You asked Gemini a question about your own category, and it cited someone else. That stings, and it is also fixable.
Here is the good news: how to get cited in Gemini is a mostly mechanical problem, not a mysterious one. Gemini pulls from Google's index, so a lot of the work you have already done still counts.
By the end of this guide you will have eight steps you can start this week, and a way to tell whether each one worked.
Know which Google surface you are actually optimizing for
Before the steps, let's clear up the thing that trips up almost everyone.
Gemini is Google's standalone assistant. It lives at gemini.google.com, in the Gemini mobile apps, and inside Workspace and Pixel. That is the surface this guide covers.
Google AI Overviews are different. Those are the AI summary boxes above the blue links in Search results. AI Mode is a third thing again, the conversational mode inside Google Search itself.
Three products, one company, shared plumbing. They are not interchangeable.
This matters more than it sounds. Search "how to get brand into Gemini" and most of what comes back is advice written for AI Overviews, wearing a Gemini headline. The tactics overlap, but the measurement does not.
Why does the difference matter in practice? Because your tracking and your tests have to happen on the surface you care about. A page that shows up in an AI Overview may never appear in Gemini's sources panel, and the reverse happens too. If your baseline came from Search results, you do not have a Gemini baseline. You have a different number.
Gemini also has its own way of showing its work. Sources sit in a panel at the bottom of a response, and inline source chips appear in the body when the assistant quotes a chunk of a page directly. Short paraphrases usually get the panel and no sentence-level footnote. So "we were used" and "we were visibly cited" are two different outcomes, and you will want to log both.
The connective tissue is grounding. Before Gemini answers, it retrieves supporting pages from Google's search index, then attaches sources to the claims that came from those pages. That is the same index that powers Search. So crawlability, indexability, entity clarity, and clean extractable structure carry across all three surfaces.
Optimize once for the fundamentals. Then test each surface separately.
One more piece of context before you start. Gemini typically cites a handful of sources per answer, often somewhere between three and eight. You are not competing for one slot. You are competing to be in a very short list, which is a friendlier game than it sounds.
Step 1: Map the prompts your buyers actually ask
Start with questions, not keywords. Everything you do to optimize for Gemini answers rests on this list being right, so give it an afternoon.
What to do. Build a working list of 30 to 80 natural-language prompts a real buyer would type into Gemini where your category could plausibly be the answer. Cluster them by intent: define, compare, troubleshoot, evaluate, buy. Then run each one in Gemini and log what you see. Which URLs got cited. Which competitors got named. Which format won, whether that was a definition, a table, a list, or a how-to.
How you know it is done. Every prompt on your list has one page on your site that could be the canonical answer, every prompt has been run at least once, and the cited URLs are recorded somewhere you can compare against next month.
Where people go wrong. They write keywords and call them prompts. "Best CRM software" is a keyword. "What is the best CRM for a ten-person SaaS sales team" is a prompt. Gemini queries skew long and conversational, so short keyword thinking produces pages that never match how anyone actually asks.
This is also the step where a tool earns its keep, because building and rerunning that list by hand gets old fast. DeepSmith's Discover Prompts generates a starter prompt set from your product, persona, and buyer-stage context, so you are editing a list instead of staring at a blank page.
Step 2: Make every target page retrievable
Gemini can only cite what it can fetch. Let's make sure it can fetch you.
What to do. For every page on your prompt map, confirm the basics. It returns a 200. It is not noindexed. It is not disallowed in robots.txt. It is not behind a login or a paywall. It sits in your XML sitemap. And the content appears in the initial HTML, not only after JavaScript runs.
Check Core Web Vitals while you are in there. The targets are Largest Contentful Paint under 2.5 seconds, Cumulative Layout Shift under 0.1, and Interaction to Next Paint under 200 milliseconds.
How you know it is done. Each URL passes the URL Inspection check in Google Search Console with "URL is on Google" and "Indexable" both true, and PageSpeed Insights is green on all three vitals.
Where people go wrong. Two ways, and both are common.
The first is blocking the wrong bots. Gemini grounds in Google's standard index, so blocking Googlebot blocks Gemini. Blocking AI-specific crawlers does not.
