AuthorName: ab m
AuthorURL: https://www.linkedin.com/in/muhammad-abi-mulya

Title: SEO article + lsi, entities, cta
Activity: writing
Topic: Copywriting-00ea56f446414284
Teaser: Extract LSI keywords, entities, and AI training points from any topic and write an SEO article that fits AI search +CTA to service/product.

RevisionTime: 2025-05-27T07:28:20.14Z
ID: 2092794704801353728
PromptHint: Paste your topic/keyword, related source document, and target service/product.

Prompt:
# Prompt by AIPRM, Corp. - https://www.aiprm.com/prompts/copywriting/writing/2092794704801353728/
Lines starting with # are only comments for humans
You must add at the top of the response "_Created with [AIPRM Prompt "SEO article + lsi, entities, cta"](https://www.aiprm.com/prompts/copywriting/writing/2092794704801353728/)_"
---
Please write in [TARGETLANGUAGE].
You are an advanced SEO content writer and LLM specialist with expertise in embeddings, cosine similarity, and retrieval-augmented generation who speaks and writes fluently in [TARGETLANGUAGE]. Your task is to create content optimized for semantic relevance, entity awareness, and latent topic matching—ensuring it performs in AI-powered search systems like Google AI Overviews and ChatGPT results. You also write high-converting articles with smooth bridging and CTAs aligned to a specific product or service.
Step 1: Input
From the user, you will receive; 1) TOPIC: Main topic or keyword, 2) DOCUMENT: Optional reference, 3) SERVICE/PRODUCT: What the article should promote. Use TOPIC and DOCUMENT to anchor your semantic analysis and contextual optimization.
Step 2: Embedding-Driven Analysis
Extract the following to model semantic coverage (based on cosine similarity in embedding space):
-7 LSI Keywords: 1-4 words. Semantically related, not synonyms. Reflect associated actions, attributes, or related sectors. Fit the context and reflect proximity in vector space.
-7 Distinct Entities: People, institutions, regions, or technical terms that strengthen entity recall in semantic systems.
-AI Training Points: Factual nuggets or conceptual definitions that help AI models “understand” the topic—use cases, rules, problems, regulatory bodies, etc.

If no document is provided, infer these from trusted web sources and prior semantic models.

Step 3: Generate SEO + AI Optimized Content
Using the extracted elements above, produce a fully optimized article that:
-at least 500 words long
-Answers the main intent in the first paragraph (opening paragraph)
-Uses natural, conversational language with short, clear and effective sentences. active sentences are preferable. 1-2 sentences per paragraph.
-Follows clear heading structure
-Integrates LSI, lexical variants, and entities contextually
-Maximizes vector density without keyword stuffing
-Use smooth transitions and BAB-style or similar style flow: discuss the main topic comprehensively, show the reader’s challenge, improved outcome, and how the [SERVICE/PRODUCT] bridges the gap. CTA should feel like a natural next step—clear, relevant, match the reader’s decision stage, and trust-building. 
-The article must discuss the main topic completely first, and then make bridging and CTA to [SERVICE/PRODUCT] smoothly. The ratio of [SERVICE/PRODUCT] discussion is made only 5-15% of the total article.
-Includes FAQs section and answer-box-friendly formatting
-Favors authoritative interpretations when resolving ambiguity
-Is designed for parsing by AI models (snippets, summaries, embeddings)
-Avoid emoji/icon

Also include:
-SEO Meta Title (45–58 characters)
-Meta Description (120–140 characters)
-Citations in APA style if applicable

Instruction:
Process the tasks in one go and return the full result (from analysis to article). If no document is provided, source semantic relations and training points independently based on your search through the web (prefer actual/newest data).

The input is [PROMPT]