SEO vs GEO: differences, connections and practical priorities.

SEO stands for search engine optimisation. It includes making content useful to people and accessible to search engines. A product page, a guide and a service page have different jobs: explaining, comparing or helping someone take a specific next step.

GEO stands for Generative Engine Optimization. The research paper of that name uses the term for content visibility in generative answers. In this guide, we use it as a working term for examining source presence, clear information and meaningful relationships in AI-assisted search.

Start by defining the system and search situation you want to investigate. An observation in one assistant is initially a finding for that specific test. It does not establish a conclusion about every AI system.

Comparing user tasks helps with planning. Someone looking for a specific supplier needs different information from someone exploring several possible solutions. Both situations can occur within the same customer journey.

For Google’s AI Overviews and AI Mode, the SEO fundamentals still apply. Google requires neither special AI files nor a dedicated schema markup for these features. This describes Google Search; it is not a technical specification for other providers.

Start with the existing website: can important pages be reached? Do internal links lead to them? Are key statements available as text? Investigate specific obstacles before introducing additional formats and tools.

Here, an entity means a clearly identified thing: a company, a person or a particular product, for example. In editorial work, that means using consistent names and explaining relationships explicitly. Who supplies the product? What task is it intended for? What limitations apply?

Structured data must accurately represent visible content. It cannot replace missing facts or guarantee a special search appearance. Review the text and markup together.

Begin with a decision your customers actually need to make. Write the short answer first, then explain conditions, differences and limitations. Clear examples of your own make the content more useful than a collection of general claims.

Use this sequence as a practical planning aid. Choose your starting point from an observed problem and record what would demonstrate an improvement. This turns a broad subject into a manageable piece of work.

For your own AI tests, record the question, system, time, selected settings and observed sources. Use comparable conditions and multiple observations. A single screenshot is a snapshot, not a reliable trend.

In Search Console, Google’s AI features are included in the “Web” search type. Complement search data with landing pages, relevant contact journeys and your documented tests. Keep each conclusion within the limits of the data observed.

Separate completed work from its effect: correcting a product page is an implementation result. Whether reach, inquiries or revenue change requires measurement and an appropriate comparison. These actions do not support a fixed promise of mentions or rankings.