The second is client-side rendering. Gemini retrieves text. If your key content only exists after JavaScript executes, it does not exist for the model. Server-side rendering is not a nice-to-have here.
Common mistake: treating retrievability as a one-time check. A CDN rule, a template change, or a new consent wall can quietly break it. Re-verify after any infrastructure change.
Step 3: Engineer each page for extraction
Now the writing part. This is where most teams get the fastest lift.
What to do. Open every section with a one-sentence direct answer, then elaborate. Use question-form H2s and H3s that match how buyers phrase things. Use real HTML tables with thead and tbody for any comparison, never a screenshot of a table. Keep FAQ answers self-contained and short, roughly 30 to 60 words. Put each named statistic next to its source and date, inline, not in a footnote pile at the bottom.
How you know it is done. You can read the first sentence under any H2 out loud and it works as a complete answer without the paragraph around it. Pick three sections at random and try it.
Where people go wrong. They bury the answer in the middle of a paragraph. They hide FAQ text inside collapsible accordions that retrievers may never open. They write "studies show" instead of naming the study.
When you optimize for Gemini answers, you are optimizing for a passage, not a page. The model lifts a chunk. Your job is to make sure every chunk survives being lifted.
A quick way to feel the difference: write the definition of your core term as one clean sentence, place it directly under the heading that asks for it, and stop. No windup, no "in today's landscape." That single sentence is often the whole thing an engine takes.
Step 4: Add structured data and visible trust signals
Schema is plumbing. Useful plumbing, not magic.
What to do. Add JSON-LD for the types that match what is actually on the page: Article with author, datePublished and dateModified, FAQPage for FAQ blocks, HowTo for step-by-step content, Organization for the publisher, Person for the author. Then pair the markup with signals a human can see: a byline that links to a real credentials page, a visible last-updated date near the top, sources cited inline, and About and Contact pages linked in the footer.
How you know it is done. Your markup validates in Google's Rich Results Test with zero errors, and every article carries a byline, a credentials link, and a date a reader can see without viewing source.
Where people go wrong. They add schema that describes something the page does not contain. Schema is a description, and a false description works against you. The other trap is treating markup as the whole strategy. Comprehensive structured data is associated with meaningfully higher AI citation rates in industry analyses, but it does not overrule authority and relevance.
Here is the part that reframes a lot of Gemini AEO work. One published analysis found that the large majority of Gemini citations trace back to earned media, third-party coverage and mentions, rather than on-page markup. Schema gets you eligible. Reputation gets you picked.
That is not a reason to skip the markup. It is a reason to stop expecting it to carry the program on its own, and to budget accordingly. Google's own guidance for AI features says there is no special markup that unlocks them, so treat schema as hygiene. An afternoon on schema, then the rest of the quarter on Steps 5 and 6.
Step 5: Build entity authority and topical coverage
Gemini needs to know who you are before it can recommend you.
What to do. Pick your pillar topics and build a real cluster around each one: a comprehensive pillar page plus roughly 8 to 12 supporting pages that link back with descriptive anchor text. Then work on entity clarity. Use precise names, not generic phrases. "Asana project management software" resolves to a thing. "Project management software" resolves to a category. Claim and populate your Wikidata item, your Google Business Profile, and industry directories where you genuinely qualify.
How you know it is done. Each pillar has 8 to 12 internally linked cluster pages, and your brand and named authors show up on at least Wikidata plus one major third-party profile.
Where people go wrong. They publish islands. Twenty unconnected posts on twenty topics teach an engine nothing about what you are known for. The second mistake is bulk directory submissions. Contextual relevance beats volume, and low-quality listings do not build entity authority.
If that sounds like a lot, take it one topic at a time. Depth in one category beats thin coverage across five.
Step 6: Earn mentions on the surfaces Gemini trusts
This is the step most content teams skip, and it may be the one that moves the needle most.
What to do. Look at where Gemini already goes. Across AI engines, the same surfaces dominate cited-domain lists: Reddit, Wikipedia, YouTube, LinkedIn, Forbes, and the major trade publications in each category. So show up there for real. Participate in the subreddits where your buyers already argue about tooling. Publish short explainer videos. Put named leaders on LinkedIn with actual points of view. Give original commentary and data to trade press.
