How to Do SEO Competitor Analysis Without Drowning in Data

Most SEO competitor analysis ends the same way.

A spreadsheet with dozens of tabs. Thousands of keywords.

A dozen screenshots of a rival's homepage. And no decision.

The problem isn't a lack of data.

It's collecting data before you know what you want it to answer.

I run competitor research as a repeatable pipeline for my own projects.

These are the eight steps behind it, in the order that keeps the data useful.

Step 1: Pick Your Search Competitors

Start with who Google thinks you compete with.

That's often a different list from the one in your head.

Take five to ten of your most important money terms.

The searches that bring in paying customers.

Search each one (logged out, in the right country) and note which domains appear on page one again and again.

Then compare that list with the businesses you actually lose deals to.

You'll usually find three groups:

• Direct rivals who also rank. Include them.
• Rivals who don't rank. Useful for sales, not for SEO research.
• Sites you've never thought about. Directories, publishers, a national chain. Include the ones that hold several of your terms.

Settle on three to five domains.

More than that adds cost and reading time without adding new patterns.

Step 2: Write Down the Questions First

This step is the one that stops you drowning.

Before you pull a single row, write the questions this research must answer.

Mine almost always come down to five:

1. What pages do they have?
2. Which of those pages earn rankings and traffic?
3. How is their site organised?
4. What kinds of informational content work for them?
5. Which sites link to them but not to me?

Every later step answers one of these.

If a dataset doesn't answer any, don't collect it.

Note: Ranking data from tools like Ahrefs or Semrush costs money, either as a subscription or as API usage. Before a big pull, I estimate the cost from the number of competitors and the size of their sites. Large online shops can have hundreds of thousands of URLs.

Step 3: List Every Page Each Competitor Has

You can't analyse a site you've only seen through its main menu.

The best free source is the competitor's XML sitemap.

It's the list of pages they ask search engines to crawl.

Check /robots.txt first.

Google's guide to building sitemaps tells site owners to add a Sitemap: line there, so it usually points straight to the file.

Big sites split their sitemaps.

Google limits each file to 50,000 URLs or 50MB uncompressed, so you'll often find a sitemap index pointing to many child files. Follow every one.

I've written a full walkthrough, with code, on finding every page on a competitor's site.

It also covers what to do when there's no sitemap.

Don't use a site: search as your page list. Google's own site: operator documentation says the results are not always exhaustive, and bigger sites shouldn't expect to see all their URLs.

At the end of this step you have one list of URLs per competitor.

Step 4: Join the Page List With Ranking Data

A sitemap tells you what a competitor built.

It doesn't tell you what works.

For that, export the competitor's organic pages and keywords from a rankings tool.

I pull them through the Ahrefs API, but a top pages export from any major tool does the same job.

Now join the two lists on URL.

This sounds simple.

It isn't, because the same page gets written in different ways:

• With and without a trailing slash.
• With tracking parameters on the end.
• Under a country folder, like /en-gb/, on one list but not the other.

Clean every URL the same way before you join.

Lowercase the host, drop parameters and fragments, and strip locale folders.

Then flag each row:

That third group is my favourite.

It shows where a competitor's results have drifted away from their plan.

Step 5: Read How Their Site Is Organised

Now step back from single pages and look at the shape of the site.

Group the URLs by their first folder: /services/, /locations/, /collections/, /blog/.

Count how many pages sit in each.

Then ask:

• How many sections do they have? A shop with 60 collections targets demand differently from one with 8.
• How deep do pages sit? Count the clicks from the homepage to a typical product or service page.
• How many items live in each section? Product counts per collection show where they've invested.
• Which words repeat in their URLs? Recurring words show the vocabulary they've built the site around.

This is the step that turns a list of pages into a strategy you can read.

If their structure is much cleaner than yours, that's a finding in itself.

It belongs in a technical SEO review of your own site.

Step 6: Sort Their Content by Type

Counting blog posts tells you very little.

A calculator, a downloadable checklist and a 3,000-word buying guide do very different jobs.

So give every informational URL a type:

• Tool or calculator
• Lead magnet (template, checklist, download)
• Guide
• Blog post
• Glossary entry
• Comparison

Keep the ranking data next to each one.

Then look for formats that rank across several competitors.

For example, if every site above you has a cost calculator and you don't, that's a decision worth making on purpose.

This list also feeds straight into your content planning.

My guide to doing a content gap analysis shows how to turn it into topics without repeating what you already have.

Step 7: Find Sites That Link to Them but Not You

The last question is about links.

Export the referring domains for each competitor.

Then find domains that link to two or more competitors but not to you.

These are often:

• "Best providers in X" listicles
• Industry directories
• Comparison and review sites

A site that already mentions three of your rivals writes about your category.

You have a real reason to contact it.

Check every domain by hand before outreach.

Some will be spam, some will be dead, and some will only list businesses that pay.

For the directory side specifically, I've covered the process in how to find directory listing opportunities.

Step 8: Turn the Findings Into Decisions

Raw data is only worth something if it changes what you do next.

Go back to the five questions from Step 2.

Write one or two sentences under each, and point to the rows that prove it.

Then route each finding to the work it affects:

Keep the raw sheet per competitor.

When you repeat the research in six months, the differences between runs are often the most useful finding of all.

If you want the keyword side automated too, read how to automate keyword research.

Competitor mining is one of its stages.

Start With One Competitor This Week

You don't need five rivals and a paid API to begin.

Pick the one competitor that annoys you most.

Find their sitemap, count their pages by folder, and look at which sections hold the most URLs.

That alone will show you something you didn't know about how they win.

When you're ready to do it across a whole market, my competitor analysis automation runs these steps as a pipeline and hands you the raw sheet per competitor.

It sits alongside the other SEO automation services I run, and you can see how the research ends up in a keyword plan or ask me to map your competitors for you.