Dynamic Segmentation

Dynamically segment users based on their interests, preferences, or browsing behavior on your website.

Target effectively different groups of users without the need for full personalization by using dynamic segmentation and dynamic content. This allows you to refine your marketing strategies and target users with content that is relevant to their specific interests.

A visual representing dynamic segmentation
Illustration: circular diagram with "price-conscious," "trendy," and "eco-friendly price tag

Rule-based segments vs. dynamic segments

Divide customers into rule-based segments based on their actions or add a temporal component to use them as dynamic segments.

Illustration: Family

Use customer interests in segments

Use segments to distinguish the interests of your users into impulsive, temporary and permanent.  This allows the store to show exactly matching recommendations, although temporarily products outside the regular interest are also considered.

Illustration: Two hotel listings, one "No Vacancy," another "Available" to "Book Now."

Segmentation according to brand affinity

Special preferences of your users can be highlighted as soon as they enter the store. The teaser areas on the start page offer special potential, as they can be dynamically changed after each session.

Want proof?

trbo helps companies of all types and sizes create exceptional customer experiences through personalization.

Discover more related features – matching your business needs

trbo offers a variety of features for your personalization journey.

With our product trbo Personalize we can provide you with the exact solution to achieve your website goals.


trbo Personalize


Create the perfect user experience with the right content at the right time
  • AI Recommendations
  • Content Personalization
  • A/B/MV Testing
  • Dynamic Segmentation

See the trbo toolbox

The technical base

Dynamic Segmentation

In order to be able to use dynamic segments, there must be a cleanly structured tracking system in which data is collected, if necessary also an external data connection. 

Machine learning, with the help of algorithms and data analytics, automatically detects patterns and preferences of your store’s users.

Enable data & analytics on consumer behavior:

  • personalized recommendations
  • targeted offers
  • customized content 

The click-in channel is an important data collection related to dynamic segments, as specific content and offers can be developed there.

Use A/B testing to test different versions of your website, content or offers. Find out which version performs best and gives users the best possible experience.

Personalized content and recommendations can be delivered independently of a specific online store or e-commerce platform to enable seamless and consistent personalization across different sales channels.

Telekom Logo
t-online Logo
Auf der Suche nach einem Anbieter mit dessen Hilfe wir mittels Software as a Service auf unseren Webseiten den Besuchern für sie relevante Angebote anzeigen können, sind wir mit trbo fündig geworden und haben damit auch durchweg positive Erfahrungen gemacht. Bekommen haben wir ein Tool, welches speziell auf die Bedürfnisse der Telekom zugeschnitten ist und auch bei sich ändernden Anforderungen von trbo schnell und lösungsorientiert angepaßt wird. Hat man ein Problem, so steht einem der trbo Support stets kompetent und schnell zur Seite.
When we were looking for a provider with whom we could show visitors relevant offers on our websites using Software as a Service, we found trbo and have had consistently positive experiences with it. We have received a tool that is specifically tailored to Telekom's needs and can be adapted quickly and in a solution-oriented manner as trbo's requirements change. If you have a problem, trbo support is always available to help you quickly and competently.
Frank Benner Business Epic Owner for Campaign Automation Business Epic Owner für Kampagnenautomatisierung

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Start delivering memorable, 1:1 experiences that keep your customers coming back.

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Let's get personal

Start delivering memorable, 1:1 experiences that keep your customers coming back.

We’ll reach out personally to guide you through how trbo can take your website’s performance to the next level.

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FAQs

What is dynamic segmentation in trbo?

Dynamic segmentation in trbo is an automated audience-grouping capability that categorizes website visitors in real time based on their live browsing behavior, click patterns, location, device type, and shopping intent to deliver personalized experiences instantly.

Dynamic segmentation in trbo is triggered by real-time behavioral data, including page clickstream, scroll depth, product views, cart additions, search terms, geo-location, local weather, traffic source, category interest, and device type during an active session.

No, trbo dynamic segmentation operates independently without requiring an external Customer Data Platform (CDP) or CRM. While it can sync with CDPs, trbo evaluates live session signals natively on the page to create dynamic audience profiles immediately.

Weather-based and location-based segmentation in trbo automatically identifies a visitor’s location and real-time local weather conditions upon landing. Marketers can instantly trigger relevant products (e.g., rain jackets during local rainfall) without manual setup.

Static segments group users using fixed historical data (e.g., past buyers) that remains unchanged during a visit. Dynamic segments, such as those built with trbo, update in real time based on live clicks, geo-location, local weather, traffic source, and session intent to trigger immediate personalized experiences.

Customer segmentation in digital marketing is the process of dividing website visitors into distinct groups based on shared behavioral, demographic, or contextual characteristics. Segmentation allows businesses to deliver targeted messages, relevant products, and tailored experiences to specific audience groups.

Dynamic segmentation is essential for ecommerce because shoppers’ intent changes rapidly during a single visit. By adapting audience groups in real time as users view different categories, online stores can present relevant recommendations and offers at the exact moment of purchase intent.