How to run an AI-assisted SEO competitor analysis that actually works

Now you can do in 20 minutes what used to take a full afternoon. Feed two Semrush exports into Claude or ChatGPT, and also you’ll get a cultured competitor evaluation – full with matter clusters, hole tables, and prioritized briefs.

The output appears convincing. The tables are clear. The suggestions sound assured.

That’s the issue. AI can arrange and summarize information shortly, however it may possibly’t make strategic selections. With out the best workflow, prompts, and validation, you threat appearing on insights that sound correct however lack depth.

Used accurately, although, AI can floor significant patterns – revealing variations in topical depth, content material protection, and authority alerts that affect search visibility.

Right here’s a walkthrough of an actual two-competitor evaluation utilizing Claude and Semrush information, exhibiting find out how to flip quick AI outputs right into a dependable technique. You’ll get a repeatable workflow, examined prompts, and a validation guidelines to catch frequent errors, together with a transparent sense of the place to belief AI — and the place to depend on your judgment.

AI received’t run a competitor evaluation for you. However it may possibly compress the guide work — clustering, sample matching, and synthesis — so you possibly can deal with deciphering intent, validating alternatives, and deciding what’s price pursuing.

Word: The websites on this evaluation are actual however anonymized. Web site Y is our shopper, whereas Rivals A and B are direct opponents in the identical area of interest. The information is from actual Semrush exports pulled in early 2026.

Begin with information, not a immediate

At any time when potential, begin by exporting information out of your website positioning instrument. Don’t ask an AI assistant to guess what an website positioning instrument can inform you.

In any other case, you assume your AI assistant is a measurement instrument. Though it isn’t, it’ll attempt its greatest to reply to your request. This typically appears like plausible-sounding visitors estimates, key phrase lists, and aggressive assessments which are partially or fully fabricated.

Right here’s what we exported and why each bit issues.

Export 1: Natural Analysis > Pages (high 100 by estimated visitors)

This report tells you which of them pages are profitable. Key columns embody the URL, estimated visitors per web page, variety of rating key phrases per web page, the intent breakdown (business, informational, navigational, transactional), and the visitors change column that exhibits momentum.

For instance, a web page pulling 14,500 visits from 1,632 key phrases is a special asset from a web page pulling 400 visits from 12 key phrases. The intent break up tells you why that visitors issues.

Export 2: Natural Analysis > Positions (high 100 key phrases by visitors)

This export tells you which of them key phrases are profitable. Key columns listed below are key phrase and place, search quantity, keyword difficulty , search engine outcomes web page (SERP) options (picture packs, video carousels, and Individuals Additionally Ask), and key phrase intent tags.

As a substitute of telling you which of them URLs carry out greatest, this report reveals which search queries drive probably the most visitors. You want each studies for a whole image.

The export guidelines 

For every competitor and to your personal web site, pull:

• Semrush Natural Analysis > Pages, high 50-100, sorted by visitors.
• Semrush Natural Analysis > Positions, high 100-500, sorted by visitors.
• Semrush Key phrase Hole report (non-compulsory).
• Screaming Frog crawl with URLs, titles, H1s, phrase depend, crawl depth, and inner hyperlinks. This non-compulsory report provides structural context (like how deep pages are buried within the web site structure) that the Semrush exports don’t embody.

Conduct a 20-minute aggressive evaluate

Subsequent, feed your exports into your AI assistant. Ask it to do three issues: classify, cluster, and evaluate.

Subject taxonomy (per web site)

Right here’s the immediate I used:

I will provide you with a Semrush Natural Pages export for a web site. Every row is a URL with its estimated natural visitors, variety of rating key phrases, and intent breakdown.