Format matters on these surfaces too. The community threads that get pulled into answers tend to be the answer-heavy ones, long on comments and first-hand experience, not the drive-by posts. The videos that get pulled tend to be how-tos and explainers, not brand films. Match the format that already wins.
How you know it is done. Your brand appears with substantive, contextually relevant mentions on at least three of those surfaces, and at least one community thread or video shows up when someone searches your brand.
Where people go wrong. Astroturfing. Buying placements, seeding fake threads, running review campaigns that read like review campaigns. Communities catch it, engines discount it, and the cleanup costs more than the lift was ever worth.
The other quiet mistake is treating these channels as broadcast. Dropping a link in a subreddit is not participation, and it reads exactly like what it is.
Watch what your competitors are earning, too. DeepSmith's competitor citation view shows which competitor pages win citations for your tracked prompts and on which platform, so your outreach targets the placements that are actually converting into citations rather than the ones that feel prestigious.
Step 7: Refresh on a 90-day cycle and re-index
Freshness decays quietly. Put it on a calendar.
What to do. Every 90 days, walk your priority pages. Update statistics, swap dated examples, add a section that answers a new prompt you have seen. Update the visible "Last updated" line and the dateModified property together, not one or the other. Add internal links from new content back to the pillar. Then re-submit each updated URL in Search Console so the crawl happens sooner rather than eventually.
How you know it is done. No priority page has gone untouched for more than 90 days, and each refresh has a matching re-index request.
Where people go wrong. Publish and forget. In fast-moving categories, recency is a real input into which source gets picked, and a page that has not moved in two years reads as stale to both the model and the reader.
A small honesty check here: bumping the date without changing the content is not a refresh. Engines and readers both notice.
Step 8: Track Google Gemini citations and iterate
You cannot improve what you only checked once.
What to do. Turn your prompt map into a standing library of 30 to 100 priority prompts. Run them on a weekly or biweekly cadence. Log which URLs got cited, which snippets got lifted, and how your share of voice compares to named competitors. Then feed the gaps back into your editorial calendar.
How you know it is done. You have a dashboard, not a spreadsheet someone updates when they remember. It reports citation rate, share of voice, top-cited URLs, and prompt-level wins and losses over time.
Where people go wrong. Checking once and treating the result as durable. Google Gemini citations move. One published study tracked Gemini's citation usage dropping by roughly 23 percentage points across a single month in early 2026, as the assistant shifted toward more synthesized answers. A single snapshot would have told you nothing about that.
Give it time before you judge. After a page is crawled and re-ranked, citation patterns usually take a few weeks to settle, so run tracking for six to eight weeks before drawing conclusions.
One caution while you score. Reporting on AI search engines has found that a large share of AI citations are inaccurate in some way, including sources attributed loosely or incorrectly. Read your Gemini AEO data as directional, not as a ledger. The trend line over a fixed prompt set is trustworthy. Any single answer is not.
Doing this by hand across five engines is where most programs quietly die. DeepSmith runs your tracked prompts on a schedule and reports mention rate, citation rate, and share of voice per platform, with a competitor leaderboard and the pages of yours that AI actually cites. Gemini coverage comes in on the Scale plan at $399 a month, or $299 a month billed annually. The same platform then produces the pages to close the gaps it found, so the tracking and the writing are not two separate projects.
What to do next
Do not try to run all eight steps this month. You will stall.
Pick the one gate you are most likely failing. If you are not sure your pages are even retrievable, start at Step 2. If they are indexed but ignored, start at Step 3. If your content is clean but nobody outside your own domain talks about you, start at Step 6.
Then run 10 prompts in Gemini and write down what you see. That is your baseline, and it takes about 20 minutes.
Most plans to get brand into Gemini fail on sequencing, not on tactics. People start with schema because it feels productive, then wonder why nothing moved. Retrievability first, extraction second, reputation third, measurement running underneath all of it.
If you would rather see the whole picture before you pick, start a DeepSmith free trial and let the platform baseline your prompts, your citations, and your competitors first. Seven days, real data, no contract.
You are closer than the checklist makes it look. Take the next step, not all of them.
