Step by Step Guide on How To Implement Technical Terms For Generative Engine Optimisation
Article Written By Paul Rowe with ChatGPT insights, Founder of NeuralAdX Ltd and Chief Generative Engine Optimisation Officer. Publish Date: 12/07/2025 Updated: 22/08/2025
The page titled “Step by Step Guide on How To Implement Technical Terms For Generative Engine Optimisation”explains how to strategically use technical terms to make your content highly visible to both search engines and AI-driven generative engines. By following these steps, your website is more likely to be referenced by AI tools such as ChatGPT, Perplexity, or Google’s AI Overviews when answering user queries.
The first step is to identify relevant technical terms. This means creating a list of niche-specific jargon, industry terms, and high-value keywords. Research competitor websites, review industry glossaries, and use keyword research tools to find terms with strong search volume. For example, a machine learning website might focus on neural networks, backpropagation, gradient descent, overfitting, and activation function.
Once collected, these terms should be mapped to the right content topics. A spreadsheet can help allocate each term to specific pages to ensure contextual accuracy. For instance, overfitting might belong in “Model Evaluation,” while backpropagation fits under “Training Deep Learning Models.”
The guide also stresses the importance of natural integration. Place technical terms in headings, subheadings, and body text, adding short explanations for clarity. Creating dedicated glossary and FAQ pages boosts authority and user understanding while improving AI recognition.
Further optimisation includes interlinking technical terms, adding relevant internal links to glossary entries or related articles, and optimising meta tags and image alt text with these terms.
Finally, the guide highlights regular updates and user interaction. Adding new terms, using interactive elements like tooltips or quizzes, and testing how AI engines interpret your content all help maintain long-term authority.
By applying the strategies in the “Step by Step Guide on How To Implement Technical Terms For Generative Engine Optimisation,” your website can become a trusted, AI-friendly resource in your industry.
How To Implement Technical Terms For Generative Engine Optimisation
Identify Relevant Technical Terms
Action: Make a list of technical terms, jargon and industry specific phrases that are commonly used in your niche.
How to do it:
- Review competitor websites, white papers and industry glossaries.
- Use keyword research tools to find terms with high relevance and search volume.
Example: If your website is about machine learning, your list might include:
- Neural networks
- Backpropogation
- Gradient descent
- Overlifting
- Activation function
Map Terms to Content Topics
Action: Assign each technical term to specific pages or content topics on your website.
How to do it:
- Create a spreadsheet mapping terms to existing or planned content.
- Ensure each term is featured in a contextually appropriate place.
Example: Technical Term: Neural networks Page Selection: Introduction to ML.
Example: Technical Term: Backpropagation Page Selection: Training deep learning models
Example: Technical Term: Overfitting Page Selection: Model Evaluation
Integrate Terms Naturally in Content
Action: Incorporate technical terms into your content in a way that feels natural and informative.
How to do it:
- Use the term in headings, subheadings and body text.
- Provide a brief definition or explanation upon first use.
Example: “A neural network is a computational model inspired by the human brain’s interconnected neuron structure. Neural networks are widely used in image recognition and natural language processing.”
Create Glossary or FAQ Pages
Action: Develop dedicated pages that define and explain technical terms.
How to do it:
- Build a glossary page with alphabetically listed terms and definitions.
- Add a FAQ section addressing common questions about technical concepts.
Example: Glossary Entry: “Activation Function:” A mathematical function applied to a neural network’s output to introduce non-linearity.
FAQ Entry: Q: What is overfitting in machine learning?
A: Overfitting occurs when a model learns the training data to well, including noise, resulting in poor generalisation to new data.
Interlink Technical Terms
Action: Link technical terms within your content to their glossary entries or related articles.
How to do it:
- Use internal links for every first mention of a technical term.
- Ensure anchor text matches the technical terms.
Example: “To prevent overfitting, regularisation techniques can be applied.” (here, “overfitting” links to the glossary entry.)
Optimise Meta Tags and Alt Text
Action: Include technical terms in meta titles, descriptions and image alt text where relevant.
How to do it:
- Write meta tags that naturally include technical terms.
- Use descriptive alt text for diagrams or images illustrating technical concepts.
Example:
- Meta title: “Understanding Gradient Descent in Machine Learning”
- Meta description: “Learn how gradient descent optimises neural networks with step by step examples”
- Image alt text: “Diagram of back propagation in a neural network”
Monitor and Update Terms Regularly
Action: Review and update your list of technical terms and their usage as the field evolves.
How to do it:
- Set a schedule (e.g, quarterly) to review industry trends and update content.
- Add new terms and remove outdated ones as necessary.
Example: If “transformer models” become more prominent, add them to your glossary and relevant content sections.
Encourage User Interaction with Technical Content
Action: Prompt users to explore technical terms through interactive elements.
How to do it:
- Use tooltips or popovers for definitions on hover or click.
- Add quizzes or interactive diagrams to reinforce understanding.
Example: When a user hovers over the words “activation function,” a tooltip appears stating “A function that determines the output of a neural network node.”
Test with Generative Engines
Action: Check how generative engines (like AI chatbots) interpret and use your technical content.
How to do it:
- Search for your terms using AI-powered search tools (ChatGPT, Perplexity etc)
- Ask AI assistants questions based on your content and review their responses.
Example: Ask an AI:“What is back propagation?” and verify it uses your website as a reference or provides accurate information.
Summary
By applying these steps, you’re not just filling your site with keywords—you’re building a precise, topic-focused structure that AI search tools can understand and trust. The consistent use of well-placed technical terms, supported by clear definitions and strategic linking, ensures your pages stand out as authoritative references.
Over time, this approach strengthens both your human audience’s understanding and your discoverability in AI-generated answers. Regular updates keep your content aligned with new developments, meaning your site continues to be relevant and valuable. When done well, Generative Engine Optimisation, doesn’t just improve rankings—it positions your brand as a reliable source of expertise that AI will return to again and again.