Please:
1. Assign every URL to a subject class (e.g., "Product - Roof Racks," "Editorial - Shopping for Guides," "Assist - Technical," "Class - Stock")
2. Assign a web page kind: Homepage, Product Web page, Class Web page, Editorial/Information, Weblog Put up, Assist/Data, Touchdown Web page, or Different
3. Create a abstract desk exhibiting: matter class, variety of pages, complete visitors, and dominant intent

Guidelines:
- Base classifications on the URL path and any context out there. Do NOT guess visitors numbers or key phrase information. Use solely what's within the export.
- If a URL is ambiguous, flag it as "wants guide evaluate" somewhat than guessing.
- Group comparable matters (e.g., do not create separate classes for "off-road equipment" and "off-road bumper kits." Cluster them).
- After classifying, record any URLs the place you are lower than 80% assured within the classification. I am going to confirm these manually.

This is the info:
[PASTE PAGES EXPORT]

For Web site Y, Claude recognized seven matter clusters throughout 100 pages. Right here’s the abstract:

Even earlier than evaluating opponents, this taxonomy tells a narrative. Our shopper’s natural visitors is pushed extra by editorial content material (shopping for guides and comparisons) than by all product pages mixed.

The truth is, a single shopping for information pulled 7,336 visits by itself, and the highest product web page drove 5,021. That editorial power is each a strategic asset and a vulnerability, since editorial rankings might be extra unstable than product web page rankings.

Competitor comparability

When you’ve created a taxonomy for every web site, use this immediate to check them:

I now have matter taxonomies for 3 competing websites in the identical area of interest. I will provide the abstract tables for all three.

Please:
1. Construct a comparability desk exhibiting how every web site's visitors distributes throughout matter classes
2. Establish every web site's "content material technique signature": what kind of content material drives the vast majority of their natural visitors
3. Flag any classes the place one web site dominates and the others are weak or absent
4. Word the visitors focus: what proportion of every web site's complete visitors comes from their high 3 pages

Guidelines:
- Use solely the info supplied. Don't estimate or infer visitors for classes not current in a web site's export.
- If a class does not exist for a web site, mark it "Not current" somewhat than zero. We do not know if they've content material there, solely that it does not seem of their high 100.

Web site Y taxonomy:
[PASTE]

Competitor A taxonomy:
[PASTE]

Competitor B taxonomy:
[PASTE]

Once we used this immediate, Claude revealed three fully totally different methods from the identical area of interest.

Manually growing this comparability might require hours of spreadsheet work between categorizing 300 URLs, constructing pivot tables, and attempting to identify patterns throughout three tabs. However Claude did it in minutes.

The sample recognition alone (three fully totally different methods from three websites promoting in the identical market) is genuinely invaluable output.

The numbers present that Web site Y pulls 5 instances the natural visitors of Competitor A and thrice that of Competitor B, regardless of all three competing in the identical area.

Competitor A’s second-highest visitors web page is a bolt sample information on a assist subdomain. Competitor B is shedding floor quick, with its high class web page dropping by 1,184 visits.

In case you’re operating a aggressive evaluation and also you don’t spot patterns like these, you’re lacking the strategic story behind the info.

Apply human judgment

In case you had been to cease after producing the clusters and comparability chart, you’d have a plausible-looking aggressive evaluation. However the AI-generated output wants human intervention earlier than you make any strategic selections.

Examine the classifications

Spot-check 10-15% of classifications by visiting the URLs. Appropriate the taxonomy, after which re-run the comparability. This turns an 85% correct first draft into one with 95% or larger accuracy.

The “confidence flag” line within the immediate (“record any URLs the place you’re lower than 80% assured”) saves you from having to guess which of them to verify. In case you skip this step, the misclassifications can distort your complete aggressive profile.

For instance, once I checked Claude’s web page classifications towards the precise dwell pages, roughly 15% wanted correction. It tagged a product comparability web page as a weblog publish. It labeled a regional touchdown web page as a class web page. And it lumped an FAQ web page into the “Different” class though it served as the location’s main purchaser’s information for a particular product line.

These misclassifications had been the sort of unintentional calls that come from categorizing URLs by path construction alone, with out seeing the web page content material. For instance, if a URL path says /weblog/best-off-road-accessories/, AI assistants will name it a weblog publish even when the web page capabilities as a business comparability information.

Take into account the intent

AI assistants can floor information factors in seconds, however they will’t make strategic requires you. Decoding the info requires understanding your shopper’s enterprise mannequin, their authority degree, and their content material capability.

