How to Analyze SEO Competitors with Claude or ChatGPT

Your sales team names three competitors. Google shows you a trade publication, a spreadsheet template, and a company you have never heard of. Which ones should guide your SEO strategy?

All of them may matter, but they answer different questions. Sales competitors help you understand alternatives to your product. Search competitors show you which pages currently serve the queries your buyers use. Confusing the two produces content plans full of topics that are relevant to your industry but poorly matched to your customers.

A useful SEO competitor analysis ends with a decision: improve an existing page, create something distinct, investigate further, or leave a topic alone. A spreadsheet of competitors' rankings is evidence for that decision, not the deliverable.

Use Claude or ChatGPT with RankParse to compare the pages you found in search, inspect competitors’ most-linked resources, and investigate relevant citation contexts. The core tools are get_page_seo, get_top_pages, and a bounded get_backlinks lookup when a resource warrants deeper research. You supply the customer decision and verify the decisive pages. The workflow turns those observations into a content brief; it is a proposed process, not a report of an agent run.

Start with the customer decision you want to influence

Before opening a research tool, write down three things:

• Audience: who you can realistically help.
• Decision: what they need to understand or choose.
• Business connection: what a useful next step with your company would be.

For example, imagine a fictional warehouse software company serving manufacturers with 20–100 employees. Its audience is an operations manager replacing spreadsheets. The decision is whether to introduce inventory software and how to make that transition. The next step might be a migration assessment.

That definition rules out several superficially attractive topics. Broad retail trends may have more searches, but the company lacks a meaningful next step for most readers. Enterprise warehouse robotics may fit the industry while missing the customer's budget and problem.

Select a small group of questions around one decision. In this example:

• When does a stock spreadsheet become unreliable?
• What does inventory software for a small manufacturer need to do?
• How do you move inventory records from spreadsheets into software?
• What should an inventory migration checklist include?

Use customer calls, support questions, and your own search data to refine the wording. If you already receive relevant impressions, Search Console can reveal content opportunities grounded in your site's visibility.

Build a competitor set for each topic

Search those questions in the market and language you serve. Record the date, country, device where relevant, and exact query. A search result is a snapshot, and different locations or query wording can produce different competitors.

Inspect the pages that repeatedly appear across the question group. Do not make every domain in one result a strategic rival.

Separate three roles:

A forum thread might reveal that people need practical answers about inconsistent SKU names. A template might show they want an artifact they can use immediately. A product page might indicate that some searchers are ready to evaluate software.

Mixed results are useful evidence of uncertainty. They are not an instruction to combine every possible intent into one enormous page. Narrow the query, review related searches, and choose the specific reader task you can serve well.

For a first pass, choose three to five relevant pages per topic group. That is a manageable starting sample, not a statistical rule. Add more when the sample misses a distinct audience or format.

Give Claude or ChatGPT a bounded research assignment

Connect RankParse using the MCP setup guide. The web connector uses OAuth and provides read-only research tools. Start with the candidate URLs from your search review: similar link profiles can suggest additional domains, but they do not establish that those domains compete for your target queries.

Ask the assistant to inspect those URLs with RankParse's page SEO tool and review the competitors' most-linked pages. “Most-linked” is not “highest traffic” or “best converting.” Link-graph results reflect a periodic snapshot; record the retrieval date and any available source freshness separately. Live page checks describe current page elements, not historical changes.

Paste this prompt after replacing the bracketed inputs:

We serve [audience] and want to help them [decision]. Our useful next step is [business action]. Analyze these candidate search-competitor pages: [URLs and search-review date/market]. Use RankParse to inspect titles, headings, canonicals, and internal/external link counts, and find relevant most-linked resources on these domains. Limit the first pass to these pages and domains. Report the source URL, tool observation, freshness if available, and what remains unknown for each finding. Do not infer traffic or rankings from backlink counts. Separate observable gaps from hypotheses. Recommend one existing-page improvement, one distinct new resource if justified, and one topic to defer. Explain what evidence would change each choice.

Use ordinary browsing, where available, to read the page's actual explanation and examples; otherwise provide page excerpts yourself. An extracted heading list is insufficient evidence that a guide answers a question well. Ask the assistant to mark pages it could not read rather than fill the gaps from memory.

Before accepting its recommendation, open the decisive pages yourself. Confirm the claimed omission, check whether it is intentional scope, and have a subject expert assess your proposed contribution. In the warehouse example, the agent might propose a SKU-cleanup worksheet. The human decision is whether an implementation specialist can supply and review a useful one. Keep the worksheet idea only if that work is feasible.

