Free SEO Competitor Analysis Tool

Competitor SEO analysis means measuring the sites you compete with against the same criteria you measure yourself against, then using the differences to decide what to work on.

It is a comparison exercise, not an inspection. The output is not a list of everything wrong with your site.

It is a ranked account of where you sit behind, ahead, or level with the sites standing between you and the top of the results page.

That distinction matters because rankings are positional. No absolute score earns a top-three placement. A page ranks because it was judged a better answer than the alternatives available for that query.

Change the alternatives and the same page moves without a single edit. This is why an audit run in isolation can report a healthy site that keeps losing traffic. The site did not get worse. The field got better.

Best-practice thresholds are useful defaults and poor targets. They describe a general standard, not the bar in your specific market, and markets vary enormously in how hard that bar sits.

A comparison replaces generic thresholds with observed ones. Instead of asking whether a page loads inside a published target, it asks whether it loads faster than the pages currently outranking you.

Both questions are worth answering. The published Core Web Vitals thresholds tell you what counts as good in the abstract. Your competitors tell you what counts as enough here.

Most teams pick competitors from memory, and the list is usually wrong. The companies you name in a sales conversation are the ones with a similar product at a similar price.

Your search competitors are whoever occupies the results for the queries you want. That set routinely includes publishers, marketplaces, review sites and forum threads that are not in your business at all.

It just as routinely excludes your closest commercial rival, because they never invested in organic search. Optimising against them tells you nothing about the pages you actually have to outrank.

This tool derives the list from your site rather than asking you for one. It reads your pages to establish what you sell, finds the sites competing for that territory, then filters and re-ranks what comes back.

Each check produces its own score from 0 to 100, computed identically for every site in the run. Those scores roll up into a single overall figure on the same scale.

The roll-up is weighted. Checks with the largest observed influence on rankings — content quality, meta tags, keyword coverage, internal linking, page speed — count for more than lighter ones.

That weighting is what stops a missing Open Graph tag reading as equivalent to an uncrawlable site. It makes the headline number reflect SEO priority rather than a flat average of unrelated tests.

The overall number is a starting point, not a finding. Two sites can both reach 74 by opposite routes: one even across the board, another with excellent content dragged down by technical faults.

Those two sites need opposite work plans, which is why the comparison view leads with the per-check gap table rather than the headline figure.

Occasionally a site cannot be reached at all — a firewall blocks automated crawling, or the domain happens to be down when the run starts.

Those sites are dropped from the comparison rather than scored zero, so one unreachable competitor never drags down the field average you are measured against.

A growing share of queries now resolve inside an AI-generated answer that cites a handful of sources. Being one of those sources is a distinct competitive position.

You can hold it without ranking first in the classic listing, and you can lose it while your traditional rankings stay flat. Neither movement shows up in a rank tracker.

That is why the battery covers llms.txt and LLM optimization alongside traditional signals. They measure whether your content can be parsed, extracted and attributed to you.

The llms.txt specification is young and adoption is thin, which is exactly why it shows up as an uncontested gap in most markets. Clear structured data helps for the same reason.

Practically: if every site in your comparison scores badly on AI readiness, that is the cheapest lead available. If competitors already score well and you do not, you are losing citations now.

The most common failure is treating the report as a to-do list and working top to bottom. A comparison produces dozens of differences and most of them are noise.

Without filtering for gap size and ranking impact, teams spend a quarter closing three-point deficits on checks that were never going to move a position.

The second failure is copying tactics without the conditions that made them work. A competitor publishing weekly on a fifteen-year-old domain with thousands of referring domains operates under constraints you do not share.

Their cadence is not a strategy you can lift. It is a behaviour their existing authority allows. Compare the checks first, then ask whether the same move is even available to you.

The third is running the analysis once. Competitive position moves constantly, and a single run tells you where you stand today with nothing about direction.

Google's own guidance on creating helpful content is a useful corrective here: the goal is being the better answer, not matching a competitor field by field.