I’ve seen groups burn a whole content material dash on high-volume informational key phrases that drove loads of visitors and 0 leads. If the intent doesn’t match your corporation objectives, the amount is irrelevant.

For instance, Competitor A’s second-highest-traffic web page is a bolt sample lookup information, pulling 1,245 visits per 30 days. Claude flagged this as a content material technique hole for Web site Y, since our shopper had no equal utility content material.

Whereas that is technically right, it’s strategically deceptive. The bolt sample information targets purely informational intent. So, the web page builds authority and earns hyperlinks, but it surely’s not a business driver.

Whereas it may be useful to create utility content material like this, it ought to be a gentle background effort, not a precedence dash. The commercially related gaps (product classes, shopping for guides) come first.

Use this immediate repair:

For every alternative you flag, verify the intent breakdown from the Semrush information. 
If greater than 60% of the visitors is informational or navigational intent, flag it individually as "authority builder, not direct conversion driver" so I can prioritize accordingly.

Evaluate the SERP actuality vs. the rating place

AI assistants work from the place numbers and quantity information in your website positioning studies. They don’t know what the SERP appears like.

For instance, Claude noticed that Web site Y ranks Place 3 for “off-road roof rack” (22,200 month-to-month searches, driving 1,443 visits) and handled it as an easy optimization alternative. Push the web page to place one, and seize extra visitors. Easy.

However in actuality, the SERP is filled with wealthy options: in style merchandise, a picture pack, and Individuals Additionally Ask. The normal natural blue hyperlinks seem barely above the fold on desktop and nicely beneath the fold on cellular.

Rating in place one seemingly wouldn’t ship the visitors enhance you’d usually anticipate from a 22,200-volume key phrase as a result of the SERP options soak up a lot of the clicks.

In your high 5 or 10 precedence key phrases, do a guide SERP verify. If the web page is dominated by procuring carousels and video outcomes, then a standard natural push might not be the best play. As a substitute, a product feed optimization or video content material technique may be more practical.

Do a spot evaluation

Your website positioning instrument already has a key phrase hole report. However a uncooked record of lacking key phrases isn’t a method.

Use it as a place to begin. Then, let AI clusteri these gaps into themes, tiering them by intent and enterprise relevance and turning uncooked hole information into prioritized actions.

Begin with the instrument information

We pulled two Semrush Key phrase Hole studies evaluating Web site Y towards each opponents. They revealed:

• Lacking key phrases: 217 key phrases the place each opponents rank and Web site Y doesn’t seem in any respect. Mixed search quantity ~49,700/month.
• Weak key phrases: 106 key phrases the place Web site Y ranks however will get outperformed by each opponents. Mixed search quantity: ~33,650/month.

Feed the hole information to AI

Use this immediate together with your AI assistant:

I will provide you with two Semrush Key phrase Hole studies:
1. MISSING: key phrases the place each opponents rank and Web site Y does not
2. WEAK: key phrases the place Web site Y ranks however opponents outrank us

Every row consists of: key phrase, intent tags, search quantity, key phrase issue, CPC, and the rating place for every web site.

Please:
1. Cluster the key phrases into thematic teams (e.g., "bumpers," "roof racks," "overlanding gear," "gentle bar kits," "torque specs/fitment"). A key phrase can solely belong to 1 cluster.
2. For every cluster, present: variety of key phrases, complete search quantity, dominant intent, and common key phrase issue.
3. Separate the clusters into tiers primarily based on intent:
  - Tier 1 (Commercially related): Clusters with predominantly business or transactional intent that align with the location's core product/service providing
  - Tier 2 (Adjoining business): Clusters which are commercially related to the broader market however might not be the location's main product focus
  - Tier 3 (Authority builders): Clusters with primarily informational or navigational intent that construct topical authority however are unlikely to drive direct conversions
  Word: I'll evaluate the tier assignments and regulate primarily based on enterprise mannequin match. AI ought to make its greatest guess and flag any clusters the place the tier task is unsure.
4. Inside every tier, kind by mixed search quantity
5. Flag any key phrases which are branded competitor phrases (e.g., a competitor's product or model title). These are typically not pursuable gaps
6. For the WEAK key phrases, separate into "shut wins" (Web site Y in positions 1-10) vs. "lengthy photographs" (Web site Y in positions 50+)

Guidelines:
- Use ONLY the key phrases in these exports. Don't recommend key phrases not current within the information.
- If intent information is lacking or ambiguous, mark it "confirm manually" somewhat than guessing.
- Don't invent search quantity or rating information. If a subject is empty, say "not out there."

