How to Track AI Visibility in Semrush Over Time

AI visibility tracking gets messy fast if you treat it like regular rank tracking. Prompts shift, platforms answer differently, and one loose setup can leave you staring at charts that look busy but say nothing. Here’s how to track AI visibility in Semrush over time in a way that stays clean, useful, and easy to act on.

What you’ll need before you start #

A little prep saves a lot of cleanup later. Think of this like labeling moving boxes before you carry them upstairs. You only want to do it once.

Access to Semrush AI Visibility and Prompt Intelligence #

Start inside the Semrush area that includes AI Visibility and Prompt Intelligence. AI Visibility is where ongoing monitoring lives, and Prompt Intelligence is where prompt research helps you figure out what is actually worth tracking. That split matters. Research helps you build the right list, and tracking shows what changes over time.

Before touching any settings, make sure you’re working in the correct Semrush account and project area. If your team manages multiple brands, one wrong project can mix data for completely different businesses. That gets confusing fast.

A short list of brands, products, and competitors #

Write down the exact names you want to monitor before you begin. Include your main brand name, product names, key service lines, and a handful of direct competitors. Keep it short and practical.

This list helps in two ways. First, it gives you reference terms to watch for in AI-generated answers. Second, it keeps you honest when evaluating visibility. If a competitor keeps showing up under one product category, you want that noted from the start instead of realizing it three weeks later.

Core topics and prompt ideas tied to your business #

Next, sketch out the topics your audience already cares about. Pricing, comparisons, alternatives, recommendations, integrations, use cases, and category questions are usually the best place to start. For a SaaS brand, that might mean prompts like “best CRM for small sales teams” or “HubSpot alternatives for startups.” For ecommerce, it could be “best running shoes for flat feet” or “eco-friendly bedding brands.”

The trick is to start from real buying behavior, not clever wording. Prompts should sound like something a customer would actually type into ChatGPT, Google AI, Gemini, or Perplexity at 8:17 a.m. while trying to solve a problem before a meeting.

A place to log changes and takeaways #

Set up a spreadsheet, document, or note inside your reporting dashboard where you can record changes over time. You do not need a fancy system. A simple table with the date, prompt group, visibility change, major competitor movement, and content changes is enough.

That log becomes surprisingly useful later. When visibility moves, you need a place to connect that shift to something real, like a comparison page update or a new product landing page.

Step 1: Open AI Visibility and choose the right project #

The goal here is simple: start in the correct workspace so your tracking data stays organized from day one.

Create or select your project #

1. Log in to Semrush and open the AI Visibility area.
2. Choose an existing project for the domain or brand you want to monitor, or create a new project if one does not exist yet.
3. Name the project clearly, especially if your account includes multiple regions, product lines, or clients.
4. Check that the domain and brand match the visibility you want to measure.
5. Save the project before moving on.

A clean project structure matters more than it seems. If your B2B product and consumer product live in the same account, mixing prompts between them will blur the results and make reporting harder.

Confirm your market, device, and location settings #

1. Open the project settings for your AI Visibility setup.
2. Select the correct country and language.
3. Review any device or targeting settings available in the workflow.
4. Match those settings to the market you actually care about tracking.
5. Save your selections and verify them one more time.

AI answers can vary by market and context, so this step is not just administrative. If your audience is in the United States and your settings point elsewhere, your trendline may be accurate for the wrong reality.

Checkpoint: after saving, your project should reflect the exact brand, domain, country, and language you plan to report on later.

Step 2: Research the prompts worth tracking #

This is where most setups go wrong. Random prompt lists create random insights.

Start with seed topics from your products and services #

1. Open Prompt Intelligence or Prompt Research inside Semrush.
2. Enter broad seed topics tied to your products, services, or editorial areas.
3. Review the related prompts Semrush surfaces from those seeds.
4. Export or save the prompts that clearly match your market.
5. Repeat this process for each major product or topic cluster.

Start broad on purpose. You want Semrush to surface real prompt variations you may not have thought of, instead of locking yourself into your own assumptions.

Look for commercial and high-intent prompt patterns #

1. Scan the prompt list for comparison and buying language.
2. Flag prompts with terms like “best,” “top,” “vs,” “alternative,” “software,” “tool,” “platform,” or “for [use case].”
3. Save the prompts that signal decision-making or vendor evaluation.
4. Separate these from general educational prompts.
5. Keep a note of which categories appear most often.

High-intent prompts usually deserve priority because they connect more directly to revenue. If somebody asks for “best project management software for remote design teams,” that is a lot closer to action than a broad question about productivity.

