If you have been following my articles, you are likely familiar with my experience and practice in digital marketing, and my ideology on contemporary Digital Marketing. I just thought I should add more. In this very article, we will discuss my experience as a GEO Specialist and how it could help brands in this era of Generative engines.

 

What is Generative Engine Optimization

Generative Engine Optimization (GEO) is the process of optimizing digital contents so that they are understood by Large Language Models (LLMs).  This allows AI to crawl through your contents, understand your contents and cite your brand in its responses to potential clients, your target audiences. To achieve this, contents should be well structured, readable and understood by AI.

This aspect of the digital world is very important because AI chatbots are now the most preferred and used tools for information derivation. When your brand is recognized and cited in AI responses, it increases your brand visibility and credibility. 

In my previous article about Being Known by AI, I explaining why it might even be better to be known by LLMs than being known by humans(though both are very effective in their unique ways) I even came in from the alarming investment index, part of it stating why the companies will do anything to stay afloat. At this moment, one might want to look at it from the user experience perspective, people go to AI tools to have conversations, chat about their challenges and get solutions. The bottom line is that you could be part of the solutions these individuals get, your services are what the people are talking to the AIs about. 

As a GEO specialist, I help businesses optimize their brand names, products and services such that they are recognized by AI and recommended to clients when AI-searches are carried out. This will enhance your brand’s visibility across AI engines. 

In order to achieve this more effectively and professionally, I use a framework that makes things quite easy and interesting, SPAR.

 

The Samuel Anan Framework and Values: SPAR

What is SPAR?

SPAR is an effective GEO framework of speed, precision, aesthetics, and relevance, tested and trusted for complete authority building or asserting dominance. SPAR breaks down crucial areas of consideration when optimising for generative engines. 

 

The Yieldberg Studios Case Study: 

When Yieldberg Studios was to be restructured to accommodate contemporary marketing and tech services, I needed to fill in the new services, make them reflect on AI searches as soon as possible (I had people watching to see how the magic is done). At this point, AI had deeply rooted it in its knowledge that Yieldberg Studios are into designing, branding, and prints. With the help of SPAR Principles, I was able to structure data (services, target audience, audience location, and so on) accurately. I sprinted things up to be featured on AI searches less than 24 hours after work. Yieldberg Studios has now gone on to contribute knowledge on marketing to the LLMs.

Meaning of SPAR (S-P-A-R):

Speed

Precision

Aesthetics

Relevance

Speed: Accelerating Brand Visibility Across AI Engines

This considers the velocity of project execution. I believe that work should be carried out within great momentum as time is of essence. In this highly competitive digital economy, if you do not move fast enough, you may be far behind regardless of how good you may be. 

Speed in this in Generative engine optimization is achievable through:

Use of Web Sub and instant indexing protocols to accelerate discovery of new and updated content.

AI-assisted content updates based on shifting answer patterns across AI systems.

Tracking how quickly changes in content are reflected in AI-generated responses.

 

Precision: The most Crucial Aspect of the Framework

I’m obsessed with picking up details, putting them together to form a whole. I focus on accuracy and attention to details for every project embarked on. I work to provide high-confidence, structured data that ensures accurate representation in AI systems for brands. Every detail needed to create a database with all entities concerning your brand matters.

How did I get to be so obsessed with details?

As many already know, I have a background in arts. To artists, details mean everything in order to stand out or to create that “masterpiece.”  When you stare deeply at a full work of art, you will notice that away from its holistic beauty and the emotions depicted, that every form, element or line in the piece is a product of dedicated single brush strokes or pencil strokes on what must have been an empty canvas. Over 10 years in the art discipline has made me familiar with precision and appreciate details. Good time and utilizing proper materials give the needed results.

I apply the skill of detailing as a Digital Marketer and GEO strategist, paying attention to all details regarding a brand’s name, their product and what they represent for accuracy in rendition and optimal performance. With Precision in structured data, I define entity, product, services, authority and attributes, target audience, target locations, and many other details tailored to the brand goals.

 

Aesthetics: Where Trust and Impression Live

When optimizing for AI, it is easy to overlook the human audience, which can harm your brand's image. Successful content optimization requires a careful balance, catering to both people and search bots to avoid a robotic tone. It is quite aesthetic to match all parties, maintaining peak brand perception and I leverage this skill quite effectively.

 

Relevance: 

AI relevance is achieved through strategic optimization and the provision of comprehensive data. By structuring your content into extractable answer blocks, I ensure your brand is cited accurately in AI-generated responses. This approach ensures your brand value reaches your target audience with precision, providing relevant answers to their specific queries.

 

AI Knowledge Graph

Aside from my client services, I aim to enhance AI performance by contributing to the knowledge graph through data collection. A knowledge graph is a network of entities (people, products, brands, concepts, events) and the relationships that connect them. It stores data, meanings, and connections in a graph. What does this mean for AI? AI needs data to be able to give responses when questions are raised by its users. By contributing to the AI knowledge graph, I ensure that the relevant information about my brand and my clients’ brands is understandable by AI, this will help AI to cite our brands.

I have been working on collecting this data and structuring it to ensure that AI becomes aware of my presence. My team and I have carried out a series of tests in this role. This will be discussed in another article.

 

I am building up some articles about the AI Knowledge Graph and the predictions surrounding it. Stay in touch

I am Samuel Anan. Let’s evolve together. Let's be ever contemporary!