How to make your business top of mind for AI search engines

AI is quickly replacing traditional online search as the front door to finding a business. I recently heard a story about a car shopper who drove miles out of her way to visit a specific dealership, bypassing many car lots much closer to home. Why? Because she searched car dealerships with ChatGPT and it told her that customers had a much better experience at this particular dealership.

Stories like that are becoming the norm – and this new norm is different. AI engines such as ChatGPT, Claude, and Perplexity don’t work like traditional search engines. They don’t give you an endless list of results to scroll through. When people ask a question like, “What’s the best pizza place in my area?” AI engines come back and confidently list just a handful of spots.

In the old days, showing up on page one of search results was enough to get you considered. In the new era of AI search, there is no consideration being done. You’re either included in the handful of results or you’re not. The AI engine gives the searcher a recommendation and if your business isn’t among the few to be surfaced, you’ve probably just lost that customer forever.

So how do you get surfaced? You do it by retooling your website and overall digital presence so that AI engines can easily find, read, and understand them. But before you do that, you need to know exactly how your brand rates in terms of its AI search readiness and visibility. You need to have a clear idea of how AI engines evaluate your brand and how much they trust it. If you don’t, you can’t be AI ready – and you could very well end up invisible in the new world of AI search.

Cracking the AI search code

So, what exactly do businesses need to do to improve their chance of being discovered and recommended by AI search engines? There’s no magic bullet for piercing large language models (LLMs) and getting their attention but you can boost your visibility. There are some basic steps you should take on the technical side. The first and most obvious is to have an LLMs.txt file on your website. This lets AI crawlers know that your content is ready to be indexed, which is a small but critically important piece of the puzzle.

There are other technical upgrades you should make but they’re basically table stakes. What really matters are the signals your online presence is giving off. For instance, brands have long been told that review volume matters most. Well, volume is still important but now AI engines are reading the actual text of reviews to extract the sentiment therein. This means the details in the reviews of your business matter more than ever and that the quality of those reviews is just as important as the quantity, if not more so.

Savvy businesses have always been good at soliciting reviews from their customers and using sheer volume to rank high in traditional search results. The difference today is that simple review volume and star ratings aren’t the be-all and end-all they once were. Now, AI is zeroing in on sentiment itself, looking at the substance of what customers actually write rather than just the star rating they leave.

Likewise, on-page signals and site content also matters more now because AI engines are looking for attestation, or evidence across a business’s pages that backs up what is being claimed elsewhere. That includes, for instance, how well your FAQs are populated, whether they actually answer the questions people are asking, and whether that information is easily digestible by an LLM.

For multi-location brands, it also means consistency. If a brand’s main webpage has a ton of useful information but the individual location pages have incomplete or inconsistent messaging, that’s a shortcoming AI engines pick up on.

3 layers of visibility

Let’s take a more granular look at how businesses are treated by AI engines and what they can do to improve that treatment.

• Understand brand-level visibility: Businesses need to be aware of the way AI engines describe their category, and which sources the engines are citing to compile that description. Most businesses have no idea what an AI engine currently says about them, let alone whether it’s accurate.
• Research location-level visibility: This is especially important for any multi-location business. It’s very possible for a brand overall to perform well in AI search while its individual locations don’t perform as well or go missing from AI search results altogether. To avoid this, brands need to double-check the listing accuracy for all their locations. They also need to focus on how often individual locations get mentioned by AI engines and what sentiment is attached to each one.
• Conduct an AI-readiness audit: AI engines don’t prioritize things like keywords and backlinks the way traditional search engines do. What matters more is your content structure and the signals you send. For instance, are your pages designed to answer the actual questions people are asking? Are you generating enough customer reviews, and responding to those reviews in a way that engenders trust? These are the factors that increasingly determine whether an AI engine can find and confidently recommend your business.

Final takeaway

AI is taking a sledgehammer to the old rules of search. Just because your brand earned the top spot on the Google results page in the old days doesn’t mean your business will be equally rewarded by an AI search engine nowadays.

If your digital footprint isn’t built for the way LLMs extract and evaluate information, your business could be invisible to the people who are looking for it. Meanwhile, businesses that do transform their digital identity for maximum AI-engine appeal will likely find themselves growing like never before.

For more information, visit reputation.com/

About the author

Reputation

Anu Choudhury is the Chief Technology Officer at Reputation. She is a technology leader with experience in building complex systems in diverse domains such as Networking, Cloud Services, and Automotive Technology. She has a demonstrated track record of setting up highly technical global organizations with best-in-class software development processes, defining product and execution strategy, and solving complex operational challenges.