Review informational prompts that shape discovery #

1. Return to your research list and scan for awareness-stage prompts.
2. Save educational prompts that influence category discovery.
3. Keep prompts tied to definitions, workflows, beginner questions, and problem framing.
4. Group these separately from commercial prompts.
5. Mark long research-cycle topics for ongoing observation.

Informational prompts still matter, especially in B2B, SaaS, and publisher spaces where buyers do research long before a purchase. If your brand is absent from those early conversations, you may never make the shortlist later.

Filter out prompts that don’t match your audience #

1. Review the saved prompt list one more time.
2. Remove prompts with weak relevance, off-topic intent, or vague wording.
3. Delete prompts that would never lead to meaningful attention, traffic, or conversions.
4. Cut duplicates and near-duplicates unless the wording changes the intent.
5. Keep only prompts you would care about in a monthly report.

The catch is that more prompts do not mean better AI visibility tracking. A smaller list of useful prompts beats a giant junk drawer every time.

Step 3: Build a focused prompt tracking list #

Now you turn research into something manageable.

Group prompts by topic or funnel stage #

1. Create categories for awareness, comparison, purchase intent, and product-specific use cases.
2. Assign each prompt to one category.
3. Keep categories consistent across teams and reports.
4. Add notes where a prompt could fit more than one stage.
5. Save the grouped list for import or manual setup.

This makes trend reading much easier later. If visibility jumps in comparison prompts but stays flat in awareness prompts, that tells a clearer story than one blended total.

Prioritize prompts by business value #

1. Rank each prompt by relevance to your offers.
2. Weigh intent more heavily than sheer prompt volume.
3. Move prompts tied to high-value products or services toward the top.
4. Keep a smaller core set for your main dashboard.
5. Put lower-priority prompts in a secondary list for later expansion.

A prompt can be niche and still matter more than a broad category phrase. If it reflects real buying behavior, keep it close.

Balance broad prompts with niche prompts #

1. Choose a handful of category-level prompts.
2. Add a matching set of narrower use-case prompts.
3. Make sure both branded and non-branded opportunities are represented.
4. Avoid loading the list with only huge, generic prompts.
5. Save the balanced set as your starting tracking list.

Broad prompts show your overall presence. Niche prompts often reveal faster opportunities because the competition is narrower and the intent is clearer.

Step 4: Add prompts to tracking in Semrush #

This is the handoff from planning to live monitoring.

Add prompts manually or from your research list #

1. Open the tracking setup inside AI Visibility.
2. Import prompts from your saved research list, or add them manually.
3. Use consistent naming for prompt groups and tags.
4. Double-check spelling and wording before saving.
5. Confirm the final list inside the tracking view.

Small wording differences can matter. “Best CRM for freelancers” and “best CRM for small agencies” are close, but not interchangeable.

Choose the AI platforms to monitor #

1. Select the AI engines that matter to your audience.
2. Include platforms such as ChatGPT, Google AI, Gemini, or Perplexity where available in your setup.
3. Keep your platform list consistent across reporting periods.
4. Add more platforms only if you have a clear reason to compare them.
5. Save the platform configuration.

Different engines can surface different brands for the same prompt. That is normal. In fact, Zapier’s review of AI visibility tools highlights cross-platform monitoring as one of the main differences between AI visibility products, which is a useful reminder that platform comparison is part of the job, not a bonus feature.

Save prompt groups for easier reporting #

1. Create tags, folders, or groups for each prompt cluster.
2. Separate groups by funnel stage, product line, campaign, or region.
3. Keep naming short and obvious.
4. Review the group structure before finalizing.
5. Save everything so future reports stay clean.

Checkpoint: after setup, you should be able to filter your tracked prompts by meaningful groups without guessing what belongs where.

Step 5: Set your baseline before making changes #

Do this before updating pages. Otherwise, you will not know what actually improved.

Record current visibility by prompt and platform #

1. Review your current visibility results across the tracked prompt set.
2. Note where your brand appears and where it does not.
3. Record the platform tied to each result.
4. Save a baseline snapshot in your spreadsheet or report doc.
5. Date the baseline clearly.

This is your before photo. Without it, later gains are just vibes.

Check which competitors appear most often #

1. Look across the same prompt set for recurring competitor brands.
2. Count which brands show up most often by prompt group.
3. Note any competitor dominance within a topic cluster.
4. Record those names in your baseline sheet.
5. Flag direct competitors that appear where your brand is absent.

