How to Rank on Google Gemini and Microsoft Copilot

Learning how to rank on Google Gemini — and on Microsoft Copilot, its closest structural equivalent — matters for a reason that has nothing to do with either product being the most popular AI assistant. It's distribution. Gemini is embedded in Google Search, Android, Workspace, and Chrome. Copilot is embedded in Windows, Edge, Bing, and Microsoft 365. Between them they sit inside the default software of an enormous number of business users who will never deliberately choose to open an AI tool.

That makes them the two AI surfaces where a business is most likely to be recommended, or omitted, without the buyer ever visiting a search results page. And critically, they behave differently enough from each other — and from ChatGPT — that a single generic "optimize for AI" approach leaves visibility on the table.

Written August 2026. This category changes faster than any other in search; verify current behaviour before acting on anything more than six months old, including this.

How the Two Systems Actually Choose Sources

The mechanics differ in ways that matter for tactics.

Gemini is grounded in Google Search. When Gemini answers a question that needs current information, it runs retrieval against Google's index and synthesizes from what it finds. Google's own Search Central guidance is consistent on this point: there is no separate "AI SEO" — the same crawlable, useful, well-structured content that ranks is what becomes available to the AI layer. The practical consequence is direct: your Google organic and local visibility is the primary input to your Gemini visibility. If you don't rank in Google's top results for a query, you are largely unavailable to Gemini's grounding step for that query. This is also why Gemini's answers and Google's AI Overviews frequently cite overlapping sources.

Copilot is grounded in Bing. Same architecture, different index. And Bing's index is genuinely different from Google's — different crawl priorities, different ranking weights, and notably a lower competitive bar in most verticals. Businesses that have never given Bing a thought are frequently invisible to Copilot despite ranking well on Google.

That second point is the most actionable thing in this article. Bing Webmaster Tools costs nothing, takes twenty minutes, and is a direct input to Copilot visibility. Verify the site, submit the sitemap, use the URL submission tool for new content, and check the index coverage report. Most competitors haven't.

	Gemini	Copilot
Retrieval index	Google Search	Bing
Primary lever	Google organic + local ranking	Bing organic ranking
Webmaster tooling	Google Search Console	Bing Webmaster Tools
Competitive density	High	Noticeably lower
Local business emphasis	Strong (Business Profile data)	Moderate
Fastest win	Improve Google ranking for target queries	Verify and submit to Bing

The Content Shape That Gets Cited

Both systems are extractive before they are generative. They find passages that answer the question, then assemble them. Content that's easy to extract from gets cited; content that requires the model to infer the answer from a narrative usually doesn't.

Five properties consistently separate cited pages from ignored ones.

1. The answer appears immediately after the question. A heading phrased as the actual query, followed by a direct two-to-four sentence answer, before any elaboration. If your answer arrives in paragraph seven after a scene-setting introduction, it will be skipped in favour of a page that leads with it.

2. Claims are specific and attributable. "Local SEO usually takes three to six months to produce measurable ranking movement for a new business" is extractable. "SEO takes time" is not. Numbers, timeframes, and ranges are strongly preferred by extraction because they can be quoted without distortion.

3. Facts are self-contained. Each passage should make sense removed from its context. A sentence that depends on the previous three paragraphs to be intelligible is a bad citation candidate. This is the single most common structural fix in AI visibility work.

4. The page has structural clarity. Real heading hierarchy, one topic per section, tables for comparative data, lists for enumerable items. Both systems parse structure and use it to locate answers.

5. Entity information is unambiguous. The model needs to know what your business is, where it operates, and what it does — consistently, everywhere. Conflicting information across your site, your Google Business Profile, your Bing Places listing, and third-party directories produces uncertainty, and uncertain entities get omitted rather than risked.

Our Answer Engine Optimization service exists specifically for the first four, and the entity work in point five is the foundation of AI engine optimization.

Curious whether Gemini and Copilot currently mention your business at all? Get a Free Visibility Audit →

Structured Data Does Real Work Here

Schema markup was always useful for rich results. For AI retrieval it does something more valuable: it removes ambiguity about what your page asserts.

The types that matter most:

• Organization with a stable @id, address, contact points, and sameAs links to your verified profiles. This is your entity anchor — the thing that lets both systems connect mentions of your business across the web to one entity.
• LocalBusiness for physical locations, with accurate hours, service area, and geo data.
• FAQPage for genuine question-and-answer content. This maps almost exactly onto how retrieval wants to consume information.
• HowTo for procedural content, where each step is discrete and ordered.
• Article with a real, attributable author and accurate dates.

