Visibility in the times of Generative Engine Optimization (GEO): Optimizing the top 3 types of AI Search
Did you know that a whopping 68% of adults in the U.S. use generative AI platforms as their primary tool for online searches? (Source: Statista)
How do you search for information on the Internet? Do you google or shoot prompts at ChatGPT, Gemini, or Perplexity? Search engine results give you 10 blue links on a page to carry on your quest. However, generative AI search provides a comprehensive one-shot answer to your question that you can further narrow down with finer prompts. Google and other search engines are still very popular, but generative AI has quickly reshaped how everyone searches for information. They provide a conversational and context-aware search experience. So, the question is, does your brand appear in the generative AI results?
How to make your brand visible in Gen AI search?
As a marketer seeking a first-mover advantage, the question arises: how to optimize content for generative AI visibility? How do we show up in generative AI’s results within the intent of creation, conversation and critical thinking? Because when brands show up in these channels, they gain value and mindshare. Interestingly, LLMs rely on their training data and use Google or Bing to validate their answers. So, when it comes to optimizing for generative AI search, the aim is to create content that integrates into AI-generated responses, providing answers that match what users need.
Coming to generative AI searches, there are several engines that can be boiled down to 3 types. So, marketers must clearly define the objectives of their optimizing efforts and determine the strategy for each type of AI search engine. Now that we recognize Gen AI optimization is paramount, search marketers should align their strategies with the Generative Engines they target. Tailored strategies are a game-changer for real, impactful results.
What is the Ideal B2B Content Strategy for Videos
Having a robust content strategy is the bedrock of successful B2B video marketing. It ensures that the right people see your videos, drive meaningful engagement, and contribute to business goals. Let's break down the content strategy into the 3:TOFU, MOFU and BOFU.
Top of Funnel (TOFU)- Aware and attract
Middle of Funnel (MOFU): Demonstrating value and nurturing your audience
Bottom of Funnel (BOFU): Deep dive and convert your audience
Understanding the 3 types of Generative AI Engines
1. Training-First Systems (Claude, Llama)
In this context, success relies on establishing a robust, enduring foundation rooted in brand belief systems. This approach underscores the importance of thought leadership pieces, case studies, and authoritative content that gradually solidify brand authority and credibility.
2. Search-First Systems (Perplexity, AI Overviews)
Fundamental SEO principles are key here. To appear in search results promptly, you can simply focus on refining the SEO strategies and securing search engine indexing.
For example, I asked Perplexity: What are the best semiconductor marketing companies? And here are the results. Anion Marketing came No. 5 in this search results.
3. Hybrid Systems (Gemini, ChatGPT)
The key is to strike a balance here. It is critical to have a strong foundational content base while being agile and keeping up with real-time updates that keep the brand relevant.
I asked the same question in ChatGPT. It is a general question, so it relied on its training data. On further prompting it, ChatGPT did a real-time search and voila! Our brand is here ranking No. 2!
Testing and Learning Across AI Models
As a marketer, you can experiment with the various AI systems to assess content visibility and ranking patterns, both across and within models. By monitoring the changes and noting the attributes that consistently appear for your queries, and which ones vary- to what extent - you can decide the strategies for each of the 3 AI systems.
Strategy for the 3 Types of Generative AI Engines
Let us deep dive into each of the Gen AI systems and find out the apt strategy.
Optimizing for Training-First AI systems like Claude or Llama:
The strategy here is to build a strong digital presence that is consistent, valuable, and authoritative. Being a long-term strategy, this approach may not reflect immediate results, but when these AI systems update their training data, ensure that your brand becomes part of their knowledge base.
Action:
Focus on creating high-quality, evergreen content that ensures brand positioning as an industry leader. You can also identify the gaps in search intent, where the user might be looking for other alternatives- this can form a strategic starting point.
Breaking the silo:
Advertising, PR, and initiating long-term reputation-building initiatives strengthen the brand’s image in the public consciousness. The outlook is long-term.
Optimizing for Search-First Systems like Perplexity:
These Gen AI systems work in real-time, pulling information from web indexes to generate answers. To influence Search-First Systems, the key lies in understanding how these Gen AI systems process and prioritize content. They are highly responsive to SEO tactics, making search optimization a direct path to Generative AI Optimization.
Steps that marketers can take:
- Use proven SEO strategies, ensuring your content is relevant and well-optimized for discoverability.
- Coming up with timely, newsworthy content that aligns with user interests.
- Prioritizing indexability and having a strong indexing reputation.
Optimizing for Hybrid Systems like ChatGPT or Gemini:
The Hybrid AI systems constantly switch between training data and retrieving real-time information. For these versatile systems, marketers, too, need to be agile.
Will only optimizing SEO do the trick here? No. Marketers must understand how different queries are processed in these popular Hybrid AI systems. To separate the customers’ potential queries that will trigger ChatGPT to fetch answers in real-time from the web vs. the ones, ChatGPT answers trusting its legacy training data. Prompts that trigger real-time search are the key to visibility here.
How will marketers strategize for this?
- Evergreen content:
Ensuring your content is evergreen and robust enough for the Hybrid Gen AI model to refer to from training data. - Refreshing content cadence:
Evergreen and robust content also goes stale. Monitoring, refreshing, and making it relevant to today’s context is imperative. - Being agile:
Check insights, keep an eye on emerging trends and be ready to jump on addressing trending topics with up-to-date content.
Which path to take?
Is there a one-size-fits-all approach here? No!
Understanding how each AI system works and how your customer searches for answers is the key. It may feel like entering uncharted territory. However, for a marketer, the fundamentals remain the same: understanding the target audience, meeting them where they are, being curious, being relevant, providing value, and always evolving. Whether you are building a lasting legacy with Training-First AI Systems, honing the fast-paced race with Search-First Systems, or balancing both with Hybrid Systems, the key lies in agility.
So, which path do you want to take, or master them all? With an AI-driven future, it is okay to feel overwhelmed. We, at Anion Marketing can help you to strategize and reach out to your customers exactly where they are. We can craft a tailored strategy for you. Contact Anion Marketing today!
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