Behavioral segmentation refers to the practice of identifying and grouping online visitors based primarily on their online browsing and decision making patterns. This includes factors such as context and circumstance, as well as current objectives.
Traditional segmentation practices tend to group and target visitors by constant and flat attributes like geography (city, state, content), demographics (gender, age, income, etc. if available), technical (OS, browser, screen resolution), digital context (referrer, marketing channel, current page, etc.) as well as some dynamic lifecycle events (repeat visits, purchases, lifetime value, average order value.
On the other hand, behavioral segmentation is dynamic, ad-hoc, and adaptive as it depends on constantly changing variables such as the visitor’s current needs, moods, time constraints, and other discernible considerations.
For example, a certain visitor to an online retail site may fall into the following “traditional” segments:
- Visitor Type: Returning
- Marketing Channel: Email
- Gender: Male (CRM data or browsing history)
- Geo: Nevada, US
- Affinity: Running
While “behavioral” segments, ordinarily computed on a per-session basis due to their dynamic nature, would be represented as:
- Goal Oriented: Visitor knows the exact type of running shoes they are looking for.
- Satisficer: Per Barry Schwartz, the visitor doesn’t need endless comparisons and recommendations; once a “good enough” pair of shoes is encountered, the quest ends.
- Rushed: In a hurry, the visitor needs not be interrupted during the shopping experience.
Additional behavioral segmentation examples include:
- Explorers: Visitors in a passive consumption mode are more susceptible to enticing content.
- Maximizers: Visitors who experience FOMO need to consider every available option in order to make a decision.
The advantages of behavioral segmentation emanate from an adaptive nature which caters directly to a visitor’s in-the-moment needs increasing the probability of impacting the decision-making process.
