Bulk domain analysis: compare 50 competitors in an afternoon

You can compare 50 competitors in a single afternoon if you work from a list, run every domain through the same checker, and judge the results as a group instead of one by one. The advantage of bulk analysis is not speed alone. It is that the same method applied to every site makes their errors similar, so the ordering you get is far more trustworthy than any single number.

Why bulk beats one-by-one

Looking up competitors individually creates two problems. You spend hours, and you quietly change your method from site to site, checking one more thing for a favorite and skipping it for a rival.

When you analyze 50 domains with an identical routine, the method becomes a constant. A bias that affects all sites equally does not change the ranking. And patterns that are invisible in single lookups, such as a cluster of small sites all growing together, become obvious in a table.

Step 1: Build a clean list (30 minutes)

Quality in means quality out. Start by defining the market in one sentence, for example "AI video generators for marketers." Then collect candidates from several places.

• A category directory. The AI startups directory groups tools by category, such as ai-video or ai-writing, which is a fast way to see who is in a space.
• Search results. Search the main phrases a buyer would use and note every domain on the first few pages.
• Review and listing sites. Comparison articles and app marketplaces list alternatives.
• Your own data. Customers, lost deals and community threads mention competitors you may not know.

Write the list as bare domains, one per line. Remove duplicates and protocol prefixes. If a company has several domains, such as a marketing site and a separate app, pick the one where visitors arrive.

Aim for 50, but accept 30 or 80. The goal is coverage, not a magic number.

Step 2: Run the batch (15 minutes)

Paste the list into the bulk checker, which accepts many domains at once and returns modelled monthly visits for each. The estimates come from five free popularity lists,, combined from the methods described in our methodology.

Export or copy the output into a spreadsheet. Add columns for the date and the source, so you can repeat the exercise later and compare.

If a few domains return nothing, do not discard them. A blank usually means "too small to appear in the public lists," which is itself a finding.

Step 3: Clean and normalize (30 minutes)

Raw output needs a little care before you draw conclusions.

1. Merge duplicates. If two domains belong to the same company, decide whether to combine their traffic.
2. Flag parent brands. A product living on a big company's domain will show the whole company's traffic. Mark these as not comparable.
3. Convert to bands. For each site, turn the number into a band, such as under 10k, 10k to 100k, 100k to 1M, over 1M. Bands prevent false precision.
4. Add context columns. Category, launch year if known, pricing model and primary region.

The banding step matters most. Estimates for small sites are unreliable, so the difference between 12,000 and 15,000 visits should not be allowed to change your conclusion. A band change should.

Step 4: Rank and look for structure (45 minutes)

Sort by estimated visits and look at the shape.

• Is there a clear leader? In many markets one or two sites hold a large share and the rest trail far behind.
• Where is the cliff? Often there is a visible drop between the top group and the long tail. That cliff marks the real competitive set.
• Are there clusters? Groups of similar-size sites often share a strategy, such as all targeting the same keyword family.
• Who is isolated? A site far above the others deserves a close look. Either it is a true leader or it is a parent-brand distortion.

Next, add the dimension of time. Re-run the same list a month later, or check the trending traffic rankings, and mark who moved up or down a band. Movement within a band is noise. A band change is a signal.

Step 5: Segment the list (30 minutes)

Not every competitor is equally relevant. Split your 50 into groups.

Group	Description	What to do
Leaders	Top bands, established	Study positioning, pricing and channels
Direct rivals	Similar size and offering	Track monthly, compare features
Rising	Moving up bands	Study what changed, watch closely
Long tail	Small or blank	Check occasionally, mine for ideas
Not comparable	Parent brands, different markets	Exclude from ratios

Your attention is limited. The point of the exercise is to decide which five to ten sites deserve a deeper look.

Step 6: Deep dive on the shortlist (60 minutes)

For each of the top few, add what the bulk run could not tell you.

• Run each individual domain through the traffic checker for regional data, tech stack and an SEO audit.
• Read their pricing page and note the lowest paid plan.
• Look at their top content and what keywords it targets.
• Check how recently their site was updated and how often they publish.

This is where you convert numbers into strategy, such as "three rivals are growing by targeting comparison keywords we ignore."

Step 7: Record decisions (15 minutes)

Write a one-page summary with the market definition, the date, the method, the bands, the shortlist and three actions. Save the spreadsheet. In a month or a quarter you will be glad you did, because trends only exist when you have a history.

Mistakes that ruin a bulk analysis

Mixing sources halfway. Use one checker for the whole batch. If you must switch, redo everything.

Over-reading small differences. Rankings among small sites shuffle constantly. Ignore changes that stay within a band.

Including the wrong domains. A product that is part of a larger company inflates its own numbers. Check each top entry by hand.

Treating the list as complete. You will miss new entrants. Re-check new entrants periodically.

Forgetting the denominator. A competitor with 5 percent of the market leader's traffic is not necessarily irrelevant if they own a niche you care about.

How accurate is it?

Be upfront with anyone who reads your analysis. Public tools, free or paid, estimate rather than measure. In one small Screaming Frog test, estimates for small sites were often well off, while the author's takeaway was that these tools suit trends and competitor comparisons better than exact traffic. That is exactly the use case for a bulk run, which is why ranking and banding work better than quoting numbers.

A reusable template

Keep a spreadsheet with these columns: domain, date, source, estimated visits, band, previous band, category, notes. Duplicate it each month. After three months you will have a real picture of your market's movement, built in a few hours a month.

What a good output looks like

At the end of the afternoon you should have three things. First, a sorted table of your market with bands and dates. Second, a shortlist of five to ten sites with a sentence about why each matters. Third, a list of questions the data could not answer, such as which rivals are profitable or which channels drive their growth.

That third item is the most valuable. Good research does not pretend to know everything. It tells you precisely what to investigate next, whether through interviews, product trials or direct requests for numbers.

FAQ

How many domains can I analyze at once?

The bulk checker is designed for many domains in a single run, and 50 is a comfortable size for an afternoon workflow. Split larger lists into batches to keep your cleanup manageable.

Do I need paid access for bulk analysis?

You can start with the free tools. Paid plans on the pricing page unlock more of the leaderboards, which helps when you want to see names across entire rankings.

What should I do with domains that return no data?

Keep them in the sheet and mark them as below the public threshold. They are probably small or new, and recording that is useful.

How often should I repeat the analysis?

Monthly is a good rhythm for active markets and quarterly for slow ones. Use the same list and the same tool each time so that changes are real.