7 GEO Strategies To Get AI Models to Recommend Your Brand

The way people search has changed and most brands haven’t caught up yet. ChatGPT has over 900 million weekly active users. Google’s AI Overviews appear in nearly 50% of search results. Perplexity is growing fast, quietly eating into traditional search traffic.

All of these platforms share one thing in common: they generate answers from sources they trust. If your brand isn’t one of those sources, you simply don’t exist to a massive and growing audience.
The good news? Most brands haven’t started yet. The window to build an early position is still open.

Here’s how I’d approach it.

GEO stands for Generative Engine Optimisation. In my view, it’s the single most important discipline in search marketing right now. Put simply, it’s the practice of making your brand the source that AI search engines cite, reference and recommend when users ask questions in your space.

It’s different from traditional SEO and AEO, and the difference matters.

• Traditional SEO gets your pages ranking in Google’s standard search results. You target keywords, earn backlinks, and structure content so search engines can crawl and rank it.
• AEO (Answer Engine Optimisation) takes it a step further. The goal is to get your content into featured snippets and voice search answers, what most people call “position zero”.
• GEO goes beyond both. AI platforms do not return a list of blue links. They read multiple sources, synthesise the information, and write their own answer. If your brand appears consistently in the sources they draw from, you get cited. If not, you get left out entirely.

The signals, the content structure, and the strategy required are all different from what you may be used to. The rest of this article breaks down by recommendations to achieve success in the new area of search.

Most GEO advice skips straight to tactics. In my experience, that’s a mistake. If you don’t know where you stand right now, you’ll have no way of knowing whether anything you do is working.

Start with a simple audit. I’d pick 10 to 15 questions your ideal customer might ask an AI engine, such as:

“What’s the best tool for [your category]?”
“Can you recommend [your category] in London?”
“What should I look for when choosing [your service type]?”.

Then run each of those queries across Gemini, ChatGPT, and Perplexity.

For each response, note three things:

• Is your brand mentioned at all?
• If not, which competitors are getting cited?
• Are any sources named. If so, which ones?

This gives you a baseline.

You’ll quickly see which platforms you have traction on, which you’re invisible on, and what kinds of queries tend to surface competitors instead of you.

I’d repeat this process every month, because AI generated responses aren’t static. Models update, new content gets indexed, and citations shift. What’s true today may look very different in 60 days.

Doing this manually across several platforms gets time consuming fast, which is why dedicated GEO tracking tools are worth considering to automate the monitoring and flag changes over time.

Something I see get lost in the rush to talk about AI search is this: Google’s AI Overviews heavily favour content that already performs well in organic search.

AI engines frequently pull citations from top ranking pages. If your website ranks well for a relevant query, it is far more likely to be used as a source.

Your existing SEO foundations are not wasted. In my view, they are the bedrock of any solid GEO strategy.

I’d keep doing the things that drive organic rankings:

• Publishing well researched, high quality content
• Earning backlinks from credible publications
• Keeping technical SEO clean, covering site speed, crawlability, and structured data
• Building topical authority in your niche

The shift I’d encourage is not away from SEO. It’s about layering GEO tactics on top of it. Think of organic search performance as the floor. GEO is what you build above it to reach the AI layer.

The brands I’ve seen do this well are not choosing between SEO and GEO. They run both in parallel. Their content is built to perform in traditional rankings and to be cited by AI systems at the same time.

This is where most of the practical work happens. AI engines are selective about what they cite. Structure and specificity matter more than most people realise.

Here is what I recommend focusing on.

Write for citability, not just readability

Content that reads well and content that gets cited are not the same thing. I’ve learned to treat them as separate goals.

AI engines look for clear, specific claims. Definitions, data points, step-by-step processes, and expert positions are what get pulled into generated responses. Vague or hedged paragraphs get skipped.

Here is a simple example of the difference:

Weak: “Customer retention is an important part of any business strategy.”

Citable: “Increasing customer retention by just 5% can increase profits by 25% to 95%, according to research from Apple Research.”

The second version gives the AI something concrete to work with. The first gives it nothing.

Answer questions directly

AI search runs on questions. Users type conversational queries and the AI looks for the most direct, useful answer it can find.

I’d structure content around the actual questions your audience asks, not just the keywords they search.

Use H2 and H3 headers that mirror real questions. Keep paragraphs tight. Add FAQ sections that address common follow-ups in a clean, scannable format.

When an AI engine scans a page and finds a clear answer to a specific question, that page becomes a natural candidate for citation. Make it easy for the AI to find what it needs.

Use schema markup

Schema markup helps AI models understand not just what your page says, but what it means.

FAQ schema signals that you are directly answering questions. How-To schema signals a process. Organisation schema establishes your brand identity and authority.

None of it is particularly exciting to implement, but in my experience it works. The right schema across your key pages gives AI systems much stronger signals about what your content covers and why it is relevant.

Build topical depth

AI engines favour sources that demonstrate genuine expertise on a subject. Mentioning a keyword frequently is not the same as being an authority on it.

