driven analytics, struggled to gain organic traction despite an innovative product. Its content lacked the semantic depth for search engines and AI systems to interpret intent, geo-targeting was weak, and potential customers in its core San Francisco market were missing the brand entirely.

Strategic SEO Solution

Designed a semantic SEO framework tailored to Azuno's needs: reorganized content around entities, context, and relationships to match how LLMs process queries; built localized landing pages and optimized the Google Business Profile to target San Francisco's tech community; and structured content to be machine-readable and easily surfaced in AI-powered search experiences.

Tactical Execution Plan

  • Reorganized existing content around entities, context, and relationships instead of isolated keywords.
  • Built localized landing pages targeting San Francisco's tech community and optimized the Google Business Profile.
  • Structured content to be machine-readable and easily surfaced in AI-powered search experiences.
  • Aligned the broader content strategy with how large language models interpret and surface information, future-proofing the SEO approach.

The Methodology

  1. 1Ran a semantic audit of Azuno's content library against how LLMs interpret intent — product pages read as marketing copy, not machine-parseable assertions.
  2. 2Reorganized content into entity-centered clusters (capabilities, integrations, use cases) so each page answered one unambiguous question an LLM or human would ask.
  3. 3Built San Francisco–targeted landing pages and optimized the Google Business Profile to capture the local tech market the brand was entirely missing.
  4. 4Structured every page with clean headings, direct assertions, and JSON-LD so both Google and AI search experiences could extract answers without inference.
  5. 5Instrumented 4 months of continuous monitoring across Search Console, ranking positions, and AI-citation checks to prove which clusters compounded fastest.

Key Learnings

  • Local + semantic is a compound play: geo-targeted pages captured immediate high-intent demand while entity clusters built long-tail authority in parallel.
  • AI platforms surface pages that make unambiguous claims with clean structure — Azuno's answer-first content started appearing in AI-generated summaries within months.
  • The 4-month window was enough to show signal: +120% organic traffic and top 3 local rankings for "AI analytics San Francisco."
  • Future-proofing isn't theoretical — content structured for entity relationships continues ranking as search engines shift from keyword matching to understanding.

“Farrukh showed us how semantic SEO and geo-targeting could work hand-in-hand with the way AI and language models interpret search intent. His strategy didn't just boost our rankings, it made our content future-proof in an AI-first world.”

Margaret Genet

Head of Marketing, Azuno · San Francisco, CA

MEASURABLE GROWTH

Proven Results

+120% increase in organic traffic within 4 months
Top 3 local search rankings for "AI analytics San Francisco" and related geo-keywords
35% growth in qualified leads from Bay Area businesses
Improved discoverability across AI-driven search platforms, positioning Azuno as a thought leader in the AI/LLM space
STRATEGIC ALIGNMENT

Deploy this methodology

This case study proves that pairing entity-based semantic structure with local geo-targeting compounds visibility across both traditional and AI-driven search.