Introduction to Generative AI Optimization
There’s been a lot of talk recently about whether large language models (LLMs) are replacing a considerable amount of Google searches. While Google is clearly still the market leader, with 14 billion searches per day worldwide, an estimated 37.5 million “searches” on ChatGPT represent an opportunity for your brand. SEO professionals have years of experience testing optimization tactics on Google, but we’re still at the beginning stages of understanding how to get your brand cited in generative AI chatbots.
Understanding the Opportunity
This is an exciting opportunity because it forces people to test and learn rapidly. Through some testing and research, here are some tips that have helped develop initial recommendations for clients for generative AI optimization, regardless of whether it’s ChatGPT, Gemini, Deepseek, or whatever generative AI chatbot comes next.
Using Generative AI Chatbots to Learn About Your Brand
First, use generative AI tools and start asking them questions about your brand to find the sources they utilize to answer your queries. This will help you better understand what sources it’s been trained on and what pages on your site (or competitor sites) matter to its understanding of your brand. Ask questions like:
- Tell me about [company]/[product].
- What are the best brands in [vertical] and why?
- What are the pros and cons of [company]/[product]?
Analyzing the Results
For example, when asking ChatGPT-4o, “Tell me about HubSpot,” it gives a nice summary with a lot of useful citations. From this, you can see that a legal page is being cited multiple times in a company overview, so those are important. You can also see the HubSpot Knowledge Base where information is being pulled from as well. Often, a company’s About page is the main citation, but clearly, HubSpot has built out a better legal section than its core pages.
Ensuring LLMs Can Crawl Your Website
This was true at the beginning of SEO, and is still true now. Ensure you have a robots.txt file on your website’s server with directives to crawlers about pages and sections they can crawl and index. A lot of site owners initially rushed to block LLMs from crawling their sites when ChatGPT first launched, as it was unknown (and also probably scraping content for the model). If you want to be included in generative AI results now, though, you need to be where the AI crawlers can see you, so double-check that it is all configured correctly.
Utilizing Credible Citations and Quotes in Content
A group of researchers from several prominent universities conducted a study on AI search engine optimization and what was more likely to surface in response to queries. The tactic that worked the best, especially for factual queries, was adding citations from authoritative sources. Using language like “according to [source],” adding a statistic with a credible citation, or a quote from a known expert all increased the likelihood of showing up in a generative AI chatbot responses by as much as 25.1% for sites ranking in position 4 in Google and by 99.7% for sites ranking in position 5 in Google.
Mentions in Prominent Databases and Forums Help
There are lots of reasons to be paying attention to prominent forums like Reddit and Quora or popular database sites like Wikipedia. Not only do they own lots of organic search real estate, but they are also obvious sites for training LLMs. Reddit is now, smartly, selling data licensing to AI companies. Being a topic of discussion on these sites will only help your brand.
Developing an Exceptional About Page
If there is one area of your website you need to improve on, your About page may be it. Generative AI models utilize these types of pages to understand what a company does and how credible the company is. If you ask any of these platforms for information about your brand, you may be surprised by how heavily they rely on your About page to deliver the answer.
Focusing on Long-Tail Keywords
Modern transformer-based LLMs are based on a statistical analysis of the co-occurrence of words. If an entity is mentioned in connection with another entity with frequency in the training data, there is a high probability of a semantic relationship between the two entities. To optimize for this, it’s more useful to use keyword research tools to better understand related keywords.
Stopping Siloing SEO
We’re entering an era when websites get fewer and fewer clicks from organic search. For most brands, a multi-channel strategy has never been more imperative. Not only does building brand recognition help fuel some of the other best practices here, but LLMs are also being trained on social media and marketing content. Having an aligned, cross-channel strategy only strengthens your brand.
Tracking Referrals and Reverse-Engineering
Once you start seeing generative AI platforms driving traffic to your site, start paying attention to what pages bring that traffic in. Then, visit that generative AI platform and try to recreate searches that could lead to your page as the answer. You’ll start to learn what topics these platforms associate with your brand, and then you can find ways to double down on that type of content.
Conclusion
While the tool companies are trying to catch up with how to help digital marketers optimize in this era of generative AI, we will have to be more reliant on ourselves to reverse-engineer what we’re seeing in the data and run our own experiments. By following these tips and staying ahead of the curve, you can ensure your brand is well-represented in the world of generative AI.