NLP (Natural Language Processing)

NLP (Natural Language Processing) is a branch of artificial intelligence (AI) that enables machines (search engines, chatbots) to read, understand, and interpret human language in the same way humans do—taking into account context, nuance, and intent.

In the world of Search marketing (SEO/AISO), Google’s implementation of NLP technologies (updates like BERT, MUM, RankBrain) marked the end of the “keyword era” and the beginning of the “semantic search era.” The search engine stopped matching character strings (e.g., “shoes” to “shoes”) and started understanding meaning (e.g., recognizing that “footwear for running on asphalt” is the same as “road running shoes”).

How has NLP changed the rules of SEO?

For a Marketing Manager, it is crucial to understand that the Google crawler has “learned reading comprehension.” This changes content creation in three areas:

From Keywords to Entities:
- Past: Keyword Density mattered.
- Today (NLP): Relationships between objects (Entities) matter. If you write about “Apple,” NLP analyzes the context (words like iPhone, Jobs, Stock vs. Pie, Orchard, Recipe) to know if you mean the tech company or the fruit.
From Phrase to Intent (Intent Matching):
- NLP can infer intent even from imprecise queries. If a user types “something for a child’s headache,” thanks to NLP, Google will show painkillers (product) rather than an article on head anatomy (knowledge), even though the word “painkiller” was not in the query.
Sentiment Analysis:
- Algorithms can assess whether a review or article has a positive or negative tone. This impacts E-E-A-T (Experience, Expertise, Authoritativeness, and Trustworthiness).

How to write content optimized for NLP?

To make your site “liked” by language models (Google Gemini, ChatGPT), the text must be easy to process:

Simple Syntax: Use Subject-Verb-Object constructions. overly complex sentences make it difficult for the machine to extract facts.
Logical Structure: Clear division into headers (H2/H3) phrased as questions, followed immediately by definition-style answers (ideal for Featured Snippets).
Semantic Vocabulary: Using synonyms and related terms (LSI Keywords) that build a “context cloud” around the main topic.

What is the role of NLP in AISO strategy?

NLP is the “fuel” for AISO strategy. Generative models (LLMs) operate 100% based on NLP. If your content is chaotic, full of jargon, or logically flawed, the language model will be unable to process it and will not use it to generate a response (Zero-Click Answer). Conclusion: Good NLP on the page = higher chance of being cited by AI.

What is Google BERT and how does it relate to NLP?

BERT (Bidirectional Encoder Representations from Transformers) is a breakthrough Google algorithm update from 2019, based on NLP. It allowed the search engine to understand words in relation to neighboring words (left-to-right), enabling correct interpretation of prepositions (e.g., "flight to USA" vs. "flight from USA"), which were previously ignored.

Are there tools to check NLP optimization?

Yes. Tools like SurferSEO, NeuronWriter, or Google Cloud Natural Language API allow you to check "how a robot sees your text" and suggest missing entities or semantic phrases to cover the topic comprehensively for the algorithm.

Does writing for NLP kill creativity?

No. Writing for NLP is essentially writing clearly and understandably. What is good for NLP (structure, concreteness, no fluff) is usually also good for the busy reader scanning the text.