Collect two different kinds of competitive evidence

Give the assistant a compact input packet before it calls tools. Include your domain, the audience and decision, three to five observed search-result URLs, their domains, and the query/market/date notes from your search review. Add your closest existing page and a short account of what your specialist can contribute. This last input prevents a list of competitors' assets from becoming a commitment to produce resources you cannot maintain.

RankParse supplies two useful views of that packet. get_page_seo describes the fetched page's metadata and structure now. get_top_pages identifies pages with inbound links in the periodic link snapshot. Neither replaces the search-result review you supplied: a linked page may not rank for the question, and a ranking page may not be prominent in the link graph.

Run the first stage with this prompt:

For these supplied competitor URLs and our existing URL, use
get_page_seo. Return title.text, final_url, canonical.url,
headings.h1, headings.h2, and internal/external link counts.
Flag failed or unexpected responses. Do not infer full coverage
from headings: the returned H2 list is limited.

Then use get_top_pages for these two competitor domains, limit 10.
Keep url, inbound_links, referring_domains, and any partial status.
Record retrieval time and snapshot information if available.
Group the returned resources by likely reader task, marking that
classification provisional until we read each selected resource.
Do not infer search positions, traffic, or conversion rates.

The top-pages documentation explains that the results can include subdomains and that total counts the returned rows. Ten rows are not the domain's complete inventory. The recorded HTTP status in link data also is not a current availability check. Fetch a resource with get_page_seo or open it before building your recommendation around it.

Select one or two resources that overlap the customer decision. Ask the assistant why each warrants reading, then inspect the actual content. If you cannot browse through the client, provide excerpts containing the relevant instructions and examples. A title such as “Migration checklist” is a reason to look, not evidence that the checklist handles duplicate SKUs correctly.

Follow a promising resource back to its context

A competitor's linked worksheet may be worth studying because people use it to support their own explanations. To investigate, ask for get_backlinks on that competitor domain with a small limit and sort=recent, then look for returned to_url values matching the resource. This requests URL-level evidence; it does not filter the entire domain's link graph to that page. If none of the returned rows match, record “not present in this sample.”

When useful rows exist, open the from_url pages and verify the link, surrounding text, and audience. Keep crawled_at separate from today's retrieval time. A recently retrieved row can describe an older observation, and the linking article may have changed since then.

For a domain-level comparison, get_competitor_gap accepts your domain, the competitor as vs, and a limit. Its output identifies linking domains found for the competitor but not yours in the snapshot. It does not identify missing keywords or prove that a publisher wants your resource. Use it only when the research question includes potential citation audiences; a content brief does not always need this extra call.

For [our domain] versus [one relevant competitor], call
get_competitor_gap with limit 10. Preserve crawl_release,
partial, scored, and the returned count.

Classify domains by audience relevance only where we have evidence.
Choose up to three that merit manual editorial review. Explain
what to inspect before calling them opportunities. If scored is
false, do not interpret zero scores as low authority. Do not draft
outreach or assume a missing snapshot link is absent today.

The competitor-gap response can be partial even when scoring succeeds. Large competitors are sampled; the result is not an exhaustive map of their relationships. Authority ordering helps sort research, but domain authority is not a Google ranking factor or proof of editorial quality. A small specialist publication may be more relevant to your buyers than a higher-scoring general site.

From returned fields to a resource decision

Consider this invented evidence packet, not a live study:

Eight referring domains are not eight endorsements of every claim in the worksheet. One manually inspected citation does not represent all eight. The defensible decision is narrower: create a useful duplicate-SKU example within the migration resource because the reader need, observed citation context, and available expertise align.

Use a synthesis prompt that carries those distinctions into the brief:

Turn evidence C1-C5 into one proposed brief. For every required
section, name the reader task and evidence supporting it.
Separate what RankParse returned from manual observations and
our original contribution. Include one reason not to proceed.

Do not reproduce competitors' wording, headings, or proprietary
worksheets. End with a decision table: improve existing page,
create new resource, investigate, or defer; owner; dependency;
and evidence that would reverse the choice.

If the tool sees a bot challenge, sparse JavaScript-only content, or an unexpected redirect, mark that comparison incomplete and read the page manually. If link evidence is empty, continue with the verified search and content observations; absence from a snapshot does not invalidate a customer problem. For a large site, repeat this process by audience or product line instead of ranking unrelated departments in a single competitor table. For a small team, one completed brief with verified evidence is a better endpoint than an expanding list of domains to research.

Read the pages for utility, not just headings

Comparing headings finds common coverage. It rarely explains why a page is useful.

Work through each page as the intended reader. Ask whether you can make the decision or complete the task after reading it. Record observable evidence instead of impressions such as “high quality” or “thin content.”