MISSING key phrases:
[PASTE]

WEAK key phrases:
[PASTE]

Once we used this immediate with Claude, clear thematic clusters emerged from the 217 lacking key phrases:

Appropriate AI’s priorities

This step determines the place you spend the subsequent quarter’s content material funds, so human judgment is crucial.

In case you let an AI assistant set your content material priorities primarily based purely on search quantity and intent labels, you’ll find yourself chasing another person’s market as a substitute of dominating your individual. Quantity is seductive, however enterprise alignment is what drives income.

For instance, Claude clustered 323 key phrases and tiered them by intent in minutes. However it assigned bumpers/skid plates (~12,000/month quantity) the identical precedence as overlanding gear (~2,800/month) as a result of it doesn’t know what Web site Y sells.

With out our human override, we might have constructed our content material calendar across the flawed cluster.

Establish small pushes that make large variations

Subsequent, discover the low-effort alternatives with the most important payoffs.

For instance, from 106 weak key phrases, we separated 17 shut wins the place Web site Y already ranks in positions one by 10. These have actual potential:

Web site Y sits at place three throughout nearly each “overlanding” variant, whereas Competitor A holds place one. These are optimization alternatives. A targeted push towards higher on-page focusing on, inner linking changes, and content material updates incorporating “overlanding” language extra explicitly might flip a number of of those to place one or two.

That’s a special motion than writing a brand new web page. Claude would have defaulted to the latter if we hadn’t break up the info into shut wins and lengthy photographs.

Think about authority context

As a closing validation step, pull the backlink profiles to your opponents.

Once we did this, we discovered that each had comparatively skinny hyperlink profiles. Competitor B had 199 backlinks with a median web page authority rating of simply 1.1 (on Semrush’s 0-100 scale), whereas Competitor A had 128 backlinks, averaging a 3.1 authority rating. The best high quality hyperlinks for each got here from the identical handful of overlanding and off-road car publications.

Essentially the most-linked pages and the highest natural pages barely overlapped for both competitor. Solely the homepages appeared in each lists.

Competitor B’s high backlinks pointed to product pages, whereas its high natural visitors got here from class pages. Competitor A’s greatest hyperlinks got here from editorial options, whereas their natural visitors was dominated by the homepage and a assist web page.

This tells us their natural rankings are pushed extra by topical relevance and on-page website positioning than by direct hyperlink fairness to particular person pages. It means the key phrase gaps we recognized are seemingly winnable by content material and optimization somewhat than requiring a significant hyperlink constructing marketing campaign.

Flip the hole evaluation into a quick

Use your competitor evaluation to draft a content material transient with AI. Enter this immediate:

Based mostly on the hole evaluation we ran, [DESCRIBE PRIORITY CLUSTER] emerged as a precedence. Draft a content material transient for optimizing the present presence and/or creating a brand new web page to seize this cluster.

Embrace:
1. Main and secondary goal key phrases (from our information solely)
2. Advisable web page kind and format (primarily based on what's at the moment rating for these phrases)
3. Content material construction with prompt H2s
4. Content material components the rating opponents embody that our web page ought to match or exceed
5. Estimated phrase depend vary primarily based on competing content material

Then, in a separate part known as "Differentiation: For Human Evaluate," recommend 3 potential angles that will make this web page genuinely totally different from what already ranks. These are recommendations for me to judge, not closing selections.

