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Behavioral Data

Behavioral Data

Definition: behavioral data


‍Behavioral data shows everything about a visitor’s self-directed actions while on your site or inside your app. ‍It provides information not just around who a customer is, but about what they explicitly doing while poking around the web.


In marketing terms, we generally capture both ‘events’ and ‘properties’ for these users. As long as proper tracking is in place, we are able to capture this data from both identified and anonymous visitors.


Behavioral data falls in as one of the four major groups of data commonly used for segmentation and personalization by marketers: Demographic, Firmographic, Behavioral, and Contextual. While each of these sources provides relevant context on their own, when the sources are combined, you can get a more robust picture of a customer’s unique wants and needs.

Why is behavioral data important?

While knowing about a visitors title, industry, or role is important when trying to segment and personalize an experience, behavioral data takes on-site personalization a step further. By studying what a visitor finds interesting on your site and how exactly they shop, you can create more relevant ads, copy, headlines, content, and pages for different groups of visitors.   


For instance, if a customer reads a series of E-commerce case studies and blog posts, you can rationally assume that type of content is relevant to them — and you can start personalizing their experience with that in mind.

Examples of behavioral segmentation

There are several ways to source behavioral data and segment your traffic. Here are some common points of behavioral data that can segment your audience:

  • On-site activities
  • On-site actions taken in the past
  • Content consumed, shared, bookmarked
  • Repeat visits
  • Session length
  • Pages visited
  • Sessions per page
  • Referral path
  • Actions by day / time / season
  • Events triggered (log-in, registered, launched campaign)

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