For the warehouse example, the notes might look like this. The pages and findings below are fictional illustrations, not a live search study.

These notes support specific editorial decisions. “Write a longer guide” does not.

Check whether the apparent omission really belongs on the page. A product comparison is not necessarily deficient because it lacks a migration tutorial. Different pages can serve different stages of the same journey.

Also assess the evidence behind claims. Does the author explain their method? Are examples specific enough to inspect? Do screenshots or instructions match the current product? Can you distinguish demonstrated experience from generic advice? Apply the same standard to your proposed content.

Use competitive metrics as clues

Estimated traffic, ranking keywords, and referring domains can help you decide where to investigate. They cannot tell you a competitor's qualified pipeline or the profitability of a page.

A page with many estimated visits might rank for broad definitions. A page with few visits might address an expensive, urgent buying decision. Comparing those pages on traffic alone favors the wrong outcome.

When using third-party data, record the provider, retrieval date, market, and page or domain scope. SEO tools show different numbers because their coverage, definitions, and methods differ. Treat a small difference between estimates cautiously.

Inspect the actual queries behind an attractive traffic estimate. Then ask:

1. Are those searchers plausible customers?
2. Does the ranking page serve the same job we want to serve?
3. Do we have a credible reason to contribute?
4. Can we maintain the proposed resource?

Backlinks can add context too. If several relevant sites reference a competitor's worksheet, the worksheet may be useful enough to cite. That observation supports researching an original resource; it does not establish that copying the format will earn links or rankings. Evaluate the quality and relevance of those backlinks before treating the count as a meaningful advantage.

Turn the research into a choice

A “content gap” is simply something another site covers and yours does not. Some gaps are worth closing. Others reflect audiences you do not serve.

Use four editorial tests before adding work to your calendar:

Customer fit. Can you name the person and decision this page helps? If the answer is “anyone interested in our industry,” narrow it.

Evidence of need. Do search results, customer questions, or your own data support the problem? One competitor's article is a weak signal by itself.

Distinct contribution. What can your company provide that improves the reader's ability to act? This could be specialist review, a usable template, a worked calculation, or a better explanation of an overlooked constraint.

Delivery cost. Can you produce and maintain it with the people you have? A comparison that needs constant product testing may be a poor commitment for a small team.

Do not hide uncertainty inside a precise-looking score. A simple high, medium, or low assessment with written reasons is often more useful. If you need to compare this work with technical fixes and existing-page improvements, use an SEO prioritization process across the whole backlog.

For our fictional warehouse company, the migration checklist could pass all four tests. A general “best inventory software” list might not: the team has not evaluated enough competing products to make defensible recommendations.

That is a good reason to defer the comparison, even if competitor tools show attractive traffic.

A brief that preserves the useful research

The output should tell a writer what the reader needs and what evidence must be created. Here is a compact brief for the fictional migration resource.

Reader: Operations manager at a small manufacturer, moving from spreadsheets to inventory software.

Reader outcome: Identify data cleanup tasks and decide whether records are ready for migration.

Page promise: A readiness checklist with a small worked example of duplicate SKUs, units of measure, and stock reconciliation.

Original contribution: A blank review worksheet plus an annotated fictional dataset showing what needs correction and why.

Required review: An implementation specialist verifies the sequence and identifies situations that need accounting or system-specific advice.

Scope boundary: No claim that this checklist covers every migration platform, accounting treatment, or manufacturing setup.

Next step: Use the checklist independently; request a migration assessment if unresolved problems need support.

Success evidence: Relevant search visibility, worksheet use where measurable, and qualified assessment requests associated with the page.

Notice what the brief does not require: matching a competitor's word count, repeating every heading, or mentioning every related keyword. Those requirements would make the page easier to imitate and harder to focus.

Revisit the decision after publication

Record the publication date and the assumptions behind the brief. Review whether the page is indexed, whether its visible queries fit the intended audience, and whether readers take useful next steps. Allow for your site's normal discovery and sales cycles; there is no universal week when a new page must prove itself.

If the page attracts a different audience, investigate the title, examples, and scope before expanding it. If it attracts the right readers but few qualified inquiries, check whether the next step is appropriate and whether measurement is working. Low inquiry volume alone does not prove the content failed.

Keep a short decision log: what you observed, what you changed, and what would make you reconsider. Repeat competitor research when a material question arises, such as a new result format or a customer need your current page cannot answer.

The best outcome is a smaller set of defensible content decisions. You understand whom the page serves, why your contribution deserves to exist, and what evidence will tell you whether to keep investing.