How does Pathmonk detect the stage of the customer journey?

If you’ve already had the Pathmonk tracking snippet installed on your website for a few hours, you’ll start seeing data that helps you understand how Pathmonk detects buying journey stages. To view it, go to Analytics → Visitors Journey → All Visitors.

You’ll see a list like this:

In this report, you’ll find every single website visitor, each one identified by a unique fingerprint. As you can see, every visitor is automatically assigned a journey stage (from Awareness to Conversion), including Bounced visitors.

Now, let’s click on one of the fingerprints located in the Awareness stage.

In this example, the visitor has only visited the website once, and Pathmonk’s AI has detected 3 tracking points (these could be any type of intent signal, for example, scrolling, clicking, or viewing multiple pages).

Based on this behavior, the AI assigns the visitor a low level of interest and automatically categorizes them in the Awareness stage of the buying journey.

Over time, if the same visitor returns, spends more time exploring, or interacts with key content, Pathmonk’s AI will reclassify their stage dynamically, for instance, moving them into Consideration or Decision as their intent grows.

Now let's click on a fingerprint tagged in the Decision stage for a completely different picture. 

In this example, the visitor has completed 7 page views in a single session, and Pathmonk’s AI has detected 51 tracked points. This indicates a high level of interest and buying intent.

If this visitor falls into the Pathmonk-enabled segment of your test, they’ll experience different micro-experiences than someone in the Awareness stage. That’s because Pathmonk automatically adjusts the messages and interactions shown, prioritizing content that guide the user toward conversion.

Basically, our AI algorithm learns from each action on a website.  As visitors spend more time on a site, clicking through pages, scrolling down, and even leaving and returning, Pathmonk uses those actions to determine the buyer journey stage. The algorithm moves visitors through the stages and updates the microexperiences without human intervention.  

The algorithm builds knowledge based on how long a visitor is on the site, how many times they visit the site, their number of interactions and engagement, and of course when they convert.  All of this data is analyzed to not only determine the buyer journey stage but also to refine the microexperience activity to find the ideal time and place to be displayed that will result in a conversion for future visitors.