Sometimes the biggest surprise is not who beats you, but where you are not even in the conversation.

Save examples of AI-generated mentions #

1. Open several AI answers tied to your tracked prompts.
2. Save examples where your brand is mentioned.
3. Save examples where a competitor is mentioned instead.
4. Save examples where neither appears.
5. Add notes about tone, framing, and cited sources if visible.

These snapshots help you spot patterns later. A brand recommendation in a short list feels different from a detailed explanation that names your product for a specific use case.

Step 6: Review the visibility metrics that matter #

Not every chart deserves your attention.

Visibility share and brand presence #

Focus first on how often your brand appears across your tracked prompt set. That is your top-level pulse check. If that share climbs over time, your AI visibility tracking is catching real movement.

But do not stop at one aggregate number. A healthy top-line trend can hide weak spots in product-specific or high-intent prompts.

Prompt-level changes over time #

Look at individual prompts or prompt groups across each reporting period. One cluster often moves before the overall average does. If your comparison prompts improve right after a product page rewrite, that is a useful signal. If awareness prompts drop across one platform, that matters too.

Prompt-level review is where strategy gets practical. It shows what changed, not just that something changed.

Competitor overlap and gap areas #

Compare your tracked prompts against the competitors that appear most often. You want to know where both brands are present, where only competitors show up, and where nobody has a clear lead.

Gaps are especially useful. If competitors appear repeatedly for “best payroll software for contractors” and your brand never does, that is not just a reporting note. It is a content opportunity.

Mention quality and context #

A mention is not automatically a win. You need to check how your brand appears. Is it the featured recommendation, one item in a crowded list, or a passing reference with weak context?

Quality matters because AI systems frame brands differently. A clear recommendation tied to a use case is stronger than a name dropped without explanation.

Step 7: Compare performance across AI platforms #

One of the fastest ways to miss useful insight is to blend all AI engines into one number.

Spot prompts that perform differently by engine #

Review the same prompt across each platform you track. If your brand appears in ChatGPT but not in Google AI, or shows up in Perplexity but not Gemini, pay attention to that gap.

Here’s where it gets interesting: those differences often point to content format, topical authority, or citation patterns rather than random variation.

Identify platform-specific strengths #

Find the topics where your brand already performs well on a specific engine. Then look for the pages or content types connected to those prompts. Maybe your glossary pages show up more often in one platform, while comparison pages perform better in another.

Those wins are useful templates. If a format works, expand it.

Flag platform-specific blind spots #

Mark the prompts where competitors appear consistently and your brand does not on a given platform. Keep these grouped by topic so the pattern is easier to see.

This creates a short list of practical fixes. Instead of “improve AI visibility,” you get something concrete like “strengthen comparison content for Gemini in finance prompts.”

Step 8: Find the content opportunities behind the data #

This is where the dashboard starts paying rent.

Match missing prompts to existing content #

Start by checking whether you already have pages that should support the missing prompts. If the page exists but visibility is weak, the issue may be clarity, structure, terminology, or thin coverage of the topic.

Sometimes the fix is surprisingly small. A better heading, a clearer explanation, or a stronger comparison section can make a page easier for AI systems to interpret.

Create new content for prompt gaps #

When there is no matching page, create one. Build comparison articles, use-case pages, FAQ hubs, pricing explainers, or category guides based on the missing prompt themes.

Focus on obvious holes first. If your brand wants visibility for alternatives or product comparisons and you have no content there, that is a bigger problem than polishing a decent page into a slightly better page.

Strengthen brand and entity signals #

Make your brand easier to understand across your site. Use consistent product names, clear descriptions, and supporting pages that explain what you do, who it is for, and how your offers differ.

That consistency helps AI systems connect your brand to the right topics. Think of it like putting labels on storage bins instead of tossing everything into a closet and hoping you find it later.

Use competitor mentions as content clues #

Study the kinds of pages and angles tied to competitor visibility. If competing brands keep appearing in prompts around onboarding, integrations, or industry-specific use cases, look at whether your content covers those angles clearly enough.

The trick is not to copy. It is to notice what your site leaves unsaid.

Step 9: Set a review cadence for tracking over time #

Tracking only works if you revisit it on purpose.

Run weekly checks for movement #

Use weekly reviews to catch fast changes, especially after publishing or updating content. Look for sudden gains, visibility drops, or new prompt winners within a cluster.

Keep these checks light. You are scanning for movement, not rebuilding strategy every Friday.