Validate everything with the Rich Results Test rather than assuming your CMS plugin emitted valid markup — in our audits, broken or contradictory schema is more common than absent schema, and contradictory is worse than none.

Off-Site Signals: What the Model Learned Before It Searched

Retrieval determines what a model finds when it looks. But both Gemini and Copilot also carry learned associations from training, and those associations come from how your business is discussed across the web — not from your own website.

This is why a company can have a technically flawless site and still never be recommended. Nothing outside the site corroborates it.

What actually builds this layer:

• Third-party listings and directories with consistent entity data. Boring, unglamorous, and load-bearing.
• Industry roundups and "best of" lists. These are disproportionately cited when someone asks a recommendation question, because they're structured exactly as the answer needs to be.
• Review platforms with volume and recency. Both systems lean on review sentiment when asked for a recommendation.
• Genuine mentions in publications and community discussion — including forums, which have become notably more influential in AI answers as models weight discussion-based sources for practical questions.
• Your own presence on platforms with strong crawl priority, answered substantively rather than promotionally.

None of this is fast, and none of it can be bought credibly. It's the reason AI visibility work has a longer horizon than technical SEO fixes — and the reason starting matters more than optimizing.

Local Queries Behave Differently

A large share of high-value AI queries are local: "find me a commercial electrician in Mississauga," "who does emergency HVAC near me." For these, both systems lean heavily on structured local data rather than on your website's prose.

The inputs that matter:

1. A complete, accurate Google Business Profile — categories, services, hours, attributes, photos. This is Gemini's most direct local input.
2. A Bing Places listing, claimed and completed. Frequently neglected, directly relevant to Copilot.
3. Review volume and recency across both ecosystems.
4. Citation consistency — name, address, phone identical everywhere.
5. Service area accuracy — claiming areas you don't serve produces mismatched recommendations and, eventually, bad reviews.

Our local search optimization service treats these as the same project as traditional local SEO, because functionally they now are.

Measuring Something That Has No Dashboard

There is no Search Console for AI citations. That doesn't mean measurement is impossible, only that it's manual.

A workable monthly routine:

1. Build a fixed prompt set — 15 to 30 questions a real prospect would ask, covering your services, your location, and comparison queries. Keep it stable so results are comparable over time.
2. Run it in both Gemini and Copilot on a schedule, in a clean session without personalization where possible.
3. Record three things per prompt: whether you're mentioned, whether you're cited with a link, and who is mentioned instead.
4. Analyze the competitors that appear. Look at the specific page they're citing and identify what makes it more extractable than yours. This is the most informative part of the exercise by a distance.
5. Watch referral traffic from AI sources in analytics. Volumes are small relative to search but the traffic quality is generally high, because the user arrived after a specific recommendation.

The Bing Layer, in Detail

Because the Bing index is the single highest-leverage and least-contested lever available, it's worth being specific about what to do there rather than leaving it at "verify the site."

Verify in Bing Webmaster Tools. You can import directly from Google Search Console, which takes minutes and carries your existing verification and sitemaps across.

Submit your sitemap, then use URL submission. Bing offers direct URL submission with a generous daily quota — a mechanism Google removed years ago. New and updated pages can be pushed for crawling immediately rather than waiting to be discovered.

Check the index coverage report. It's common to find that Bing has indexed a fraction of what Google has, particularly on sites built as static exports or single-page applications. Every unindexed page is a page Copilot cannot cite.

Claim Bing Places. The local equivalent of a Business Profile, and vastly less contested. Complete categories, hours, service areas, and photos.

Consider IndexNow. The protocol Bing and several other engines support for instant notification of content changes. If your platform supports it, it removes crawl latency from the equation entirely.

None of this is difficult and none of it takes more than an afternoon. The reason it works is entirely that competitors haven't bothered — Bing is treated as an afterthought, while Copilot sits on the desktop of a very large number of business buyers.

Crawlability for AI Retrieval

A separate technical layer determines whether your content is available to be retrieved at all, and it catches out modern sites more often than old ones.

Server-rendered content. If your key content only appears after client-side JavaScript execution, retrieval may not see it. Google renders JavaScript reasonably well; other crawlers are less reliable. Check what your pages look like with JavaScript disabled.

