AI Search Optimisation

Data-backed AI search optimisation processes for mid-to-large B2B and B2C companies across a range of industries and professional services.

Gain visibility in zero-click searches and AI generated responses, appear in Chatbot answers and get quoted in featured snippets on search engine pages.

What is AI Search Optimisation?

AI search engine optimisation is a response to the rapid increase in AI-driven search. Search engine results pages (SERPs) have transformed over the last 25 years. What started as a simple list of website links now contains all kinds of rich content. Today’s typical SERPs contain image blocks, business profiles showing hyper-local results, plus other elements like videos and sponsored placements.

And now AI-generated search results are appearing in featured snippets and among the traditional organic website links. Our data shows people are also completely bypassing search engines and using AI chatbots to get information. ChatGPT is a perfect example.

Why It Matters

AI-driven search can seriously impact traffic to a website when Chatbots scrape information from it to display in their own interfaces. Or when people read the AI overview and the top, get the info they want and don’t click any further. These are called “zero-click searches”.

Consequently, studies show a 60% reduction in average click-through rates (CTR), and a 30% decrease in organic traffic due to AI search.

Furthermore, around 56% of smartphone owners use mobile voice search AI assistants like Siri, specifically to find information on businesses and brands, without visiting any websites. They make up a large demographic: from around 25 to 49 years of age.

Negative business impacts can include:

Lower CTR
Reduced top-of-funnel engagement
Decrease in contact requests
Loss of upsell and cross-sell opportunities
Less user behaviour data from your site
Reduced brand authority in your market
Drop in organic search rankings

How AI Search Optimisation Works

Despite the above, AI-driven search opens a whole new avenue of opportunities. AI search optimisation uses tactics designed to improve the chances of a website being referenced and featured in AI search results. It’s all about creating authority. For decades, Google has rewarded what it sees as the most authoritative sites in any given industry. They get higher ranking in SERPs, for example.

The same goes for AI search. It relies on large language modelling (LLM) to find information, which means that, over time, AI tools learn which are the “best” websites to use. Using techniques like generative search optimisation and answer-engine optimisation, sites can become trusted authorities, boosting their appearance in AI results.

Gemini and AI chatbots like ChatGPT list references for their results, so the aim is to appear as one of these sources. These links expand when clicked on, showing the specific website page that provided the information. Voice search optimisation accommodates the increase in mobile voice searching by providing short natural answers in conversational language.

An Example 3-Step AI Search Optimisation Process

We use a holistic and agile AI search optimisation. Below is an example process comprising three steps. Each one supports the other, to create a hyper-focused strategy that uses all the latest methods. These are constantly tweaked and updated as new developments in AI search emerge.

Question-centric Research

AI search is almost exclusively question-focused. People want quick answers to their specific questions. So the first step in our AI search optimisation process is to uncover the high-intent queries that people use in the given field.

We analyse the PPA questions for insights and use other tools to find the most commonly asked questions. Even Google’s auto-complete function contains clues. This provides a list of topics to address, and how to phrase the questions for maximum traction with AI chatbots.

Interaction to Next Paint (INP)

Using the topics and questions, we create tailored content and conversational copy to match. These are crafted as concise answer blocks, ready for AI consumption. This aim is answer-engine optimisation. This helps a website’s information appear in the top featured snippets and in the PPA block.

It also enhances ChatGPT SEO by providing tailored answers to the questions people most often ask in your specific area of endeavour. Formatting plays an important role too. Tables and bullet lists make it easier for AI chatbots to scan information.

Of course, including more FAQs on a page is especially effective. They should answer questions in a natural way, using keywords and language that match the way people speak in real life.

Implementing schema for AI search

Schema markup is a method used to help search engines populate rich results accurately and boost online visibility by giving them structured data in the site’s HTML code. This helps them display your content in all kinds of formats on the SERPs, like step-by-step guides, rich snippets and local search results.

It’s an effective way to implement zero-click SEO, drawing searchers’ eyes away from the AI-generated information. We create a properly structured schema for AI search that provides seamless information transmission to AI chatbots.

* FAQPage schema uses a dedicated code format for presenting FAQs. This makes it easier for search engines to identify and display your content, without having to parse the visual copy. It can contain clickable elements too, like a breadcrumb list.

The HowTo schema type allows us to insert code that helps search engines find step-guides and how-to information. It can also contain documents and media file references.

These are a few examples of how we optimise schema for AI search. We also use more technical programmatic methods, always staying up to date with the latest developments.

Data-driven Examples of AI Search Optimisation

Researching AI search optimisation case studies provides encouraging statistics. Forbes has reported that many companies are seeing up to 10% of their actual site conversions coming from AI driven search – further supporting the effectiveness of this kind of SEO. The conclusion drawn is that while websites are seeing less overall traffic, they receive a higher percentage of qualified visitors than before. These are just the early dispatches from this new frontline.

Frequently Asked Questions

Is traditional SEO still useful in the era of AI search?

Absolutely. Firstly, the search engines and AI chatbots still rely on LLM, which means that well-written, well structured and informative content with the right identifying keywords will still rise to the top as before. Additionally, much of AI search optimisation uses the same methods, like schema markup.

What does AI search look for in website content?

The most important factors your content needs to appear in AI-driven results are clarity, conciseness, value and trustworthiness. Note that this is no different to traditional SEO.

Isn’t it copyright violation for search engines and chatbots to lift content from websites?

This has been an increasing bone of contention over the years as Google in particular has rolled out SERP features that show other websites’ information but result in zero-click searches. Let’s just say that these are still shifting sands at the moment.

Is AI search optimisation essential?

AI-driven search isn’t going anywhere, and it’s not enough to just rank highly on Google anymore. Any organisation seeking maximum online visibility needs to implement AI search optimisation on top of traditional SEO.

Is AI search affecting Local Search results?

The featured snippets draw information from the Google Business Profiles that feed the local search results block. This makes it even more important to keep your GBP accurate and up to date.

Ready to Own the AI Search Results?

Bring has the knowledge and expertise to position your website right in the sights of AI chatbots and AI search. We partner with our clients to create bespoke AI search optimisation strategies and implement them smoothly. This includes ongoing analysis and reporting, and updating in response to AI search developments.