# Spotting buying interest: which page views count

> Spot buying interest on your website: which page views, clicks and returning visits count, and how to rate company visits with a points scheme.

Quelle: https://whovisit.app/en/blog/spot-buying-interest-website-page-views
Veröffentlicht: 2026-11-07
Herausgeber: Whovisit (ARAVILO, Innsbruck)

A company was on your website. At first that is merely a fact. Whether it implies interest in your offer depends on what the company did there. Anyone who treats every identified company like a prospect wastes time. Anyone who reads visits by their weight sees more quickly where a conversation is worthwhile.

This article shows which signals are meaningful, how to read them and where the pitfalls lie. Everything works at **company level**: you see what happened from within an organisation, not what a particular person did.

## Strong and weak signals

Not all pages say the same amount. The following table is a rule of thumb, not a law of nature. Depending on your offer, the weighting shifts.

| Signal | Weight | Why |
|---|---|---|
| Viewed prices or plans | strong | Anyone checking prices is usually already comparing |
| Contact page viewed, phone or email link clicked | strong | The step to an enquiry is close |
| Form submitted | strong | This is an enquiry you can answer directly |
| Download (price list, data sheet, catalogue) | strong | Anyone who downloads documents wants to pass them on internally |
| References or case studies | medium to strong | Often read as reassurance before a decision |
| Service or product pages | medium | Shows interest in the topic, not in buying |
| Return on another day | medium to strong | Anyone who comes back is occupied with it |
| Blog articles | weak to medium | Often research, sometimes chance |
| Home page alone | weak | Usually a brief glance |
| Careers, legal notice, privacy | weak | Applicants, auditors, the curious |

What matters is the **combination**. A company that views services, references and prices and comes back the next day tells a different story from a company with a single glance at a blog article.

## Active time instead of time on page

Time on page sounds like a good measure but is deceptive. A browser tab left open over lunch counts as two hours on page, although nobody is looking.

Better is **active time**: the time in which the tab is visible and the window is in the foreground. Active time keeps counting only if both are true. A forgotten tab thus produces no phantom time. This helps with questions like: did someone skim the pricing page in ten seconds or read it for four minutes?

## Reading scroll depth correctly

Scroll depth shows how far down a page someone got, as a percentage. It is useful but easy to overrate:

- **A high value does not automatically mean reading.** Anyone who rushes down quickly reaches 100 percent quickly.
- **Short pages distort.** On a short page, 100 percent is reached quickly.
- **Long pages with the pricing block far down** say something when scroll depth is high and the active time fits.

Always read scroll depth and active time together. High depth with very short time is skimming; low depth with long time is often a conversation in the background.

## Clicks with meaning

Some actions are more telling than any time on page. Whovisit records these clicks:

- **Email link** (a click on a `mailto:` address)
- **Phone link** (a click on a `tel:` number)
- **Download** of files such as PDF, ZIP, Word, Excel, PowerPoint, CSV, DWG or DXF
- **Outbound click** to another domain
- **Form submitted**, with the form's identifier but without the content entered

A submitted form reaches you directly anyway. What is valuable is the click on an email or phone link: it shows that someone considered making contact, even if no message arrived. The outbound click, by contrast, is ambiguous: it may lead to a competitor or to a social media profile.

## A simple points scheme

Anyone with many companies in the report needs an order. The following scheme is expressly an **example to build yourself**. The numbers are invented and do not come from a measurement. Adapt them to your offer.

| Event of a company in 14 days | Example points |
|---|---|
| Pricing page viewed | 3 |
| Contact page viewed | 2 |
| Download of a price list or data sheet | 3 |
| Click on phone or email link | 3 |
| References or case studies viewed | 2 |
| Second visit on another day | 2 |
| Service page viewed | 1 |
| Blog article read | 1 |

Then you decide at how many points you take a closer look at a company, for example from 6. Important here:

- This is a sorting aid for your attention, **not a probability** and not a verdict on the company.
- After a few weeks, check whether the highly rated companies actually came into conversation more often. If not, change the weights.
- Do not count identical events without limit. Ten blog articles are not worth ten times as much as one.

Such a scheme rests on fixed rules that you define yourself. It is not an automatic rating by artificial intelligence.

## Pitfalls

Before you call or write to a company, check who was really there:

- **Your own staff.** Colleagues look at the pricing page, bosses check the presentation. If your own office network shows up, that is not the market.
- **Applicants.** Someone from a company may view the careers page. That is curiosity about you as an employer, not a buying signal.
- **Suppliers and service providers.** They also read your site, often out of self-interest.
- **Competitors.** Anyone watching the competition looks closely at prices and services.
- **Bots and tools.** Data centre networks are counted separately and not stored as a company. Even so, companies' checking tools can show up.
- **Many people behind one network.** A company address can bundle hundreds of people. Any department can be behind a visit.

Added to this is the limit of the method itself: anyone accessing from home or on mobile is invisible in this analysis. Why that is so and how much the figures fluctuate is explained in [Identification rate: why the figures vary so much](https://whovisit.app/blog/erkennungsquote-besuchererkennung).

## What you do with the list

A ranked list is only the beginning. How to turn a company with a high score into a conversation without crossing any lines is covered in [From the identified company to a conversation](https://whovisit.app/blog/von-der-erkannten-firma-zum-gespraech). How visits, actions and page sequences can be read in the report and processed further as a file is shown in the help section under [Reading the report and exporting it as CSV](https://whovisit.app/hilfe/bericht-lesen-und-exportieren). And if you want to know where the job of web analytics ends and that of visitor identification begins: [Identifying companies with Google Analytics: what works and what does not](https://whovisit.app/blog/firmen-erkennen-google-analytics).

Where the companies in the list come from in the first place is explained in [Which companies visit my website?](https://whovisit.app/blog/welche-firmen-besuchen-meine-website).