Machine Learning in SEO – Implementation Guides
Implementation guides for utilising machine learning in organic search and broader digital marketing projects, showing different ways that the data can support the execution of the project, or improve the organic search visibility strategy. These are guides are typically a follow-up to the Machine Learning Tutorials and Machine Learning Templates and show you the ‘what now’ section, following the execution of a ML API or the training of the model. What to do next, and how to ensure that the insights and data you have gathered is actually properly utilised and incorporated into your strategy or project.
57 posts
- Implementation guides
How to Find Machine-Learning-Enabled Automation in Your SEO Workflow
You do not need one magic script that does everything. You need a repeatable habit of spotting small automatable tasks. Here is…
Lazarina Stoy31 Jul 2026 · 6 min - AI search optimisation
How modern search actually works: the five-stage retrieval funnel
Before an AI answer engine writes one word, it has already thrown away almost everything. If you do not know where in…
Beatrice Gamba30 Jul 2026 · 8 min - AI search optimisation
Indexed is not selected: your AI search problem isn’t ranking
Agentic systems decide whether your content is used before anyone sees an answer. Ranking measures the wrong thing. The distinction that reorganises…
Beatrice Gamba30 Jul 2026 · 8 min - AI search optimisation
How LLMs Co-Cite: Building Authority by Association
When an LLM cites multiple sources in a single response, the sources it pairs together quietly signal which brands belong in which…
Beatrice Gamba13 May 2026 · 7 min - AI search optimisation
Cross-Platform Entity Consistency: The LLM-Era NAP
Local SEO has always known that NAP consistency matters. The LLM era extends that principle to every brand and every entity. Here…
Beatrice Gamba13 May 2026 · 5 min - Implementation guides
What Schema.org @id Does and Why Your Entity Graph Falls Apart Without It
The @id property is the single most important technical element of structured data for entity recognition. Without it, your schema markup is…
Beatrice Gamba13 May 2026 · 6 min - AI search optimisation
Why Entity Relationship Mapping Is Critical for Brand Visibility
Individual entities have limited value. Connected entity networks are what create exponential authority. Here are the six relationship patterns that turn isolated…
Beatrice Gamba12 May 2026 · 10 min - Implementation guides
How Structured Data Reinforces Entity Understanding in AI Search
Structured data turns your content from text Google has to interpret into facts machines can read directly. Here is how schema.org, JSON-LD,…
Beatrice Gamba12 May 2026 · 12 min - AI search optimisation
5 Steps to Identify and Fix Entity Recognition Gaps That Block LLM Visibility
Five specific entity gaps stop LLMs from citing your content with confidence. Here is how to spot each one in your own…
Beatrice Gamba11 May 2026 · 7 min - AI search optimisation
How Entities Power Query Fan-Out in AI Search
Most of the searches happening on your behalf right now were never typed by anyone. Here is how AI systems generate entity-driven…
Beatrice Gamba11 May 2026 · 8 min - Implementation guides
What Is SERP Feature Analysis? How to Use It for Smarter Keyword Research
SERP features aren't just visual elements — they're Google's live admission of what it thinks users want for any given query. Here's…
Lazarina Stoy11 May 2026 · 11 min - Implementation guides
What Is Search Intent in SEO? A Practical Guide to Using It in Semantic Keyword Research
Search intent goes far beyond informational, navigational, and transactional. Here's how to think about explicit and implicit intent, what the patents reveal…
Lazarina Stoy11 May 2026 · 26 min
