My AI assistant has also created a podcast episode for the following article. If you prefer listening to reading, you can listen to the podcast via the following link (ATTENTION: Podcast is created exclusively by AI, no guarantee for accuracy).
Success stories like yours from Logikcull show that LLMs such as ChatGPT are also having an increasing impact on the search behavior and ultimately the purchasing behavior of customers. In the case of Logikcull, the company itself was surprised when more and more new customers stated that they had become aware of the software company via ChatGPT. By June 2023, five percent of all leads from Logikcull are expected to have been brokered via ChatGPT. That’s the equivalent of almost 100,000 US dollars a month in subscription revenue for the company(source: OMR).
The field of Large Language Model Optimization (LLMO) is still very new, little researched and there are hardly any really valid and measurable results. Nevertheless, there are initial approaches as to how we can align our websites for the future of LLMs. In the following article, I will give you some initial tips.
What are Large Language Models (LLMs)?
Large Language Models means “large language models”. These models are types of artificial intelligence (AI) that are trained to understand, generate and interact with human language. They can write texts, answer questions, create summaries and more by being trained on enormous amounts of text data. These models recognize patterns, structures and correlations in the data on which they have been trained and use them to generate new content that meets user requirements.
One of the best-known LLMs at the moment is probably ChatGPT or GPT-4o (Generative Pre-trained Transformer) from OpenAI: With ChatGPT, we can already perform a variety of tasks today, such as writing articles, translating texts, answering questions, creating a wide variety of media and writing code.
What is Large Language Model Optimization (LLMO)?
Large Language Model Optimization (LLMO) is an advanced approach in the field of online marketing and artificial intelligence that aims to influence the output of large LLMs such as ChatGPT or Perplexity. Put simply, this technique is similar to classic search engine optimization (SEO).
Specific results can be promoted or influenced by targeted interventions in the training data or by optimizing the content available to LLMs. However, the mechanisms and methods of LLMO differ from those of SEO. LLMs work differently than the classic Google search. Consequently, companies must also choose other methods to optimize their own website for LLMs.
Why is LLMO important?
Consumer surveys, such as the one presented below, clearly illustrate that a growing number of users are directing their queries to ChatGPT or other Large Language Models (LLMs) instead of turning to established search engines such as Google. It is to be expected that this trend will continue and that more and more consumers will initiate their Internet searches via ChatGPT and similar services. As a result, the field of website optimization will become increasingly important for LLMs.
Anyone who thinks they can wait until well-founded research results on LLMs are available should bear in mind that hesitating too long can be risky. Optimization for LLMs takes time. An LLM cannot adapt its algorithm overnight. As Google already knows, adjustments to the website take a few weeks to have an effect on the ranking. It can be assumed that the effects of Large Language Model Optimization (LLMO) will need more time to achieve visible success.
Another reason why companies should not put off the topic of LLMO for too long is the competitive advantage. Companies that are already dealing with LLMO today are likely to gain a clear competitive advantage in the foreseeable future.
What are the best practices for LLMO?
As already mentioned, there has been little research and well-founded testing on LLMO to date. However, if you consider how an LLM works and how it derives its answers on the basis of training data, then the following tips and best practices for LLMOs can already be defined today.
1. the distribution of your own brand on the Internet
LLMs often use database websites, knowledge aggregators or other large publishers such as the Financial Times or Forbes. Database websites are, for example, company directories or rating platforms. Knowledge aggregators are platforms such as Wikipedia or YouTube.
Thus, a possible measure in the context of LLMO is that companies work on being listed by other websites and especially by other well-known databases. In concrete terms, this means that companies must use PR measures or even purchased content to secure a “place” on other LLM-relevant websites.
It is important to mention here that it is not purely about backlinks, as we know it from SEO. It’s really about mentioning them by name, in the right context. And on websites that are of great importance to the LLM.
2. optimize the content of your own website for LLMs
To create the following tips with regard to optimizing your own website for an LLM, I have held several expert discussions with SEO specialists, AI researchers and LLM developers in recent weeks.