Crawler access. Review your robots.txt and any bot-blocking at the CDN or WAF layer. Aggressive bot protection frequently blocks AI crawlers alongside genuinely malicious traffic, and the result is silent invisibility. Decide deliberately which AI crawlers you allow rather than discovering the answer accidentally.

An llms.txt file. An emerging convention for pointing AI systems at your most important content in a clean, structured form. Support is inconsistent and it is not a substitute for anything above, but it costs almost nothing to publish.

Clean, stable URLs and working canonicals. Retrieval systems handle duplication poorly. Conflicting canonicals and parameter-driven duplicates fragment whatever authority a page has.

Fast, accessible pages. Retrieval favours what it can fetch reliably. Timeouts and errors during a crawl attempt mean the content simply isn't considered.

Content Formats That Travel Well

Some content shapes are cited far more than others across both systems. Worth building deliberately:

Comparison tables. "X vs Y" content with a structured table is among the most-cited formats, because the comparison is already assembled in the form the answer needs.

Definition-plus-elaboration. A crisp definition in the first two sentences under a clear heading, followed by depth for human readers. Serves both audiences without compromise.

Numbered processes. Ordered, discrete steps with a clear outcome. Maps directly onto how assistants present procedural answers.

Cost and pricing content with ranges and variables. Heavily requested, rarely answered well, and extremely extractable when written with actual numbers.

Genuine FAQ blocks. Real questions, direct answers, visible on the page, marked up with FAQPage schema.

Original data. Anything you can measure and publish that nobody else has — survey results, aggregated anonymized client data, local benchmarks. Original data is the most durable citation magnet available, because there is no alternative source for it.

What Changed for One Business

A GTA commercial services company ranked well on Google — first page for most of its core commercial terms — but appeared in none of the 22 prompts in its test set on either Gemini or Copilot. A competitor with weaker Google rankings appeared in nine.

Diagnosis found three causes:

1. The site had never been submitted to Bing. Coverage was partial and several key service pages were unindexed — which alone explained the Copilot absence.
2. Content was written as narrative. Service pages opened with two paragraphs of positioning before reaching any extractable fact. The competitor's pages led with direct answers and used question-shaped headings.
3. Entity data conflicted. Three different phone number formats across the site, Business Profile, and directory listings, and a legal name on the profile that differed from the trading name used everywhere else.

The work over four months: Bing Webmaster Tools verified with sitemap submitted and pages manually submitted; Organization and LocalBusiness schema implemented with a stable @id and complete sameAs set; entity data reconciled everywhere; nine service and blog pages restructured to lead with direct answers under question-shaped headings; and an FAQ block added to each service page addressing the questions the sales team heard most.

At the four-month re-test: mentioned in 14 of 22 prompts on Copilot and 9 of 22 on Gemini, from zero on both. Copilot moved first and moved further, which is the expected pattern — the Bing index was the fastest thing to fix and the least contested.

The Gemini gains lagged and correlated closely with the pages that also improved in Google organic rankings, which is exactly what the grounding architecture predicts.

The Priority Order

If you do nothing else, do these in this sequence:

1. Verify Bing Webmaster Tools and submit your sitemap. Twenty minutes. Largest single lever on Copilot visibility for most businesses.
2. Reconcile your entity data — name, address, phone, and business description identical across your site, Google Business Profile, Bing Places, and major directories. One day.
3. Restructure your top ten pages to lead with answers. Question-shaped headings, direct answer immediately below, self-contained facts. Two to three weeks.
4. Implement and validate Organization plus LocalBusiness schema with a stable entity anchor. One week.
5. Build your prompt set and start measuring monthly. Ongoing, and it's what tells you whether any of this worked.

For the broader picture across all AI assistants, our complete AI engine optimization guide covers the cross-platform strategy, and how to get your business recommended by ChatGPT handles the one major assistant with materially different mechanics.

Invisible to the AI assistants built into Windows, Android, and Chrome?

We run your business against a real prompt set on Gemini and Copilot, identify which competitors are being recommended instead and exactly why, and give you the ranked fixes that close the gap.

Get a Free Growth Audit →

---

Related reading: AI Engine Optimization: The Complete Guide | How to Get Your Business Recommended by ChatGPT | What Is Google AI Overview?