Earlier than finalizing the transient, cross-reference the goal key phrases towards Web site Y's current pages export. Flag any current pages that already rank for or goal comparable key phrases. These are potential cannibalization dangers that should be resolved earlier than creating new content material.

Guidelines:
- Don't fabricate competitor content material particulars. Base factor suggestions on what we all know from our information (URLs, web page varieties, key phrase footprints)
- In case you want data you do not have (e.g., precise competitor web page content material), say "guide evaluate wanted: [specific thing to check]" somewhat than guessing

From this immediate, Claude drafted a clear transient with goal key phrases from our information, really useful format (long-form information with product integration), and an H2 construction.

It additionally carried out a cannibalization verify. As a result of we added a cross-reference line to the immediate, Claude flagged that Web site Y already had a associated web page pulling 838 visits. If we’d created a brand new web page with out checking, it could have competed with the present web page. That one line within the immediate saved us from pointless inner competitors.

However the differentiation part wanted human enter. Solely somebody who is aware of Web site Y’s model voice and buyer objections might choose the best angle from these prompt choices:

• First-hand testing and evaluate angle: Web site Y installs and checks these merchandise, to allow them to present actual utilization by way of path checks, set up photographs, and buyer experiences.
• Comparability angle: What’s the distinction between overlanding versus off-road? This straight addresses the key phrase overlap we seen within the hole information.
• Purchaser qualification angle: Who wants overlanding gear versus who could be wonderful with customary off-road equipment?

The expertise alerts (precise path checks, buyer tales, set up particulars) additionally want substantial human oversight. That is the place Google’s emphasis on expertise, experience, authoritativeness, and trustworthiness meets sensible execution. In case you don’t have real first-hand expertise to attract on, no quantity of key phrase optimization will shut that hole.

Run by a validation guidelines

Earlier than you act on any AI-assisted competitor evaluation, undergo this guidelines to stop the commonest errors.

Information validation

• Base all evaluation on instrument exports (Semrush, Ahrefs, Screaming Frog), not AI-generated estimates.
• Examine for export dates (if information is older than 90 days, current algorithm updates or market shifts might have modified the image).
• Use a significant pattern measurement (high 50+ pages per competitor, not simply high 10).
• Embrace each Pages and Positions exports.

Classification validation

• Spot-check 10-15% of the AI assistant’s web page kind and matter classifications towards dwell pages.
• Appropriate any misclassifications and re-run the comparability.
• Examine whether or not AI created overly granular or overly broad classes.
• Confirm that pages on subdomains or uncommon URL constructions had been labeled accurately.

Intent validation

• Examine intent tags (not simply search quantity) on all flagged alternatives.
• Separate commercially related gaps from informational and authority-building gaps.
• Confirm intent interpretation with a guide SERP verify in your high three to 5 precedence key phrases.
• Make a aware resolution to pursue, defer, or skip high-volume informational key phrases.

Prioritization validation

• Verify your AI assistant’s precedence rating aligns with your corporation objectives, not simply search quantity.
• Examine whether or not the services or products matches what you promote if a cluster appears like tier one primarily based on quantity alone.
• Decide if alternatives are achievable given web site authority and content material sources.
• Verify no alternatives are branded competitor phrases you possibly can’t realistically win.
• Examine whether or not a spot is healthier addressed by optimizing current content material versus creating new content material.

Temporary validation

• Select a differentiation angle for AI-generated briefs (not simply key phrases and construction).
• Confirm the really useful content material format matches what ranks in SERPs.
• Verify the transient doesn’t goal key phrases that your individual web site already ranks for.
• Establish E-E-A-T alerts and decide what unique content material the web page wants that AI can’t generate.

The shift to AI-assisted website positioning competitor evaluation

AI instruments have modified the place you spend your time when conducting a competitor evaluation. The information gathering, clustering, cross-referencing, and preliminary synthesis that used to eat most of your time? AI handles that effectively.

As a substitute, AI assistants unlock pondering time. Now, you possibly can spend that point on the components that decide whether or not your evaluation results in outcomes: deciphering intent, validating classifications, and making strategic calls about what’s price pursuing and what’s a distraction.