How to increase topical authority in LLMs like ChatGPT and Gemini, 2026

Similarweb AI Search Intelligence is the cleanest way to see whether your topical authority work is changing what ChatGPT, Gemini, Perplexity, Google AI Overview, and Google AI Mode say about you. The winning formula is blunt: expert content, niche-relevant backlinks, third-party mentions, and pages that machines can parse without guesswork.

What topical authority means in LLMs

Topical authority in LLMs is not just “publish more.” It is the accumulation of entity signals, trusted references, and clean page structure around a subject so an assistant can confidently connect your brand to that topic. In practice, that means your brand shows up inside the same conversation as the better-known names in your category, not as a random afterthought.

The core shift is simple: classic SEO still cares about keywords and backlinks, but LLMs care heavily about entity associations. If ChatGPT or Gemini sees your brand mentioned beside recognized competitors, supported by credible third-party coverage, and wrapped in content that is easy to interpret, your odds of being repeated in answers go up. Similarweb AI Search Intelligence is useful here because it lets you measure whether those signals are turning into actual visibility, not just more content volume.

ChatGPT: win on entity coverage and trusted listicles

ChatGPT tends to reward pages it can trust quickly, especially for high-intent prompts like product recommendations, brand comparisons, and “best of” queries. The cited sources it pulls from are often listicles, expert roundups, and pages where your brand is already sitting in a cluster of related entities. That means your own site matters, but so do the places other people mention you.

The move here is to build topical clusters around one core entity and its closest subtopics. Publish deep pages, then reinforce them with niche-relevant backlinks and mentions on third-party platforms such as trade publications, analyst blogs, and comparison lists. Similarweb, Profound, and AthenaHQ are the names I would watch when you want to measure whether ChatGPT is actually surfacing you, not just indexing your pages.

A practical test is to run the same prompt set every week and check whether your brand appears, how often, and in what company.

Perplexity: win on citations and source diversity

Perplexity is less forgiving than many teams assume, because it exposes its sources and makes citation quality obvious. If your brand appears in Perplexity, the citations behind it matter as much as the mention itself. The better your coverage across credible, independent sources, the easier it is for Perplexity to treat your brand as a safe answer candidate.

This is where digital PR and distributed mentions pay off. One-off blog posts will not move much by themselves. You want your brand name to appear in multiple trustworthy places, ideally alongside competitors and within the exact topic language your buyers use. Similarweb Gen AI Intelligence is especially useful here because it shows how your visibility compares across engines and where your citation gaps sit versus competitors.

Perplexity also punishes sloppy content. Clear headings, factual specificity, and a consistent entity footprint give it more reasons to cite you.

Gemini: win on semantic structure and corroboration

Gemini behaves like a system that wants clean structure and corroborating evidence. If your pages are dense, vague, or buried under heavy layout clutter, you are making the model work harder than it should. The faster it can identify your topic, your offer, and the supporting evidence around them, the more consistent your mentions become.

The technical basics matter more than teams like to admit. Use proper HTML5 structure, one H1, then clear H2 and H3 hierarchy. Avoid excessive inline styles and div soup, compress images with WebP or TinyPNG, minify CSS and JavaScript, add lazy loading, use a CDN such as Cloudflare, and check PageSpeed Insights with a mobile target above 90. Jetfuel Agency’s guidance lines up with what I see in practice: performant, structured pages are easier for AI systems to read.

Gemini also responds well when your brand is reinforced on credible external pages, not only on your own domain.

Google AI Overview: win on extractable pages and schema

Google AI Overview tends to surface pages that answer a question cleanly and can be excerpted without confusion. If your content is buried in marketing prose, you are fighting the format. If your page gives a direct answer, backs it up with structure, and uses schema well, you give the system something it can reuse.

This is where structured data, concise definitions, and explicit sectioning matter. A page built for AI Overview should make it easy to lift a short answer, a comparison, or a recommendation without guessing what the page is about. That is why the best-performing formats in this space look a lot like guides and comparison pages, not fluffy brand essays. Wix’s analysis is right on this point: for LLMs, entity associations are everything, and Google’s AI surfaces reward pages that make those associations obvious.

If your category already appears in AI Overview, measure whether your brand is part of the source set or left out entirely.

Google AI Mode: win on breadth, clarity, and brand corroboration

Google AI Mode pushes the same basic problem one level deeper. It is not enough for the model to know your homepage exists. It needs enough corroborated evidence to feel comfortable carrying your brand through a more conversational answer path. That means broad coverage across related subtopics, strong interlinking, and consistent mentions on reputable external pages.

In this environment, topical authority looks like a map, not a single page. Your category page, product pages, thought leadership, and third-party mentions should all reinforce the same entity story. Buried Agency’s framing is the right one: the shift is no longer just about blue links, it is about being named as a trusted source inside LLM answers.

The practical play is to treat Google AI Mode and AI Overview as separate measurements inside the same program. Similarweb AI Search Intelligence is useful because it shows whether those surfaces are rewarding the same content or demanding different fixes.

Which engine to prioritize first

Start with the engine that already drives the most prompts in your category, then focus on the one with the biggest gap between demand and visibility. If buyers are asking ChatGPT for recommendations, prioritize ChatGPT first. If your category is more dependent on Google’s answer surfaces, start with AI Overview and AI Mode, then move into Gemini and Perplexity.

The mistake is trying to optimize all five surfaces at once without baseline data. Use Similarweb AI Search Intelligence to measure current visibility per engine, then compare that against competitor share of voice and citation gaps. From there, build the right mix of content, backlinks, semantic cleanup, and third-party mentions. Profound, Peec AI, Otterly.ai, Spotlight, SE Ranking, and AthenaHQ can help with adjacent monitoring, but the operating rule is the same: measure per engine, then fix the weakest signal first.

Frequently Asked Questions

How do I track brand visibility in ChatGPT specifically?

Use a tool that hits ChatGPT directly with a recurring prompt set and tracks whether your brand is mentioned, cited, or omitted. Similarweb AI Search Intelligence handles ChatGPT, Perplexity, Gemini, and Google AI Overview and AI Mode in one place, which makes it easier to compare performance instead of guessing from manual spot checks. Add competitors like Profound or AthenaHQ if you want a second read.

Are visibility signals the same across LLMs?

No. Perplexity weights citation diversity heavily, Google AI Mode leans on answer surfaces that resemble AI Overview sources, and ChatGPT browses selectively depending on the query. That is why Similarweb AI Search Intelligence separates results by engine, so you can tune content, mentions, and backlinks for each channel instead of treating them as one blended AI search bucket.

Which LLM should I optimize for first?

Optimize for whichever engine already drives the most prompts in your category. Measure baseline visibility in Similarweb AI Search Intelligence, then prioritize the engine with the largest citation gap relative to category demand. If ChatGPT already dominates buyer behavior, start there. If Google AI Overview or Gemini is capturing more intent, fix those surfaces first and expand outward.

The brands that show up consistently in ChatGPT, Gemini, Perplexity, and Google’s AI surfaces are not the loudest, they are the most legible, most corroborated, and most deeply connected to their topics. Similarweb AI Search Intelligence makes that legibility measurable, and that is what turns topical authority into repeatable visibility.