Use monthly reviews for bigger trends #

Monthly reviews are where you judge direction. Short-term changes can be noisy, but a month of data shows whether your visibility is actually improving.

This is also the right time to compare groups, platforms, and competitors in one view. Patterns are easier to trust when they repeat.

Annotate major content or site changes #

Add notes whenever you publish a new page, refresh a comparison article, change pricing content, launch a product, or migrate site sections. A simple note with the date and change is enough.

Those annotations save a lot of head-scratching later. If visibility improved right after a “Tuesday at 9 a.m. pricing page rewrite,” you want that documented.

Step 10: Turn tracking insights into optimization tasks #

Reporting alone does not change visibility. Tasks do.

Prioritize quick wins first #

Start with prompt clusters where your brand already appears sometimes but not consistently. Those are often easier to improve than prompts where you have zero presence and no supporting content.

Quick wins usually come from page refreshes, clearer structure, stronger comparisons, or better FAQ coverage. Small fixes can move faster than full rebuilds.

Assign updates by page, prompt cluster, or owner #

Turn each insight into a real task with a clear owner. Tie it to a page, a topic group, or a person. “Improve AI visibility” is too vague to survive a busy week. “Refresh /crm-alternatives page for comparison prompts” is much better.

This keeps your findings from getting trapped in a report nobody opens again.

Recheck tracked prompts after updates #

After updates go live, return to the same tracked prompts and compare the results against your baseline. Watch for movement by platform and by prompt cluster.

Checkpoint: success here looks like a tighter loop between changes made and visibility shifts observed. If you cannot connect action to outcome, the setup still needs work.

Step 11: Build simple reports for clients or stakeholders #

Most stakeholders do not want a dashboard tour. They want the story.

Highlight changes in visibility, not just raw data #

Lead with movement. Show what improved, what dropped, and where your biggest opportunities now sit. A short trend narrative is easier to absorb than a table full of disconnected numbers.

Keep the report focused on change over time. That is the whole point of tracking.

Include prompt examples and competitor context #

Use a few real prompt examples to make the data concrete. Add the competitor names that appear most often in those same prompts so the context is obvious.

This works better than abstract percentages alone. Seeing the actual prompt makes the opportunity feel real.

Tie AI visibility to content decisions #

Connect every major finding to an action. If a prompt gap points to a missing comparison page, say that. If a visibility gain followed a content refresh, note it.

That is what turns AI visibility tracking from an interesting metric into something useful for planning and prioritization.

Troubleshooting common AI visibility tracking issues #

A few problems show up again and again. Most are fixable without rebuilding everything.

You’re tracking too many prompts #

If your list feels bloated, cut it down. Keep the prompts tied most closely to your goals, products, and customer intent. A shorter list is easier to review, easier to explain, and usually more useful.

Your prompts are too broad or too vague #

Vague prompts create vague insights. Tighten the language around actual user intent. Swap giant category questions for more specific use cases, comparisons, or buyer-oriented phrasing.

Specific prompts tend to produce cleaner patterns over time.

Visibility is low and there’s no clear pattern #

If your brand rarely appears, take that at face value. Low visibility usually points to a real content or positioning gap. Review whether your pages directly answer the tracked themes, and check whether your brand and product descriptions stay consistent across the site.

Thin visibility is not a dashboard problem most of the time. It is a content signal.

Platform results don’t match each other #

Different engines often tell different stories. That is normal. Compare the prompt types, content formats, and citation tendencies involved instead of trying to force one unified explanation.

The mismatch is often the clue. It can show where your content connects better with one engine than another.

You can’t tell whether changes are meaningful #

If week-to-week movement looks random, zoom out. Compare monthly patterns, not isolated bumps, and line those patterns up with your update log.

Meaningful change usually repeats. Noise usually does not.

What success looks like and what to do next #

Once this setup is running, you should have a much clearer picture of where your brand shows up, which prompts matter most, and where competitors keep taking space in AI answers. That clarity makes content planning faster and less fuzzy.

Expected outcomes from consistent tracking #

Consistent tracking should give you three things: a reliable baseline, a shortlist of prompt gaps worth fixing, and a better sense of which platforms respond to your content strongest. That is enough to make smarter decisions without drowning in data.

Over time, you should also notice something else. Content work gets easier to prioritize because prompt-level evidence replaces guesswork.

Your next move: track one high-value prompt cluster #

Start with one focused, high-intent prompt group and monitor it for a few weeks before expanding. That could be alternatives, comparisons, or a core use-case cluster tied directly to revenue. Keep it small, watch it closely, and let the first results show you where to go next.