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Is Your Website Intent Real? A 30-Minute Audit to Separate Buyers From Bots

· 5 min read
MarketBetter Team
MarketBetter Team
Content Team, marketbetter.ai
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Website visitor data is one of the most persuasive reports a marketing team can show: dozens of named companies on your site this week, some of them on the pricing page. It is also one of the easiest reports to get wrong.

A good share of what looks like intent is not a buyer at all. It is a crawler checking your pages, a security scanner, your own team, an existing customer logging in, or a partner looking up a link. Route that to sales and two things happen: reps waste time on accounts that were never in market, and they stop trusting the signal, including the real ones.

This is a 30-minute audit any marketing or RevOps leader can run on last month's visitor data. You do not need a data team. You need an export and a little scepticism.

Start with one export​

Pull last month's identified company visits with, at minimum: company name and domain, pages viewed, time on site or session length, number of sessions, and the date and time of each visit. If your tool shows how the company was identified (for example a reverse-IP match versus a known contact), include that too.

Sort by number of sessions, highest first. The top of that list is where most of the noise lives.

Check 1: Crawlers and automated visits​

Automated traffic has a shape. Look for:

  • Many pages in seconds. A human does not read twelve pages in forty seconds.
  • Perfectly regular timing. Visits at the same minute every day, or every few hours around the clock.
  • Odd page sets. Sitemap files, every blog post in date order, or only pages a human would rarely open, such as legal or old archive pages.
  • Hosting and cloud providers as the "company". A visit resolved to a data center or hosting company is almost never a buyer.

Exclude these from anything that reaches sales. If your tool lets you, filter them at the source so they do not inflate account scores either.

Check 2: People who already know you​

The second biggest source of false intent is friendly traffic:

  • Your own company. Staff reading your own blog will show up, especially from home networks.
  • Customers. Someone logging in to your product, reading docs or checking an invoice is not a new opportunity. It might be an expansion or a support signal, but it belongs with the account owner, not in a prospecting queue.
  • Partners, agencies and investors. They visit often and look a lot like engaged prospects.
  • Competitors. They read your pricing and product pages more carefully than most buyers do.

Keep an exclusion list for each of these groups and apply it before routing. Review it every quarter, because customers, partners and competitors change.

Check 3: Is it the company, or just the network?​

Reverse-IP identification tells you which network a visit came from. For a large company with its own network, that is usually right. For people working from home, on mobile or on shared office networks, the match can be loose or simply wrong.

Two quick tests:

  • Does the company make sense? If a ten-person firm in an unrelated industry shows up reading enterprise pricing at 3 a.m., treat it with suspicion.
  • Is there a person behind it? A visit tied to a known contact (for example someone who clicked a link in your email or filled out a form) is far stronger than an anonymous network match.

Weight matches accordingly. A known person on your pricing page is a call today. An anonymous network match on one blog post is, at most, a reason to keep watching.

Check 4: What did they actually look at?​

Not every page carries the same meaning. Rank your pages into rough tiers:

  • Strong: pricing, product pages, comparison pages, integration pages, contact or demo pages.
  • Medium: case studies, product-specific guides.
  • Weak: general blog posts, careers, about, news.

A single visit to a weak page is research, not intent. Repeat visits across several days that move toward strong pages, from more than one person at the same company, are what buying committees look like.

Check 5: Did it happen after your outreach?​

A visit a few days after your team emailed the company is a different signal from a cold visit. It often means the email worked, even with no reply. Separate these out: they should go back to the rep who sent the email, quickly, rather than into a general queue.

What to do with the results​

When you finish the five checks, put every account from your export into one of three buckets:

  1. Route to sales now: real companies, not customers, partners or competitors, looking at strong pages, ideally with a known person or repeat visits.
  2. Watch: real companies with weak or one-off activity. Keep them in marketing programs and let them earn their way up.
  3. Exclude: crawlers, hosting providers, your own staff, customers (send those to the account owner instead), partners and competitors.

Most teams find the first bucket is much smaller than their dashboard suggested. That is good news. A short list that sales trusts gets worked; a long list that is half noise gets ignored.

Make it a habit, not a project​

Run this audit once by hand so you understand your own traffic. Then turn each check into a standing rule in your tools: bot filtering at the source, exclusion lists applied before routing, page tiers in your scoring, and post-outreach visits sent back to the rep who emailed.

Revisit it each quarter. Your site changes, your customer list grows, and new crawlers appear. The goal is simple: when a rep sees an account flagged as showing intent, they should be able to believe it.

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