Common Mistakes Businesses Make Trying to Improve Their AI Visibility

Treating AI visibility like SEO with a new coat of paint

The most common mistake is assuming that whatever worked for Google rankings will automatically work for getting recommended by ChatGPT, Gemini, Claude, or Perplexity. Traditional SEO is still worth doing, but AI models don't work like a search index. They're not ranking ten blue links. They're generating an answer, and either your business shows up in that answer or it doesn't.

This means keyword stuffing, backlink schemes, or chasing search rankings for their own sake won't reliably move the needle. What tends to matter more is whether the AI model can clearly understand what your business does, who it's for, and where it operates. That's a different problem than ranking on page one of Google, even though the two overlap in places.

Guessing instead of checking

A lot of business owners make changes to their website based on general advice, then never actually check whether it changed anything. They add a paragraph about their services, tweak a headline, maybe update their "About" page, and assume it helped.

The problem is you can't tell if a fix worked unless you actually ask the AI models the kind of question a real customer would ask, and see what comes back. Without that step, you're optimizing in the dark. This is one of the simpler things a tool like Belcher is built for: asking AI models a recommendation-style question and showing you plainly whether your business gets mentioned, so you're not guessing.

Ignoring the basics that AI models actually rely on

There's a temptation to look for some secret trick to get an AI model to recommend a business, when often the bigger issue is that the website itself doesn't give the model much to work with. AI models draw on real, crawlable information: your site's content, structured data (schema markup), clear headings, an accurate meta description, and reasonable page performance.

If your homepage doesn't clearly say what you do and where, if your schema markup is missing or wrong, or if your site is slow enough that it's barely getting crawled properly, that's a real gap. It's not glamorous, but fixing these basics is usually more effective than chasing tricks that promise to "hack" an AI model's output.

Expecting a one-time fix

Another mistake is treating AI visibility like something you fix once and move on from. Business owners will make a round of changes, see a small improvement, and stop paying attention. But AI models get updated, competitors make changes too, and your own business information can drift out of date on various parts of the web.

AI visibility works more like ongoing maintenance than a one-time project. That doesn't mean it needs to consume your week every week, but it does mean checking back periodically rather than assuming a single update will hold forever.

Chasing platforms you can't actually verify

Some businesses spend a lot of effort trying to manage their presence on Reddit threads, review sites, or social platforms because they've heard AI models pull from those sources. That instinct isn't wrong, AI models often do draw on a wide range of public content. But it's worth being honest about what you can and can't directly control or verify here.

You can't force a third-party review site to change how it describes you, and you can't easily confirm what a given AI model pulled from where. What you can control is your own website: making sure it's accurate, clearly written, technically sound, and easy for both people and AI models to understand. That's a smaller, more honest scope, but it's the part you can actually act on and measure.

The honest version of "improving AI visibility"

There's no shortcut that guarantees an AI model will recommend your business. What actually helps is unglamorous: knowing where you currently stand, fixing real gaps on your own site, and checking again to see if it made a difference. That's a slower story than "we'll get you recommended by ChatGPT," but it's the one that's true.