1. adaptation to the structure of the LLM
It is recommended to ask the Large Language Model (LLM) directly to find out how it would describe or structure a particular topic, product or service. The selected topic should be similar to the field of activity of the company carrying out Large Language Model Optimization (LLMO). This structural basis can then be used by the company to create its own texts. It is advisable to use structured data. This method may seem like a simple imitation at first, but it is an effective strategy to be likely to be considered by an LLM.
2. use of clear and informative language
LLMs process information most effectively when it is presented in simple, clear and informative language. Companies should take this into account when creating website texts. Structures that represent advantages and disadvantages or comparisons are particularly suitable for processing by LLMs.
3. avoidance of excessively long continuous text
Long continuous texts without subheadings are difficult for LLMs to process. Such websites tend to receive less attention from LLMs than those that offer easy-to-understand answers. It is recommended to start longer texts with a short summary of the most important points. All content should then be prepared in such a way that it can be optimally processed by an LLM.
4. integration of quotes from relevant personalities
Including quotations and references can also be an advantage. Experts in the field of LLM optimization assume that citations of well-known personalities can have a positive influence on findability and relevance in the results of an LLM. The use of statistics and quantitative data is also seen as beneficial for the LLMO strategy.
5. continuous optimization
Experience in the field of search engine optimization (SEO) shows that this is an ongoing process. LLMO requires similarly intensive or even more extensive efforts. Companies must not rest on their laurels, but must work continuously on the further development of their strategies. It is important to keep an eye on both technical innovations and the activities of competitors.
How can I measure the success of LLMO?
Although the techniques surrounding Large Language Model Optimization (LLMO) are not always fully defined today, the methods for measuring success are comparatively easy to implement. Below I recommend two methods that can already be put to good use:
1. customer surveys
As already mentioned in the introduction, customer surveys offer valuable insights into the channels through which consumers have become aware of a company or its products and services. Many companies already integrate appropriate feedback options at the end of the ordering process to capture this information. It is recommended to expand these feedback options to include the response options “LLM”, “ChatGPT” or “Generative AI technology”. With this simple extension, companies can quickly determine whether LLMs already play a role for their customers. In addition, more extensive surveys or focus groups can be conducted to provide deeper insights, such as consumer confidence in LLM results compared to search results and product suggestions from traditional search engines like Google.
2. website analytics
I was surprised myself when I noticed via Google Analytics that more and more users of my website were coming via platforms such as Bing or Perplexity. Both are well-known LLMs who cite my site as the source for certain queries. This observation shows that even classic web analytics tools can provide initial indications of the proportion of traffic companies already receive via LLMs compared to classic Google searches.
However, it should be noted that ChatGPT does not provide any direct sources in the search results. Therefore, there is no direct link from ChatGPT to websites, which means that visitors who come via ChatGPT cannot yet be clearly identified in the website traffic. This underscores the need to continuously refine and adapt analytical methods to develop a comprehensive understanding of the dynamics and impact of LLMs on web usage.
Conclusion: Large Language Model Optimization (LLMO) – How websites are found by LLMs
In conclusion, it should be noted that Large Language Model Optimization (LLMO) is a relatively new field of research in which only limited established best practices exist. However, this fact should not be used by companies as an excuse to continue neglecting this issue. Instead, it is advisable for companies to start dealing with LLMO now, gain initial experience and thereby secure a significant competitive advantage.
What happens next?
Would you like to delve deeper into the topic of LLMO and would you like to talk to me about it without obligation?
Then write me a message with your wishes and questions and we’ll arrange an appointment. Just send me a message via WhatsApp or email.
This article is also available as a podcast episode
Attention! The podcast was created entirely by my AI-Assistant based on my contribution – no guarantee for incorrect content.
Further contributions
If you are interested in this topic, please also read my article on“How are generative AI technologies changing SEO measures?“. In this article, I show you why companies need to pay attention to these measures in addition to SEO and LLMO. The article is also available as a podcast via my AI Assistant.
In his article How to Rank Your Website on ChatGPT, Neil Patel also gives some interesting tips on how to optimize your website for ChatGPT.