I’ve seen brands publish dozens of loosely related blog posts and wonder why they aren’t getting cited.

The issue is breadth without depth. A well structured content cluster that covers a subject thoroughly from multiple angles sends a far stronger signal than scattered posts ever will.

My advice is to pick the topics that matter most to your audience and go deep. Cover the core questions, the follow-ups, the edge cases, the how-tos, and the comparisons. Become the most useful resource on that subject. The citations tend to follow naturally from there.

This is the most underrated GEO strategy I come across. Most brands skip it entirely.

Reddit now appears in Google’s results far more often than it did two years ago. That is not accidental.

Both Google and AI platforms have grown to trust user generated content as an authentic signal of what real people actually think. Ask ChatGPT for a tool recommendation or a product comparison and the response will regularly pull straight from Reddit threads.

Your brand’s presence in those threads matters. The catch is that Reddit does not tolerate obvious marketing. The approach has to be genuinely participatory.

Find where your audience talks

Search Reddit for your product category, the problems you solve, and your competitors’ names. Identify five to ten active subreddits where these conversations are already happening. Threads like “what’s the best tool for X” or “has anyone tried Y” are exactly the discussions AI engines mine for recommendations.

Contribute first, promote later

Spend a few weeks genuinely participating before your brand ever comes up. Share knowledge, answer questions, add useful context. Reddit users check account history. If every post is a product mention, you will get flagged immediately.

Be honest when you do mention your brand

Share it as one option among several. Say what it is good for and where it might not be the right fit. AI engines weight authentic, nuanced mentions far more heavily than promotional ones. They are built to surface what real people believe, not what brands want them to believe.

Check what AI engines are actually citing

Run your core queries in ChatGPT and Perplexity and look at which Reddit threads appear in the responses. If your brand is not in those threads, that is where to focus your energy next.

When someone asks ChatGPT “what are the best project management tools?”, the AI doesn’t generate that list from its own preferences. It synthesises from existing listicle content on sites with strong reputations.

A single well-placed mention in a high-authority listicle can put your brand into AI-generated recommendations across ChatGPT, Perplexity, and Google AI Overviews simultaneously.

This makes listicle placement one of the highest-leverage GEO tactics available.

Find listicles that AI is pulling from
Run your target recommendation queries in ChatGPT and Perplexity and pay attention to which articles they cite as sources. Those are the exact placements you want. Make a list.

Build a target publisher list

Identify the publications that come up repeatedly across both AI and traditional search for “best [your category]” queries.

These are the sites with enough domain authority that AI systems treat them as credible sources. Focus your outreach here rather than spreading thin across dozens of smaller publications.

Make it easy to include you

Before pitching anyone, make sure your product pages are clean and clearly written. A compelling one-liner that explains what you do, obvious differentiators, visible social proof, and transparent pricing.

Authors updating or writing listicles want inclusion to be easy. If they have to dig for basic information about your product, they’ll skip you.

Give authors a reason to say yes

Offer a free account, a demo, or data or insight they can actually use in their article. A pitch that leads with value gets a far higher response rate.

Listicles get updated regularly, and AI engines re-scan them when they do. A placement you earn this month could start generating AI citations within weeks.

One of the less discussed elements of GEO is entity recognition. Put simply, it’s about how clearly AI systems can identify and understand your brand as a distinct entity in the world.

Google and other LLM’s use entity graphs to map the relationships between things: companies, people, products, topics, and locations.

If your brand is well established with clear associations around what you do, who you serve, and what space you operate in, you are far more likely to be recommended when relevant queries come up.

Here are the signals I would focus on:

1. Google Business Profile. Keep it complete, accurate, and regularly updated. It is one of the clearest signals to Google about what your business is and where it operates.
2. Wikipedia and Wikidata. AI models are trained extensively on Wikipedia. If your brand has a page, or is mentioned accurately in relevant articles, it carries real weight.
3. Consistent NAP data. Your Name, Address, and Phone number should be identical across every directory, including Crunchbase, LinkedIn, and industry databases. Inconsistency weakens your entity signals.
4. Earn brand mentions. Press coverage, expert quotes, and guest articles all build your brand’s presence in the content AI models learn from. The more your brand appears in high quality, contextually relevant sources, the stronger your entity recognition becomes.

Google’s E-E-A-T framework covers Experience, Expertise, Authoritativeness, and Trustworthiness. It was designed for human quality raters assessing web content. The signals it looks for are almost identical to what AI systems use to evaluate whether a source is worth citing.

Here is what I would focus on:

Author credentials

Content attributed to named, identifiable experts gets treated very differently to anonymous content. If your team has real expertise, make it visible. Author bio pages, LinkedIn profiles, published research, and speaking credits all build the picture.

Original research and data

AI systems cite statistics constantly. Brands that publish original surveys, studies, or proprietary data get cited repeatedly because they have created something nobody else has. Even a simple annual customer survey can produce data points that get picked up and referenced widely.

External validation

Awards, certifications, media coverage, and verified reviews all send a clear signal to AI systems. They show that other credible sources have already vouched for your brand.